CA3081739A1 - Method and apparatus for identifying characteristics of trading cards - Google Patents

Abstract

Methods and apparatuses for detecting characteristics of a card include a method for identifying a foil card, comprising converting an image file depicting a card into a hue, saturation, value ("HSV") colour space, applying a value mask to exclude a group of pixels from analysis that do not form a principal maxima of the image, and comparing the number of remaining pixels against a threshold to determine whether the card is a foil card. In another aspect, a method for assigning a condition grading to a card comprises converting an image file depicting a diffusely illuminated card into an HSV colour space, isolating a uniform portion of the converted image file, applying a value mask to the converted image file to exclude pixels forming an undamaged portion of the card, and comparing the number of remaining pixels to a plurality of grading thresholds to assign a condition grading.

Description

METHOD AND APPARATUS FOR IDENTIFYING CHARACTERISTICS OF TRADING CARDS
Field The present disclosure relates to methods and apparatuses for identifying and sorting trading cards according to identified characteristics of the card; in particular, the present disclosure relates to methods and apparatuses for identifying foil trading cards and for assigning a condition grading to a trading card and sorting the cards based on those identified characteristics.
Background Collecting and trading cards is a popular hobby. Examples of different types of trading cards include, but are not limited to, PokémonTM trading cards, Magic: The GatheringTM trading cards, and trading cards for sports teams, such as National Hockey LeagueTM or Major League BaseballTM
trading cards. A market for trading cards exists, whereby collectors may sell or trade their trading cards with others. The value of a particular trading card is based on the characteristics of that trading card.
For an example, the literary and graphical content of the trading card, and its rarity compared to other cards, will impact the card's value.
Additionally, the condition of a trading card is an important factor of the card's value. For example, two copies of the exact same trading card may have different valuations based on the condition of each card.
For example, if one card is in mint or near mint condition, meaning that the card has not experienced any wear or damage, the mint or near mint card will be more valuable than a card that is in a played or damaged condition, meaning that the card has experienced wear and tear damage or other damage over time. Another trading card characteristic that impacts the card's value is whether the card is a foil card. Certain cards may include a special foil layer, which imparts a holographic look to the card under lighting conditions. Foil cards are rarer, and typically assessed at a higher value, than non-foil cards.
Trading card dealers may receive large volumes of used trading cards, which need to be sorted, categorized and valuated so that they can be sold in the trading card marketplace. Manually sorting the trading cards, to separate the foil cards from the non-foil cards, can be a tedious and time-consuming Date Recue/Date Received 2020-05-29 process. Furthermore, manually evaluating the condition of a plurality of trading cards so as to assign a value to the card can also be a time-consuming process. A further issue with the manual grading of a trading card's condition is that the process involves subjectivity, depending on a number of factors including the particular individual who is grading the condition of the card, the lighting conditions under which the assessment is made, and the necessity of exercising individual skill and judgment in applying the criteria for grading a card's condition. The assessment of a card's condition typically involves noting any damage to the card, caused either by accident or normal wear and tear, including but not limited to bends, tears or folds in the card, scuff marks or scratches on the card's surface, fading due to exposure to sunlight, and attempts to alter or fix the card so as to improve its appearance. An element of subjectivity is also introduced by the fact that the condition between trading cards can be quite variable, and it is difficult for an individual to consistently apply the same criteria to each and every trading card when deciding on which condition grading should be assigned to a particular card. As such, there is a need for a more objective method of assessing and grading the condition of a trading card.
To the applicant's knowledge, the prior art includes previous attempts to automate the grading of collectible objects. In one patent application, of which the applicant is aware, publication number US
2016/0210734 Al to Kass et al discloses a computerized system and method, using digital imaging devices and processes, to provide an objective, standardized, high resolution grading of collectible objects, such as trading cards. The system and methods described in Kass includes obtaining high-resolution images of a trading card, and comparing those high-resolution images to a reference image, referred to in Kass as a "Golden image". The Golden image is supplied by the manufacturer of the trading card. In one aspect of the Kass reference, an image subtraction routine is applied whereby all data points on a Golden image may be utilized to eliminate all identical data points on the front and back of the collectible card under analysis. The data that remains on the front or back of the trading card, after the elimination has occurred, is thereby determined to be one or more defects. In another aspect of the Kass reference, blob analysis employs mathematical methods to detect regions in a digital image that differ in properties, such as brightness or colour, compared to areas surrounding those regions. A blob is a region of a digital image in which some properties are constant or which vary within a prescribed range of values. Blob analysis, in Kass, is utilized to identify, quantify, and measure individual defects and the cumulative total defects area.

2 Date Recue/Date Received 2020-05-29 In another prior art reference of which the applicant is aware, US Patent No.
4,899,392 to Merton, a method and system for accurately and objectively evaluating the numismatic quality of a coin for purposes of identification is disclosed. In the Merton reference, central to the grading aspect of that invention is the exact numerical evaluation of any detracting marks on each side of the coin. In particular, each detracting mark on the coin is identified, located and measured. An assigned quantity, representative of the detracting significance of each mark, is then calculated by adjusting the measured surface area of the detracting mark by a factor representative of the relative grading importance of the area on the coin where the detracting mark is located.
While the systems and methods for automated grading, described in the Kass and Merton references, may be usefully employed for grading highly valuable trading cards and other collectibles, such systems and methods do not easily accomplish assigning a rough grading category to a large volume of trading cards to be processed within a relatively short timeframe. For example, in the trading card business for playing cards, such as PokémonTM and Magic: The GatheringTM trading cards, although there is a differentiation in the value of these cards based on their condition, it is typically not the case that such cards have an excessively high value in the hundreds or thousands of dollars for a single card, as may be the case in other types of trading card collectibles, such as vintage sport trading cards. Thus, there is a need in the industry for an objective and automated assignment of condition grading that can be applied to a large volume of trading cards within a relatively short period of time, so as to enable businesses to efficiently process and evaluate large batches of trading cards.
Furthermore, as mentioned previously, there is a need in the industry for efficiently and automatically identifying foil cards and distinguishing them from non-foil cards.
Summary In one aspect of the present disclosure, detection of a foil card as distinguished from a non-foil card is accomplished by generating an image of the card illuminated by a light source, for example, a point light source. The point light source, which may include a light emitting diode ("LED") light source, will cause the resulting image to include a principal maxima interference pattern, as a result of the diffraction grating of the foil layer of the card, if the trading card is a foil card.
Because the point light source is directed to small area of the card and the image is taken in an otherwise dark environment, the rest of

3 Date Recue/Date Received 2020-05-29 the image of the card will be dark relative to the bright area of the principal maxima. Whereas, an image taken of a non-foil card under the same lighting conditions will not include the principal maxima.
The method further includes processing the image file to convert the image file to a hue, saturation value ("HSV") colour space, whereby the HSV colour space can be used to isolate the value data for each pixel, and the value data for each pixel can then be further processed to detect whether a principal maxima is present or absent in the image file of the trading card. The algorithms thus employed will either identify the trading card as a foil card or not a foil card.
In another aspect of the present disclosure, trading card sets which include an identical portion or image across all of the trading cards within the set, such as a single, solid-colour border around the back face of the trading card, a method of assigning a condition grading to a plurality of cards utilizes the image data obtained from an image file of the back surface of each card. The portion of the image file that includes only the border, or a portion thereof, which is of uniform colour and appearance across all similar trading cards, is isolated for further analysis to determine what percentage of that border portion of the card is different from the uniform colour, which determination gives an approximation of the amount of damage or wear of the card. The calculation of the number of pixels in the image file, in the border portion of the trading card that are different, may be determined from an image file that has been converted to an HSV colour space, and evaluating the amount of pixels having a value integer that is less than a predetermined threshold. Thus, this method provides for objectively determining the condition .. grading of the trading card, without having to reference a Golden image file.
Advantageously, the condition grading method described herein may be employed without having to obtain an image of the entire surface of the trading card. For example, advantageously, rollers may be utilized to flatten the card against a platform when the image is taken, but because the methods employed herein do not require processing image data of the entire back surface of the card, images in which a portion of the card is obscured, for example by rollers, can still be processed by this method so as to assign a rough grading condition to the card. In some aspects of the present disclosure, a large batch of cards may then be sorted into different categories; for example, cards may be sorted based on whether they have been assigned a mint condition grading, a slightly played condition grading, or a heavily played condition grading. After having sorted a large batch of cards into the rough grading

4 Date Recue/Date Received 2020-05-29 categories, the most highly valued mint condition cards may be further rated by a human to assign a final valuation to them, without having to manually review the entire batch of cards. In other aspects of the present disclosure, a seller of used trading cards may assign a uniform pricing to each condition category, without having to spend any time further manually reviewing the cards.
In another aspect of the present disclosure, an apparatus is provided, the apparatus comprising an imaging chamber, a platform positioned within the imaging chamber and adapted to support an illuminated card, at least one diffuse light source positioned within the imaging chamber to illuminate the card, and a camera for taking an image of the illuminated card so as to generate the image file.
Advantageously, in some embodiments the apparatus may further include a conveyancing system and a card hopper, the conveyancing system adapted to convey a plurality of cards, one card at a time, from the card hopper to the platform. The conveyancing system may further be adapted to convey the plurality of cards, one card at a time, from the platform to a sorting deck, wherein the plurality of cards may be sorted at the sorting deck according to at least one characteristic of each card, the characteristic identified by an analysis of the image file of each card. In this manner, a large batch of cards may be loaded into the card hopper, and then the conveyancing system may automatically convey each card, one at a time, from the card hopper to the platform, where the image file is generated, and then the card may then be conveyed to a sorting deck where the card is then sorted into a respective category.
In another aspect of the present disclosure, a method for identifying a foil card includes the steps of obtaining an image file depicting an illuminated card; converting the image file into a hue, saturation, value ("HSV") colour space; applying a value mask to the converted image file so as to exclude a first group of pixels from analysis, each pixel of the first group of pixels having an integer less than a predetermined foil threshold value, said foil threshold value selected to identify said first group of pixels that does not form a principal maxima of the image file; and determining a number of remaining pixels and comparing the number of remaining pixels against a predetermined threshold number of remaining pixels, wherein if the number of remaining pixels exceeds the threshold number of remaining pixels the illuminated card is identified as a foil card. In a preferred embodiment, the image file depicting an illuminated card is obtained under lighting conditions whereby the card is illuminated by a point light source and the card is positioned outside a field of view of the point light source.

5 Date Recue/Date Received 2020-05-29 In another aspect of the present disclosure, a method for assigning a condition grading to a card comprises the steps of: obtaining an image file depicting a diffusely illuminated card, the image file depicting at least a portion of an extent of the illuminated card; converting the image file into an HSV
colour space; eliminating a nonuniform portion of the converted image file from analysis so as to isolate a uniform portion of the converted image file; applying a value mask to the converted image file so as to exclude a first group of pixels of the uniform portion of the image file from analysis, each pixel of the first group of pixels having an integer less than a predetermined threshold, wherein the threshold is selected to identify said first group pixels representing an undamaged card portion; and determining a number of remaining pixels and comparing the number of remaining pixels against a plurality of grading thresholds so as to assign a condition grading of the illuminated card. In another aspect of the present disclosure, the method of identifying the foil card may either be performed alone, or in combination with the method for assigning a grading condition to a card. Similarly, the method of assigning a grading condition to a card may either be performed alone, or in combination with the method for assigning a grading condition to a card.
An apparatus for performing either or both of the methods for identifying a foil card and/or assigning a condition grading to a card includes an imaging chamber, the imaging chamber adapted to substantially exclude any light from an external light source from entering the imaging chamber; a platform positioned within the imaging chamber and adapted to support the illuminated card; a diffuse light source, the diffuse light source positioned within the imaging chamber to illuminate the illuminated card; and an image capture device for taking an image of the illuminated card so as to generate the image file.
Brief Description of the Figures Figure 1 is a partially cutaway view of an embodiment of the card sorting apparatus in accordance with the present disclosure;
Figures 2A and 2B are a logic flow diagram depicting an embodiment of the method for identifying foil cards, in accordance with the present disclosure;

6 Date Recue/Date Received 2020-05-29 Figures 3A and 3B are a logic flow diagram depicting an embodiment of the method for identifying a grading category for a trading card, in accordance with the present disclosure;
Figure 4A is a 100x magnified photograph of a foil layer of a foil trading card;
Figure 4B is a 1000x magnified photograph of the foil layer shown in Figure 4A;
Figure 4C is a close-up view of a portion of the foil layer shown in Figure 4B, in which diffraction grating lines of the foil layer are visible;
Figures 5A and 5B are examples of an original image file and a converted image file depicting a foil card, respectively, wherein the original image file shows rainbow-coloured principal maxima and the converted file image displays pixels having a high integer value depicted in white;
Figures 5C and 5D are examples of an original image file and a converted image file depicting a non-foil card, respectively, wherein the converted file image displays pixels having a high integer value depicted in white;
Figure 6A is an example of an original image file of a near mint card;
Figure 6B is a highlighted portion of the extent of the near mint card depicted in Figure 6A;
Figure 6C is an example of a converted image file of the highlighted portion of the extent of the near mint card depicted in Figure 6A;
Figures 6D ¨ 6F are negatives of the images shown in Figures 6A ¨ 6C, respectively;
Figure 6G is an example of an original image file of a heavily played card;
Figure 6H is a highlighted portion of the extent of the heavily played card depicted in Figure 6A;
Figure 61 is an example of a converted image file of the highlighted portion of the extent of the heavily played card depicted in Figure 6A;
Figures 6J ¨ 6L are negatives of the images shown in Figures 6G ¨61, respectively;
Figure 7A is a partially cutaway perspective view of an embodiment of the card sorting apparatus including a sorting deck;
Figure 7B is a perspective view of an embodiment of the card sorting apparatus including a sorting deck and a card hopper extension;

7 Date Recue/Date Received 2020-05-29 Figures 8A and 8B are images of the front and back surfaces of an example of a Magic: The GatheringTM
trading card; and Figure 9 is a schematic drawing, showing the lighting conditions for acquiring an image of a trading card in one embodiment of the present disclosure.
Detailed Description Foil Detection Method In one aspect of the present disclosure, a method for automatically identifying a foil card, as distinguished from a non-foil card, is provided. As described above, in the trading card business, some trading cards are provided with a foil layer overlaid by a graphics layer of the card, thereby producing a holographic effect to the appearance of the card under various lighting conditions. The foil layer consists of a diffraction grating, so that light shining on the card will produce an interference pattern including principal maxima. Figure 4A is a magnified image of a foil layer 10 of a trading card, taken at 100x magnification. In the image displayed in Figure 4A, a pair of calipers 20, 20 are calibrated at a 1 mm distance D apart from each other. Figure 4B is a further magnified image of the foil layer depicted in Figure 4A, taken at 1000x magnification. Figure 4C is a close up of a portion of the magnified image of Figure 4B, in which a plurality of horizontal grooves 12 and vertical grooves 14 of the foil layer are visible. Thus, the pattern of horizontal and vertical grooves 12, 14 of the foil layer 10 create a diffraction grating.
When a foil card is exposed to a light source, the diffraction grating of the foil layer 10 will produce a diffraction pattern including constructive interference patterns presenting as principal maxima, which may be perceived as a rainbow pattern across the surface of the card when the light source is composed of white light. However, when a trading card that does not have a foil layer, otherwise referred to herein as a non-foil card, is exposed to a light source, no interference pattern will be detected across the surface of the card, because the non-foil card does not have the foil layer including a diffraction grating.
However, under most lighting conditions, the glossy surface of the card will also reflect light.
Advantageously, the applicant has discovered that taking images of trading cards that are illuminated by a point light source in an otherwise darkened environment, wherein the surface of the card is positioned

8 Date Recue/Date Received 2020-05-29 outside the field of view of the point light source, produces an image of the card in which the bright principal maxima will be clearly visible, generally unobscured by reflections of the light source, save for a small reflection of the point light source limited to a small area of the card's surface. Whereas, images taken of a non-foil card, under the same lighting conditions, may produce an image in which only a small bright spot representing a direct reflection of the point light source is visible against an otherwise darkened card surface. Such images are captured substantially in the absence of other light sources, such that the principal maxima will be clearly distinguishable in the resulting image of the trading card, as compared to the images taken of non-foil cards. The applicant has also found that a method of processing the image file of the trading card, so as to separate the pixels that are part of the principal maxima from the pixels that do not form a part of the principal maxima, enables a way of automatically detecting whether a trading card is a foil card or not a foil card.
With reference to Figures 2A and 2B, in an embodiment of the method 100 to detect a foil card, an image of the card under analysis is ideally acquired in an environment where the card is illuminated by a point source of light. As will be appreciated by a person skilled in the art, point light sources may include: lasers (including but not limited to laser lamps), incandescent lamps (including but not limited to gas lamps and carbon arc lamps), monochromatic light sources, gas discharge lamps (including but not limited to fluorescent lamps, metal halide lamps, and plasma lamps), LEDs (including but not limited to LED lamps), and other light sources known to a person skilled in the art.
In a preferred embodiment, the surface of the card is positioned so as to be outside the field of view of the point light source, such as shown in Figure 9, wherein a point source of light 52, such as an LED
light, has a field of view 52a, represented by the shaded grey area. The field of view 52a represents the area of light cast by the point light source 52 that is within a given range of brightness, measured in lumens. A surface 50a of card 50 is positioned so as to be outside the field of view 52a of the point light source 52. A reflection 52c of the point light source 52 may be visible on the surface of the card 50a, such reflection 52c caused by a ray of light 52b cast from the point light source 52. While the reflection 52c will typically appear as a bright spot on all cards, including foil and non-foil cards, principal maxima will only be visible as bright spots on the card's surface if the card is a foil card. Images of the card may be captured by an image capture device, such as a camera 54 having a field of view 54a. Advantageously, when images are taken in the lighting conditions described above and shown in Figure 9, the rest of the surface of the card will appear dark, relative to the bright spots of the principal maxima and the light source reflection 52c. As will be

9 Date Recue/Date Received 2020-05-29 explained further below, it is this feature of the resulting image files that enable the methods described herein to distinguish foil cards from non-foil cards, in embodiments of the present disclosure.
A white LED light source will produce a rainbow coloured principal maxima, due to the interference pattern created by the different light wavelengths that comprise the white light source. However, it will be appreciated by a person skilled in the art that principal maxima may also be created by a point source of light that is monochromatic or which is not a white light source, although such resulting diffraction patterns of principal maxima will not present in rainbow colour, but rather will present as the same colour as that of the point light source, appearing as a brightened interference pattern across a portion of the trading card's surface. This method may be performed on such images that are obtained separately from the computer system that is performing the foil detection method. For example, a database of trading card images, taken under the lighting conditions described above, may be obtained from an external source and then processed by a computer system executing software that performs the foil detection method. In other embodiments, as will be further described below, a card sorting apparatus may be provided which both takes the images of the trading cards to be analyzed, and which includes an integrated computer system executing the software that performs the foil detection method.
Again referring to Figures 2A and 2B, once an image of the card under examination has been obtained at step 108, where the card is illuminated by a point light source in an otherwise darkened environment, the image may either be converted into a digital image file, or otherwise the image may already be a digital image, such as where the image acquisition device is a digital camera.
The digital image file is then converted into an HSV colour space at step 110, whereby a colour histogram is created and each pixel is assigned three integers representing the pixel's hue, saturation, and value.
The converted image file is then masked, at steps 114 and 116, by applying a value mask so as to exclude any pixels that have a value integer less than a predetermined foil threshold. An example of an image of a foil card is shown in Figures 5A and 5B, and of a non-foil card shown in Figures 5C and 5D. As can be seen in the foil card image of Figure 5A, a reflection 52c of the point light source 52 appears as a bright spot, and principal maxima 56 appear as other bright portions of the image. As can be seen in Date Recue/Date Received 2020-05-29 Figure 5C, which is an image of a non-foil card taken under the same lighting conditions, only the point source light reflection 52c and some scattered random bright areas of the card 58 are visible in the image.
A predetermined foil threshold may be selected so as to identify pixels that do not form a portion of the principal maxima of the image of the trading card. For example, in the HSV
colour space, the value of each pixel indicates the relative brightness of that pixel. In the lighting conditions under which the image of the trading card is taken, because the card was illuminated by a point light source, the only pixels in the image which will have a high integer for the pixel's value, representing the brightness of the pixel, will be those pixels which form a portion of the principal maxima or, possibly, a portion of the reflection of the point light source, because the rest of the image will be relatively dark under the described lighting conditions. Examples of converted images, depicting a foil card and a non-foil card, are shown in Figures 5B and 5D respectively. In the examples of converted images shown in Figures 5B
and 5D, only the pixels having a value integer that exceeds the value threshold are shown in white.
Figures 5B and 5D also depict converted images in which the bright spot depicting the point source reflection 52c, which bright spot is not relevant to the detection of a principal maxima because it will appear in all images, has been masked from the converted images in Figures 5B
and 5D so as to exclude them from further analysis in the present method, such an optional step occurring, for example, in step 114 of method 100. As may be seen in a comparison of Figure 5B, depicting a foil card, as compared to Figure 5D, depicting a non-foil card, the white areas representing pixels that exceed the value threshold are much greater in the foil card image of Figure 5B as compared to the non-foil card image of Figure 5D. Therefore, by counting the remaining pixels at step 118, which have been identified as bright pixels based on the high integer value of each one of those pixels, one may distinguish between the foil and non-foil cards. At step 120, the number of bright pixels counted at step 118 is compared against a predetermined number of high value pixels, such predetermined threshold number selected to indicate that the image file contains a principal maxima. Alternatively, rather than calculating an absolute number of remaining pixels, this calculation may also be done to determine the percentage of remaining pixels, as compared to the overall number of pixels in the area under consideration in the image file.

Date Recue/Date Received 2020-05-29 In some embodiments, the method may optionally include obtaining a second image of the card, at step 102, whereby the card in the second image is illuminated by diffuse light source. The diffuse light source will produce an image of the trading card in which the entire surface of the trading card is substantially evenly lit by the diffuse light source. A contour detection algorithm, as would be known to a person skilled in the art, may then be applied to the second image of the trading card at step 106, so as to identify the extends and boundaries of the illuminated card in the second image file to thereby generate a contour data set. As used herein, the term "extent" refers to the edges of the physical trading card, and the term "boundary" refers to other straight line features of a trading card's image, including for example the boundary 48 depicted in an image of the rear face of a Magic: the GatheringTM card shown in Figure 88. The contour data set may then be applied to the second image file so as to exclude a second group of pixels from the image file, whereby the second group of pixels comprises those pixels located outside the extents of the illuminated card depicted in the image file. The step may therefore increase the reliability of the foil card detection method, because utilizing the contour detection algorithms enables the elimination of the surrounding background from the image, such that the analysis performed on the image is only performed on those portions of the image that are a part of the trading card itself, and not the portions of the image depicting the surrounding environment, such as the surface of the platform on which the trading card was resting when the image was taken. An example of a contour detection algorithm, not intending to be limiting, includes canny edge detection, as would be known to a person skilled in the art. The contour data set may be saved for future application, at step 106a.
In other embodiments, the method may further comprise a step of correcting a spherical distortion of the image file at step 104, such spherical distortion being caused by the curvature of the lens.
Correcting the spherical distortion of the image file may increase the accuracy of the foil card detection .. method, because the image file, once corrected for spherical distortion, is a more accurate representation of the percentage of the card surface which contains bright spots as opposed to dark spots, thereby increasing the accuracy of the method by measuring the percentage of the card surface occupied by the principal maxima in an image of a foil card. Advantageously, the second image of the card taken under a diffuse light source may also be used for other identification and card sorting methods, such as automated detection of the identity of the card by comparing the second image to a database of trading card images.

Date Recue/Date Received 2020-05-29 A further application of applying the contour data set to the image file is to optionally identify and correct an orientation of the illuminated card depicted in the image file, for example by rotating the image file so as to reorient the card to a selected orientation, at step 112.
In other applications, detecting the orientation of the card may be useful so as to sort a plurality of cards by their orientation.
As will be explained further below, an example of why it would be useful to have cards sorted by their orientation includes when you have a large batch of cards which are mixed in any number of orientations, and a particular sorting method depends on taking images of a set of cards wherein every card is in the same orientation. For trading cards, there are four possible orientations: the north and south orientations of the front surface of the card; and similarly, the north and south directions of the rear surface of the card, as indicated for example in Figures 8A and 8B, which shows the front and rear surfaces of the cards in the north orientation, respectively.
Applying the contour data to the second image file, may advantageously be used to sort the cards into different orientations, for example by utilizing knowledge of a trading card's layout which is common between all trading cards within a trading card set. For an example, not intending to be limiting, Magic:
The GatheringTM trading cards all have a similar layout, whereby the front surface 30 of the card includes a title box 32 at the top, an art box 34 underneath the title box, a type line box 36 immediately underneath the art box, and a text box 38 beneath the type line box, as shown for example in Figure 8A.
.. Automated detection software may thereby parse out the elements of the layout of a Magic: The GatheringTM card's front surface, and use that information to identify and sort the orientation of the card by detecting, for an example, the position of the art box relative to the type line box, both of which have a dimension and positioning that is substantially constant between all Magic: The GatheringTM
cards. As a further example, the back surface of a Magic: The GatheringTM card is substantially identical across all such cards. The back surface 40 of a Magic: The GatheringTM card includes a black border 42, and then an interior image with five coloured spheres beneath the word "Magic"
46 in a stylized font.
Similarly, an analysis of an image of the back of a Magic: The GatheringTM
card is easily differentiated from the front surface of the Magic: The GatheringTM card due to their different layouts, and furthermore, the orientation of the back surface of the magic card is detectable by, for example, detecting the relative orientation of the five coloured spheres 44 relative to the word "Magic" 46. It will be appreciated by a person skilled in the art that any number of characteristics that are identical across Date Recue/Date Received 2020-05-29 a set of trading cards may be utilized in order to detect and/or correct for the orientation of a trading card depicted in a given image.
Condition Assessment Method .. In another aspect of the present disclosure, a method for assigning a condition grading to a card is provided. As described above, in the trading card industry, the value of a trading card is informed by the characteristics of the card, one of those characteristics being the condition of the card. Different grading scales and methods for grading the condition of a card may be used.
However, for the purposes of illustration and not intending to be limiting, the condition grading for trading cards may include three or four grades indicating the relative condition of the card. For example, the condition of a card may be graded as being mint or near mint condition, meaning that the card has not experienced any damage or wear and tear. A mint or near mint condition is the best possible condition that a card can be in. Other condition grades may include a slightly played condition and a heavily played condition, whereby a slightly played condition indicates that the card has been lightly played and has experienced minimal .. wear and tear; whereas a card graded as heavily played indicates that the card has experienced more substantial wear and tear damage due to use over a longer period of time.
Other grading scales, including fewer or more than three levels or grades, also exist and may be utilized with the automated condition grading method described herein.
As is appreciated by a person skilled in the art, there is a level of subjectivity that goes into assigning a condition grading to a card. However, the applicant has discovered that there are ways of analysing a histogram of a digital image of the card, whereby objective criteria for assigning a grading condition may be applied to the card. Although this method may not provide for a definitive grading of the condition of a card, advantageously this method provides for a relatively quick and simplified method of automatically assigning a condition grading to a card, thereby enabling a relatively quick sorting of a large batch of cards according to their approximate condition grading.
Advantageously, this method is based on focusing on a uniform portion of a card, rather than attempting to analyse the entire surface of the card, as is described in other methods known in the prior art.

Date Recue/Date Received 2020-05-29 In one embodiment of the present disclosure, a method for automated condition grading 200 comprises obtaining a digitized image file of an image of the trading card taken under diffuse lighting conditions.
An example is shown in Figures 6A to 6L, with a near mint condition card depicted in Figures 6A ¨ 6F and a heavily played card depicted in Figures 6G ¨ 6L. The image file may be produced by a specialized apparatus for the purpose of sorting and identifying trading cards, or else the image file may be obtained from a database or other sources. The image file includes an image of at least a portion of the trading card's surface. In one aspect, the image is preferably an image of the back or rear surface of the trading card, whereby the back surface image is consistent amongst all trading cards within a set of trading cards. For example, in the Magic: The GatheringTM trading card series, the rear image of every trading card consists of a black border which is solid in colour, the black border surrounding an image including the word "Magic" in stylized lettering above a group of five coloured spheres, such as shown in Figures 6A, 6G and 88.
In one aspect, the method includes the step of masking or otherwise eliminating portions of the image which do not include the solid colour black border. In other words, the method works by analysing only the solid colour border of the rear surface of the card. In some embodiments, only a portion of the solid colour border may be analysed, such as shown by the highlighting ovals 60 shown in Figures 6A ¨ 6L.
Other trading card series, such as PokémonTM trading cards, for example, may also have a solid colour border which is consistent across all rear images of the PokémonTM card series. However, it will be appreciated by a person skilled in the art that the feature of the card image to be analysed is not necessarily limited to a solid colour border; for an example, another solid colour feature that is common amongst all surfaces of the trading card series may provide the feature to be analysed in the presently described condition grading method.
Upon obtaining an image file depicting a card, such as a rear surface of a trading card wherein at least a portion of the border is visible, in step 202, the method then proceeds to a step of correcting for spherical distortion of the image in step 204. In step 206, the image file is prepared for analysis by applying contour detection so as to define the outer boundaries of the card, as well as the solid colour border of the card. In some embodiments, the contour detection routine applied to the image file may include canny edge detection. In step 208, contour data that has been generated from the contour Date Recue/Date Received 2020-05-29 detection routine is saved. In the next step, at 210, the corrected image is converted to HSV colour space, to thereby generate a histogram of the image file. In step 212, the saved contour data is optionally used to reduce the area under consideration for the analysis of the image to only those pixels residing within the solid colour border of the card. Advantageously, this will simplify the analysis by excluding the irrelevant portions of the image file, including any surrounding environment depicted in the image, such as the platform or surface on which the trading card was positioned when the image was taken. However, step 212 is optional, and it will be appreciated by a person skilled in the art that the image file may still be analysed without excluding the irrelevant portions of the image file as is done by applying the contour data in step 212. Another optional step would be to crop the image in the image file, so as to only include the solid colour border area of the card for further analysis.
In step 214, masking is applied to the image such that only areas of the card which are known to contain solid uniform colouring, such as the outer border of the rear face of the card, are considered for analysis. Such masking may involve, for example, excluding all of the pixels that are outside the defined distance between the edge of the card and the inner surface of the base of the card. For example, in a Magic: The GatheringTM card, the border on a rear face of the card is typically 0.5 cm inwardly from the edge of the card, around the entire order of the card. Therefore, in this case, the masking may involve masking all the pixels that fall outside of the 0.5 cm border the runs around the border of the cart. In other embodiments, only a portion of the solid colour border may be considered in the analysis, such as the portion of the border highlighted by ovals 60 in Figures 6A ¨ 6L.
At step 216, a second masking operation is applied, wherein a value mask is applied to exclude any pixels with a value integer falling outside a predetermined range. The predetermined value range may be, for example, the range of pixels having a value between a value threshold and the maximum value of .. 256 for pixel. An example of the histogram produced after the second masking operation 216 is applied is shown in Figures 6C, 6F, 61 and 6L, whereby Figures 6C and 61 show the results of the second masking operation applied to the original image of the near mint and heavily played cards, respectively, and Figures 6F and 6L show the negatives of the Figures 6C and 61, so as to make the results of the second masking operation more clearly visible in the Figures. The value threshold may be selected so as to exclude all pixels that are below the value threshold, thereby indicating pixels which are a part of the Date Recue/Date Received 2020-05-29 undamaged border, because such pixels are darker than the pixels falling within the predetermined value range. Because a solid colour border is typically perceived as a darker colour, such as black or dark blue, pixels which fall outside of that dark value range indicate pixels which form a portion of a damaged border, for example damage which shows portions of the dark coloured border that have been worn away through play, including but not limited to scratches, chips or scuff marks on the card. As best seen in Figures 6F and 6L, depicting the negative images of the result of the second masking operation for the near mint and heavily played cards, respectively, the damaged portion 62 of the near mint card, in Figure 6F, is barely visible, whereas the damaged portion 62 of the heavily played card, shown in Figure 6L, is significant, appearing as several spots and vertical lines.
After applying the second masking operation in step 216, the method proceeds to step 218 wherein the number of remaining pixels under consideration is determined, and that number is then compared to a plurality of grading thresholds so as to assign a condition grading for that card. For example, in the routine that is shown in Figure 3B, in step 220 a first threshold may be selected for indicating a mint or near mint condition threshold. Without intending to be limiting, if the relative number of remaining pixels is less than 2% of the total number of pixels under consideration, this would indicate that the border is relatively undamaged, due to the low proportion of pixels which are lighter than the solid colour border. Therefore, if the mint or near mint threshold was set at 2%, the method would inquire whether the number of remaining pixels exceeds the mint or near mint threshold. In the case that the number of remaining pixels does not exceed the threshold, at step 222 condition grading of mint or near mint condition would be assigned to that card.
However, in the event that the number of remaining pixels does exceed the mint or near mint threshold, set in this example at 2%, at step 224 the method will then query whether the image contains more pixels than the slightly played threshold. For an example, without intending to be limiting, the slightly played threshold may be selected at 10% of the remaining pixels relative to the total number of pixels under consideration. In the case that the number of remaining pixels does not exceed the 10%
threshold, then at step 226 the card would be assigned the slightly played condition grading. However, in the case that the number of remaining pixels does exceed the slightly played threshold, set for example at 10%, then the routine with proceeds to step 228 in which case that card would be assigned Date Recue/Date Received 2020-05-29 the heavily played condition grading. It will be appreciated by a person skilled in the art that the examples of thresholds and condition gradings provided above are provided for illustrative purposes only and are not intended to be limiting. It will further be appreciated by a person skilled in the art that more or less condition gradings may be determined through this method, and that the particular thresholds assigned for each condition grading may also be determined and come within the scope of the present disclosure.
Although the present disclosure discusses the conversion of the digital image file to an HSV colour space, as described above at step 110 of the foil detection method 100 or at step 210 of the card grading method 200, the use of the HSV colour space is provided as an example and it will be appreciated by a person skilled in the art that the methods described herein are not limited to use of the HSV colour space. For example, it will be appreciated that converting the digital image file to a colour space other than an HSV colour space, and then using the resulting colour space characteristics of each pixel to detect card damage and/or the presence of a foil card, may be utilized in the methods disclosed herein and is included in the scope of the present disclosure.
Card Sorting Apparatus In another aspect of the present disclosure, a card sorting apparatus 300 is provided. With reference to Figures 1, 7A and 7B, the card sorting apparatus 300 includes an enclosure 302, the enclosure 302 being preferably constructed so as to exclude all external light sources from penetrating the enclosure, so that the lighting conditions within the card sorting apparatus 300 may be precisely controlled depending on whether diffuse lighting conditions or point light conditions are required.
Within the enclosure 302, there is supported a platform 304. The platform 304 is preferably constructed of a transparent material, such as glass. The platform 304 is adapted for supporting trading cards to be imaged by an image capture device 306. The image capture device 306 may include, for example, a digital camera, or any other device suitable for capturing an image of a trading card. In a preferred embodiment, the card sorting apparatus 300 may include an upper camera 306a positioned above the platform 304, and a lower camera 306b positioned beneath the platform 304 for capturing the other side of the trading card when it is on the platform 304. Advantageously, this configuration of the card sorting apparatus enables for simultaneously taking an image of the upper and lower faces of the card.

Date Recue/Date Received 2020-05-29 In order to obtain clear images of the trading card, it is important to ensure that the card is entirely flat on the platform 304 when taking an image. This can be particularly challenging in respect of foil cards, as foil cards are commonly curled in one direction due to how humidity will impact the different layers .. of the card; for example, the foil layer as compared to the card stock layer of the card may expand or contract at different rates in different humidity conditions, thereby causing the card to curl. Therefore, in some embodiments of the card sorting apparatus 300, advantageously there is provided a pair of rollers 308 positioned adjacent the platform, which rollers 308 are configured to press the trading card against the platform 304, thereby flattening the card against the platform 304 when an image is to be taken. Advantageously, for methods described herein in which it is important to run an analysis on a whole image of the trading card, whereby the trading card is not obscured, the lower camera 300 and 68 is able to take an image of an unobscured surface of the trading card, since the rollers 308 are positioned on the opposite side of the platform 304. Furthermore, for methods which do not require an unobscured image of the trading card, for example the condition grading method described herein, it does not matter that the pair of rollers 308 is obscuring a portion of the trading card surface when an image is taken by the upper camera 306a. Thus, the card sorting apparatus 300 may be utilized for performing more than one method described herein at the same time.
Advantageously, in some aspects of the present disclosure, lighting sources may also be supported .. within the enclosure 302, for illuminating the trading card when it is on the platform 304. For an example, a diffuse lighting source 310 may include a lighting source and a series of diffusion panels 310a. A point lighting source 312 may also be provided, positioned such that the card surface is outside a field of view of the point light source, for example as shown in the schematic drawing of Figure 9.
In an embodiment of the present disclosure, advantageously the card sorting apparatus 300 further includes a conveyancing system and a card hopper. For example, a card hopper 316 is configured to receive a plurality of trading cards. Optionally, a card hopper extension 330 may be attached to the entrance of the card hopper 316 so as to add capacity to the card hopper 316, as shown in Figure 78. A
set of driving rollers 318 are positioned so as to come through the floor 316b of the hopper 316, the driving rollers 318 configured to drive one trading card at a time through a narrow slot 316a through Date Recue/Date Received 2020-05-29 which the trading card passes to a second set of driving rollers 320. The rollers 320 convey the trading cards, one card at a time, to the platform 304, and then after one or more images of the trading card have been captured, for example by the cameras 306a, 306b, the rollers 308 convey the trading cards toward a third set of driving rollers 322 and then through the exit slot 324.
The exit slot 324 may lead to a collection bin (not shown), or optionally, the exit slot 324 may lead to a sorting deck 340, such as shown in Figures 7A and 7B, as would be known to a person skilled in the art.
A sorting deck 340 may be utilized to further sort the cards into certain categories; for example, not to be limiting, the sorting deck may sort the trading cards into foil and non-foil piles. As another example, not intended to be limiting, the sorting deck may sort the cards into two or more piles indicating the condition grading, card type, card price, card orientation, etc that has been assigned to each card. It will be appreciated by a person skilled in the art that the sorting deck may be used to sort the trading cards according to any number of characteristics of the trading cards, and the examples herein are not intended to be limiting.

Date Recue/Date Received 2020-05-29

Claims (37)

WHAT IS CLAIMED IS:

1. A method for identifying a foil card, the method comprising:
a. obtaining an image file depicting an illuminated card;
b. converting the image file into a hue, saturation, value ("HSV") colour space;
c. applying a value mask to the converted image file so as to exclude a first group of pixels from analysis, each pixel of the first group of pixels having an integer less than a predetermined foil threshold value, said foil threshold value selected to identify said first group of pixels that does not form a principal maxima of the image file;
d. determining a number of remaining pixels and comparing the number of remaining pixels against a predetermined threshold number of remaining pixels, wherein if the number of remaining pixels exceeds the threshold number of remaining pixels the illuminated card is identified as a foil card.

2. The method of claim 1, wherein the card is illuminated by a point light source; and wherein the card is positioned outside a field of view of the point light source.

3. The method of claim 1, wherein the method further comprises the steps of:
obtaining a second image file of the illuminated card, wherein the card is illuminated by a diffuse light source;
applying contour detection to the second image file so as to identify an extent of the illuminated card in the second image file and thereby generate a contour data set; and applying the contour data set to the second image file so as to exclude a second group of pixels from analysis, the second group of pixels comprising pixels located outside the extent of the illuminated card depicted in the image file.

Date Recue/Date Received 2020-05-29

4. The method of claim 3, wherein the step of applying contour detection includes applying canny edge detection to the second image file.

5. The method of claim 3, wherein the method further comprises the step of correcting a spherical distortion of the second image file.

6. The method of claim 3, further comprising the steps of:
applying the contour data set to the second image file so as to identify an orientation of the illuminated card depicted in the second image file; and correcting the orientation of the illuminated card to a selected orientation by rotating the second image file so as to re-orient the card in the selected orientation.

7. The method of claim 2, wherein the method further comprises the step of applying a light mask to the image file so as to exclude a third group of pixels, wherein each pixel of the third group of pixels has an integer exceeding a predetermined light threshold, said light threshold selected to identify each pixel of the third group of pixels that forms a reflection of the point light source.

8. The method of claim 1, wherein the step of applying a value mask to the first group of pixels further includes applying at least a second mask, the at least a second mask selected from a group comprising: a hue mask; a saturation mask; and wherein a predetermined threshold value of any one of the hue mask and the saturation mask is selected to identify a pixel does not form a portion of the principal maxima.

9. An apparatus for performing the method of claim 1, the apparatus comprising:
an imaging chamber, the imaging chamber adapted to substantially exclude any light from an external light source from entering the imaging chamber;
a platform positioned within the imaging chamber and adapted to support the illuminated card;

Date Recue/Date Received 2020-05-29 a point light source, the point light source positioned within the imaging chamber such that the platform is positioned outside the field of view of the point light source;
and an image capture device for capturing an image of the illuminated card so as to generate the image file.

10. The apparatus of claim 9 further comprising a conveyancing system and a card hopper, the conveyancing system adapted to convey a plurality of cards, one card at a time, from the card hopper to the platform.

11. The apparatus of claim 10, wherein the conveyancing system is further adapted to convey the plurality of cards, one card at a time, from the platform to a sorting deck;
and wherein the plurality of cards may be sorted at the sorting deck according to at least one characteristic of each card, the characteristic identified by an analysis of the image file of each card.

12. The apparatus of claim 11, wherein the at least one characteristic is selected from a group comprising: card type, card orientation, foil card, card price, condition grading.

13. The apparatus of claim 9 wherein the platform comprises a transparent material, and wherein the image capture device includes a first camera positioned above the platform and a second camera positioned below the platform, the first camera arranged to take a first image of a first side of the card and the second camera arranged to take a second image of a second side of the card.

14. A method for assigning a condition grading to a card, the method comprising:
a. obtaining an image file depicting a diffusely illuminated card, the image file depicting at least a portion of an extent of the illuminated card;

Date Recue/Date Received 2020-05-29 b. converting the image file into a hue, saturation, value ("HSV") colour space;
c. eliminating a nonuniform portion of the converted image file from analysis so as to isolate a uniform portion of the converted image file;
d. applying a value mask to the converted image file so as to exclude a first group of pixels of the uniform portion of the image file from analysis, each pixel of the first group of pixels having an integer less than a predetermined threshold, wherein the threshold is selected to identify said first group pixels representing an undamaged card portion; and e. determining a number of remaining pixels and comparing the number of remaining pixels against a plurality of grading thresholds so as to assign a condition grading of the illuminated card.

15. The method of claim 14, wherein the method further comprises the step of applying contour detection to the image file to identify said at least a portion of the extent of the illuminated card in the image file and thereby generate a contour data set delineating said extent; and applying the contour data set to the image file so as to reduce the image file to a border group of pixels, said border group of pixels located proximate the extent of the card.

16. The method of claim 15, wherein the step of applying contour detection includes applying canny edge detection to the image file.

17. The method of claim 15, wherein the method further comprises the step of correcting a spherical distortion of the image file.

18. The method of claim 16, wherein the border group of pixels is defined as an area of the card consisting of pixels having substantially uniform HSV characteristics as compared to adjacent pixels when the card is a mint condition specimen.

Date Recue/Date Received 2020-05-29

19. The method of claim 14, wherein the image file consists of an image of a rear face of the card, wherein the rear face of each card in a set of cards comprises a substantially identical image.

20. The method of claim 14, wherein the step of applying a value mask to the first group of pixels further includes applying at least a second mask, the at least a second mask selected from a group comprising: a hue mask, a saturation mask; and wherein a predetermined threshold of any one of the hue mask and the saturation mask is selected to identify a pixel that forms the uniform portion of the image file.

21. The method of claim 14, wherein the plurality of grading thresholds includes at least a mint threshold, a slightly played threshold and a heavily played threshold; and wherein when the number of remaining pixels is less than or equal to the mint threshold, the card is assigned a mint condition grading; and wherein when the number of remaining pixels is greater than the mint threshold and less than or equal to the slightly played threshold, the card is assigned a slightly played condition grading;
and wherein when the number of remaining pixels is greater than the heavily played threshold, the card is assigned a heavily played condition grading.

22. An apparatus for performing the method of claim 14, the apparatus comprising:
an imaging chamber, the imaging chamber adapted to substantially exclude any light from an external light source from entering the imaging chamber;
a platform positioned within the imaging chamber and adapted to support the illuminated card;
a diffuse light source, the diffuse light source positioned within the imaging chamber to illuminate the illuminated card; and Date Recue/Date Received 2020-05-29 an image capture device for taking an image of the illuminated card so as to generate the image file.

23. A method for identifying characteristics of a trading card, the method comprising:
a. obtaining a first image file depicting a diffusely illuminated card, the first image file depicting at least a portion of an extent of the illuminated card;
b. converting the first image file into a hue, saturation, value ("HSV") colour space;
c. applying a value mask to the converted first image file so as to exclude a first group of pixels from analysis, each pixel of the first group of pixels having an integer less than a predetermined foil threshold value, said foil threshold value selected to identify said first group of pixels that does not form a principal maxima of the image file;
d. determining a first number of remaining pixels and comparing the number of remaining pixels against a predetermined foil threshold number of remaining pixels, wherein if the number of remaining pixels exceeds the threshold number of remaining pixels the illuminated card is identified as a foil card;
e. eliminating a nonuniform portion of the converted image file from analysis so as to isolate a uniform portion of the converted image file;
f. applying a second value mask to the converted image file so as to exclude a second group of pixels of the uniform portion of the image file from analysis, each pixel of the second group of pixels having an integer less than a predetermined condition threshold, wherein the condition threshold is selected to identify said second group pixels representing an undamaged card portion; and Date Recue/Date Received 2020-05-29 g. determining a second number of remaining pixels and comparing the second number of remaining pixels against a plurality of grading thresholds so as to assign a condition grading of the illuminated card.

24. The method of claim 23, wherein the method further includes obtaining a second image file depicting the illuminated card, wherein the card is illuminated by a point light source and wherein the card is illuminated by a point light source and wherein the card is positioned outside a field of view of the point light source; and wherein the steps b to d of claim 23 are performed on the second image file.

25. The method of claim 23, wherein the method further comprises the steps of:
applying contour detection to the first image file so as to identify an extent of the illuminated card in the first image file and thereby generate a contour data set; and applying the contour data set to the first image file so as to exclude a third group of pixels from analysis, the third group of pixels comprising pixels located outside the extent of the illuminated card depicted in the first image file.

26. The method of claim 25, wherein the step of applying contour detection includes applying canny edge detection to the first image file.

27. The method of claim 25, wherein the method further comprises the step of correcting a spherical distortion of the first image file.

28. The method of claim 25, further comprising the steps of:
applying the contour data set to the first image file so as to identify an orientation of the illuminated card depicted in the first image file; and correcting the orientation of the illuminated card to a selected orientation by rotating the first image file so as to re-orient the card in the selected orientation.

Date Recue/Date Received 2020-05-29

29. The method of claim 24, wherein the method further comprises the step of applying a light mask to the image file so as to exclude a third group of pixels, wherein each pixel of the third group of pixels has an integer exceeding a predetermined light threshold, said light threshold selected to identify each pixel of the third group of pixels that forms a reflection of the point light source.

30. The method of claim 23, wherein the step of applying a value mask to the first group of pixels further includes applying at least a second mask, the at least a second mask selected from a group comprising: a hue mask; a saturation mask; and wherein a predetermined threshold value of any one of the hue mask and the saturation mask is selected to identify a pixel does not form a portion of the principal maxima.

31. An apparatus for performing the method of claim 24, the apparatus comprising:
an imaging chamber, the imaging chamber adapted to substantially exclude any light from an external light source from entering the imaging chamber;
a platform positioned within the imaging chamber and adapted to support the illuminated card;
a point light source, the point light source positioned within the imaging chamber such that the platform is positioned outside the field of view of the point light source;
a diffuse light source, the diffuse light source positioned within the imaging chamber to illuminate the illuminated card;
an image capture device for capturing an image of the illuminated card so as to generate the image file.

32. The apparatus of claim 31 wherein the platform comprises a transparent material, and wherein the image capture device includes a first camera positioned above the platform and a second camera positioned below the platform, the first camera arranged to take a first image of a first Date Recue/Date Received 2020-05-29 side of the card and the second camera arranged to take a second image of a second side of the card.

33. The method of claim 23, wherein the method further comprises the step of applying contour detection to the image file to identify said at least a portion of the extent of the illuminated card in the image file and thereby generate a contour data set delineating said extent; and applying the contour data set to the image file so as to reduce the image file to a border group of pixels, said border group of pixels located proximate the extent of the card.

34. The method of claim 33, wherein the step of applying contour detection includes applying canny edge detection to the image file.

35. The method of claim 34, wherein the border group of pixels is defined as an area of the card consisting of pixels having substantially uniform HSV characteristics as compared to adjacent pixels when the card is a mint condition specimen.

36. The method of claim 23, wherein the first image file consists of an image of a rear face of the card, wherein the rear face of each card in a set of cards comprises a substantially identical image.

37. The method of claim 23, wherein the plurality of grading thresholds includes at least a mint threshold, a slightly played threshold and a heavily played threshold; and wherein when the number of remaining pixels is less than or equal to the mint threshold, the card is assigned a mint condition grading; and wherein when the number of remaining pixels is greater than the mint threshold and less than or equal to the slightly played threshold, the card is assigned a slightly played condition grading;
and Date Recue/Date Received 2020-05-29 wherein when the number of remaining pixels is greater than the heavily played threshold, the card is assigned a heavily played condition grading.

Date Recue/Date Received 2020-05-29