JP2017019108A - Image quality change detection apparatus, image quality change detection method, and image quality change detection program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To appropriately detect an image portion where image quality change in a specific direction has occurred even if the image portion is short in directions other than the specific direction.SOLUTION: An image quality change detection device comprises image quality change detection means for detecting an image change in a specific direction in an image created by an image forming device on the basis of a distribution information in the specific direction indicating a distribution of image data of the image created by the image forming device in the specific direction. The image quality change detection means detects the image quality change in the specified direction on the basis of the distribution information in the specific direction for every more than two image areas that can be obtained by dividing the image in a direction crossing or orthogonal to the specific direction.SELECTED DRAWING: Figure 3

Description

  The present invention relates to an image quality change detection device, an image quality change detection method, and an image quality change detection program.

  Conventionally, optical data such as RGB data of an image formed by an image forming apparatus is read by an image sensor, and image quality changes such as image density unevenness or streaky abnormal images in a specific direction are obtained from the obtained optical data. An image quality change detection device for detecting is known.

  In Patent Document 1, banding, which is a streaky abnormal image elongated in the main scanning direction (direction perpendicular to the recording material conveyance direction) of the image forming apparatus, is detected, and the image quality is evaluated based on the detection result. An image quality evaluation apparatus (image quality change detection apparatus) that performs the above is disclosed. In this image quality evaluation apparatus, an image recorded on a recording material such as paper is read, and one-dimensional distribution information (specific direction distribution information) of luminance (optical data) in the sub-scanning direction (recording material conveyance direction) is read. Luminance distribution information is calculated. Thereafter, a difference value between the luminance distribution information obtained by smoothing the one-dimensional luminance distribution information with a smoothing filter and the original one-dimensional luminance distribution information is calculated, and only a portion exceeding a predetermined threshold is calculated by a human. This is extracted as a perceived banding component and integrated to extract an aperiodic banding amount. Then, a final banding evaluation value (image quality evaluation value) is calculated from the aperiodic banding amount extracted in this way.

However, the image quality evaluation apparatus disclosed in Patent Document 1 may not be able to properly detect banding with a short length in the main scanning direction (short banding).
Not only banding that occurs in the sub-scanning direction, but also banding that occurs in any direction (specific direction) that has a short length in a direction that intersects or is orthogonal to that direction (non-specific direction) is also appropriate. May not be detected.
Also, regarding image quality changes such as density unevenness or color changes that occur in a specific direction, if the length in the non-specific direction is short, there is a possibility that appropriate detection cannot be performed, as with banding.

  In order to solve the above-described problem, the present invention is configured to detect a change in image quality in a specific direction on an image based on specific direction distribution information indicating a distribution in a specific direction of optical data of the image formed by the image forming apparatus. In the image quality change detecting device including the image quality change detecting means for detecting, the image quality change detecting means specifies each of two or more image regions obtained by dividing the image in a direction intersecting or orthogonal to the specific direction. A change in image quality in the specific direction is detected based on the direction distribution information.

  According to the present invention, even if an image portion in which a change in image quality in a specific direction occurs is short in a non-specific direction, an excellent effect is achieved that it can be appropriately detected.

1 is an external view schematically showing an image quality evaluation apparatus in Embodiment 1. FIG. It is a block diagram which shows the structure of the image quality evaluation apparatus. It is a flowchart which shows the flow of the image quality evaluation method performed by the image quality evaluation apparatus. It is explanatory drawing which shows the setting method of the image area | region obtained by dividing | segmenting an evaluation object image in the main scanning direction. It is explanatory drawing which shows an example of the division which divides each image area | region into a subscanning direction. It is explanatory drawing which shows the other example of the division which divides each image area | region in a subscanning direction. It is a graph which shows the color difference distribution in the subscanning direction of each image area | region. It is explanatory drawing which shows the example of the density nonuniformity of the evaluation object image from which the color difference distribution of FIG. 7 was obtained. It is a graph which shows the maximum color difference distribution obtained from the color difference distribution of FIG. It is explanatory drawing which shows the example of a display of the evaluation result of "no abnormality" displayed on a monitor. It is explanatory drawing which shows the example of a display of the evaluation result of "abnormality" displayed on a monitor. FIG. 10 is an explanatory diagram illustrating an example of an image forming apparatus equipped with an image quality evaluation apparatus according to a second embodiment. 3 is a flowchart illustrating a flow of an image quality evaluation method performed in the image forming apparatus. It is explanatory drawing which shows the other example of the image forming apparatus carrying an image quality evaluation apparatus. It is a flowchart which shows the flow of the image quality evaluation method in a modification. It is explanatory drawing which shows an example of the table data which shows the correspondence of a known density nonuniformity generation cycle and the density nonuniformity generation | occurrence | production member corresponding to this. It is a graph which shows an example of the sub-scanning direction distribution of L * value. It is a graph which shows the generation | occurrence | production period distribution calculated | required from the frequency distribution obtained by frequency-analyzing the subscanning direction distribution of L * value shown in FIG. In a modification, it is explanatory drawing which shows the example of a display of the evaluation result of "no abnormality" displayed on a monitor, and a density nonuniformity generation | occurrence | production member.

Embodiment 1
Hereinafter, an image quality change detection apparatus according to the present invention is applied to an image quality evaluation apparatus for an image formed by an image forming apparatus such as a copying machine or a printer (hereinafter, this embodiment is referred to as “embodiment 1”). ).
First, an image quality evaluation method performed by the image quality evaluation apparatus according to the first embodiment will be described. This image quality evaluation method detects local density unevenness (including a streaky abnormal image extending in the main scanning direction) in the sub-scanning direction as a change in image quality in a specific direction on the image, and according to the detection result. The image is evaluated.

FIG. 1 is an external view schematically showing an image quality evaluation apparatus according to the first embodiment.
FIG. 2 is a block diagram illustrating a configuration of the image quality evaluation apparatus according to the first embodiment.
An image quality evaluation apparatus 100 according to the first embodiment includes a main body 101 of a general-purpose personal computer (hereinafter referred to as “personal computer”), an image scanner 102 as an image reading apparatus connected thereto, and a monitor 103 as a display unit. Consists of The personal computer main body 101 mainly includes a calculation unit 101a including a CPU (Central Processing Unit) and a storage unit including a storage device such as a ROM (Read Only Memory), a RAM (Random Access Memory), and an HDD (Hard Disk Drive). In addition, it also has general functions provided in a general-purpose personal computer, such as a communication unit including a communication interface.

  The storage unit 101b of the personal computer main body 101 stores various computer programs including an image quality change detection program for performing the image quality evaluation method of the first embodiment. The storage unit 101b also stores various data such as image data read by the scanner 102. The calculation unit 101a of the personal computer main body 101 implements various functions necessary for the operation as the image quality evaluation apparatus of the first embodiment by executing various computer programs stored in the storage unit 101b by the CPU. In particular, in the first embodiment, by executing the image quality change detection program by the CPU, density unevenness detection processing for detecting local density unevenness in the sub-scanning direction of the image read by the scanner 102 is executed. An evaluation result display process for displaying the image evaluation result on the monitor 103 according to the processing result is also executed.

FIG. 3 is a flowchart showing the flow of the image quality evaluation method performed by the image quality evaluation apparatus according to the first embodiment.
In the first embodiment, first, a sheet as a recording material on which an image to be evaluated is formed is read by the scanner 102 to obtain image data as optical data of the image (S1). This image data is general RGB data, but if the image data read here is optical data that can be used in the image quality evaluation method of the first embodiment, luminance data, brightness data, hue data, color Other physical characteristic quantities such as degree data and data obtained by arbitrarily combining them may be used. In the first embodiment, since it is necessary to obtain color difference data as described later, it is necessary that the physical characteristic amount is necessary to obtain the color difference data.

  Thus, the image data read by the scanner 102 is stored in the storage unit 101b of the personal computer main body 101, and then converted into physical characteristic quantities for calculating color difference data by the arithmetic unit 101a of the personal computer main body 101 (S2). . Specifically, RGB data read by the scanner 102 is converted into color space data such as an L * a * b * color space.

  Next, as shown in FIG. 4, the calculation unit 101 a has about 3 to 7 (here, 5) image regions 300-1 and 300-2 obtained by dividing the evaluation target image 300 in the main scanning direction. , 300-3, 300-4, 300-5 are set (S3). The number, shape, size, etc. of the image regions set here are arbitrary as long as they are two or more image regions divided in a direction intersecting or orthogonal to the sub-scanning direction in which density unevenness to be detected occurs. . Also, the number, shape, dimensions, etc. of the image area to be set may be changed according to the size of the evaluation target image (paper size), or the image area may be changed regardless of the size of the evaluation target image (paper size). The number, shape, dimensions, etc. may be constant.

  Next, the calculation unit 101a divides the color space data generated in the processing step S2 into the set five image areas 300-1 to 300-5 (S4). The divided color space data (divided color space data) is further divided into a plurality of sections divided in the sub-scanning direction (S5). There is a merit that more detailed density unevenness can be detected as the number of data divisions increases, but there is a demerit that calculation load increases, so it is set appropriately considering the balance between the two. The

FIG. 5 is an explanatory diagram showing an example of the division in the first embodiment.
In the graph shown in FIG. 5, the vertical axis represents the color space data value (here, L * value which is the brightness of the L * a * b * color space), and the horizontal axis represents the position in the sub-scanning direction. 4 shows an example of a sub-scanning direction distribution of color space data (L * value). In the first embodiment, as shown in FIG. 5, the set sections are set to be adjacent to each other without overlapping each other, and the width (length in the sub-scanning direction) of the sections is arbitrarily set. The However, the setting method of the division is not limited to this, and for example, as shown in FIG. 6, it may be set so as to partially overlap the adjacent divisions.

  Next, the calculation unit 101a calculates the color difference between the sections, that is, the distance in the color space (S6). Here, the color difference to be calculated is a color difference between two adjacent pixel rows (pixel rows extending in the main scanning direction) across the sections, but is not limited to this. For example, the sum of the color space data in each section Or the average value may be calculated, and the color difference between the sections may be calculated using the calculation result. In addition, when using the color difference between two adjacent pixel columns across the segments, for example, the sum and average value of the color space data of both pixel columns are calculated, and the color difference between the segments is calculated using the calculation result. May be. Alternatively, the color difference between the color space data adjacent to each other in the sub-scanning direction between the two pixel rows may be calculated, and the sum or average value of these color differences may be calculated and used as the color difference between the sections.

FIG. 7 is a graph showing the color difference distribution in the sub-scanning direction for the five image regions 300-1 to 300-5.
FIG. 8 is an explanatory diagram illustrating an example of density unevenness of the evaluation target image from which the color difference distribution of FIG. 7 is obtained.
By calculating the color difference between the sections as described above, as shown in FIG. 7, for each of the five image areas 300-1 to 300-5, distribution information of the color difference in the sub-scanning direction, that is, the sub-scanning direction. A data group (one-dimensional data group corresponding to the sub-scanning direction) of color differences (image quality change index value) arranged in the sub-scanning direction is obtained. According to the first embodiment, when the density unevenness in the sub-scanning direction is generated in a part of the main scanning direction (for example, the hook-shaped density unevenness in FIG. 8), the evaluation target image is divided in the main scanning direction. The accuracy of detecting such density unevenness is higher than the obtained color difference distribution in the sub-scanning direction.

  More specifically, when the density unevenness in the sub-scanning direction occurs in a part of the main scanning direction (for example, the ridge-shaped density unevenness in FIG. 8), the evaluation target image was obtained without being divided in the main scanning direction. In the color difference distribution in the sub-scanning direction, the portion in the main scanning direction in which the density unevenness occurs due to the influence of the color difference data (data having a small color difference) based on the color space data in other parts in the main scanning direction in which the density unevenness does not occur. The color difference data is diluted. As a result, the color difference data in the sub-scanning direction position where the density unevenness occurs is smaller than the color difference data in the main scanning direction portion where the density unevenness occurs, and the color difference data becomes a detection reference for the density unevenness. The predetermined threshold value is not exceeded, and detection of density unevenness is likely to occur.

  At this time, if a predetermined threshold value that is a detection criterion for density unevenness is set small, even in the sub-scanning direction color difference distribution obtained without dividing the evaluation target image in the main scanning direction, a part of the main scanning direction is obtained. Thus, it is possible to reduce the detection omission of density unevenness occurring in FIG. However, in this case, there is an increased number of false detections that detect noise that is not density unevenness that can be perceived by humans without being able to distinguish it from density unevenness, resulting in a decrease in density unevenness detection accuracy. obtain. Therefore, it is possible to reduce the omission of detection of density unevenness occurring in a part of the main scanning direction while setting the predetermined threshold value serving as a reference for detecting density unevenness to an appropriate value that can detect density unevenness in distinction from noise. is necessary.

  In the first embodiment, a color difference distribution in the sub-scanning direction is obtained for each of five image regions 300-1 to 300-5 obtained by dividing the evaluation target image in the main scanning direction. In this case, the color difference values of the image areas 300-1 to 300-5 are calculated from the color space data only in the image area, and are not affected by the color space data of other image areas. . Therefore, when density unevenness in the sub-scanning direction occurs in a part of the main scanning direction (for example, a bowl-shaped density unevenness in FIG. 8), an image area corresponding to the position in the main scanning direction where the density unevenness occurs. The color difference value is not affected by the color difference of the image area corresponding to the other position in the main scanning direction where the density unevenness does not occur. As a result, the color difference value of the image area where the density unevenness has occurred is not diluted by the color difference of another image area where the density unevenness does not occur. Therefore, since the density unevenness in the sub-scanning direction generated at the corresponding main scanning direction position can be appropriately detected from the color difference distribution of each image area, the density unevenness in the sub-scanning direction is a part of the main scanning direction. Even in such a case (for example, a bowl-shaped density unevenness in FIG. 8), the density unevenness is appropriately detected.

  Further, in the sub-scan direction color difference distribution obtained without dividing the evaluation target image in the main scanning direction, density unevenness over the image length in the main scanning direction (for example, stripe-like density unevenness extending in the vertical direction in FIG. 8). Even so, there was a case where detection omission occurred. Specifically, for example, when a white vertical line (the rightmost white vertical line in FIG. 8) is generated when the evaluation target image originally has a density deviation in the main scanning direction, the white vertical line Depending on the position of the streak in the main scanning direction, the color difference between adjacent image portions in the sub-scanning direction is greatly different. For example, at a position in the main scanning direction where an image portion adjacent in the sub-scanning direction is close to white, the color difference from the white vertical stripe is small. In such a case, in the color difference distribution in the sub-scanning direction obtained without dividing the evaluation target image in the main scanning direction, the white vertical streak is affected by the color difference data at the main scanning direction position where the color difference from the white vertical streak is small. The color difference data at the position in the main scanning direction where the color difference is large is diluted. As a result, the color difference data at the position in the sub-scanning direction where white vertical stripes are generated is smaller than the color difference data at the position in the main scanning direction where the color difference is large, and the color difference data does not exceed a predetermined threshold value as a detection reference. White vertical stripes are likely to be missed.

  Even in such a case, according to the first embodiment, the color difference values of the image areas 300-1 to 300-5 divided in the main scanning direction are obtained from the color space data only in the image area. It is calculated and is not affected by the color space data of other image areas. Therefore, as described above, even when a white vertical stripe (the rightmost white vertical stripe in FIG. 8) is generated when the evaluation target image originally has a density deviation in the main scanning direction, The color difference value of the image area corresponding to the large main scanning direction position is not diluted by the color difference value of the other image area corresponding to the main scanning direction position having a small color difference. Accordingly, even density unevenness (white vertical stripes or the like) in the sub-scanning direction in which the color difference varies depending on the position in the main scanning direction can be appropriately detected from the color difference distribution of each image region.

  The color difference distribution information for the five image regions 300-1 to 300-5 obtained as described above may be displayed on the monitor 103 or the like as it is to notify the operator. In this case, an operator who looks at the waveform of each color difference distribution information can determine whether density unevenness in the sub-scanning direction has occurred based on his / her experience and knowledge.

  However, in the first embodiment, in order to realize density objection detection with higher objectivity, the calculation unit 101a subsequently performs color difference distribution for each of the five image regions obtained as described above. For the sections corresponding to the same position in the sub-scanning direction, color difference data having the maximum color difference between these image regions 300-1 to 300-5 is extracted (S7). When this is expressed in a graph, it becomes a graph indicated by "x" in the graph of FIG.

  In this way, by extracting the maximum color difference data having the maximum color difference between the image areas, the maximum color difference distribution information in the sub-scanning direction for the evaluation target image, that is, the data of the maximum color difference arranged in the sub-scanning direction. A group (one-dimensional data group corresponding to the sub-scanning direction) is obtained. In the first embodiment, a predetermined threshold value serving as an evaluation criterion is set for the maximum color difference distribution information obtained in this way, and a human is perceived at a position in the sub-scanning direction having the maximum color difference data exceeding the threshold value. It is determined that density unevenness has occurred, and this is extracted (S8). The threshold value at this time is preferably set as appropriate from the viewpoint of detecting density unevenness perceived by humans.

  As described above, since it is possible to grasp at which position in the sub-scanning direction the density unevenness perceived by humans is generated, if the result is displayed on the monitor 103 or the like to notify the worker, the worker The occurrence of density unevenness can be easily determined. However, when performing image quality evaluation such as how much density unevenness occurs, it is necessary to take measures such as image quality improvement, the experience and knowledge of the operator is required.

  Therefore, in order to realize more objective image quality evaluation, in the first embodiment, the arithmetic unit 101a calculates the sum of the maximum color difference data exceeding the threshold extracted in the processing step S8 (S9), and quantitative image quality. Evaluate. This sum may be simply the sum of the maximum color difference data exceeding the threshold extracted in step S8, or may be the sum of the difference between the extracted maximum color difference data and the threshold. The total sum in this case corresponds to, for example, the area of the shaded portion shown in FIG.

  Next, the calculation unit 101a compares a predetermined evaluation threshold for determining whether or not the image quality is acceptable as the product quality of the image forming apparatus with the sum of the maximum color difference data calculated in the processing step S9 ( S10). If the sum of the maximum color difference data does not exceed the evaluation threshold (No in S10), the arithmetic unit 101a assumes that the image quality of the image formed by the image forming apparatus is within the allowable range of product quality. An evaluation result of “no abnormality” as shown in FIG. 10 is displayed on the monitor 103 (S11). On the other hand, when the sum of the maximum color difference data exceeds the evaluation threshold (Yes in S10), the calculation unit 101a determines that the image quality of the image formed by the image forming apparatus exceeds the allowable range of product quality. Then, the evaluation result “abnormal” as shown in FIG. 11 is displayed on the monitor 103 (S12).

  According to the first embodiment, the operator can objectively determine whether or not density unevenness exceeding the allowable range has occurred in the evaluation target image by looking at the evaluation result displayed on the monitor 103. it can. In the first embodiment, the method of notifying the evaluation result to the worker is a method of visually informing by displaying on the monitor 103. However, an auditory sound such as a beep sound is generated when the abnormality is abnormal. An informing method may be used.

[Embodiment 2]
Next, an embodiment in which the image quality change detection apparatus according to the present invention is applied to an image quality evaluation apparatus incorporated in an image forming apparatus (hereinafter, this embodiment is referred to as “embodiment 2”) will be described.
In the first embodiment described above, the personal computer main body 101 performs the image quality evaluation according to the density unevenness detection result based on the image data obtained by reading the paper on which the image is formed by the image forming apparatus with the scanner 102. In the first embodiment described above, the image quality evaluation method can be performed regardless of the location of the image forming apparatus. For example, image quality evaluation can be performed on the image forming apparatus before shipment from the factory, or a maintenance worker can perform image evaluation. It is possible to visit the place where the forming apparatus is installed and evaluate the image quality of the image forming apparatus using a personal computer and a scanner. On the other hand, in the second embodiment, the function of the image quality evaluation apparatus 100 is mounted on the image forming apparatus to perform image quality evaluation. In the second embodiment, the user of the image forming apparatus performs the image quality evaluation method himself or the maintenance worker visits the installation place of the image forming apparatus and performs the image quality evaluation using the functions of the image forming apparatus. Can be.

FIG. 12 is an explanatory diagram illustrating an example of the image forming apparatus 200 according to the second embodiment.
The image forming apparatus 200 according to the second embodiment includes an image reading unit 2 as an image reading unit that reads an image of a document, and an image forming unit 3 that forms an image on a sheet P as a recording material. The image forming apparatus 200 includes a paper supply unit 4 that supplies the paper P to the image forming unit 3 and a paper discharge unit 5 that discharges the paper P after image formation.

  The image reading unit 2 is a unit that reads an image of a document set on a transparent document table. For example, the image reading unit 2 combines an optical scanning system including a lamp, a mirror, a carriage, and the like with an optical image scanned by the optical scanning system. And a lens system for imaging. The image reading unit 2 includes an image reading sensor such as a CCD that receives an optical image formed by the lens system and converts it into an electrical signal.

  The image forming unit 3 uses, as an electrophotographic method, a plurality of toner images of color components of yellow (Y), magenta (M), cyan (C), and black (K), which are different colors, as a plurality of image carriers. A plurality of image forming units 10Y, 10M, 10C, and 10K are formed on the body drums 11Y, 11M, 11C, and 11K, respectively. Hereinafter, in this embodiment, when distinguishing between members and devices used for each color component of yellow (Y), magenta (M), cyan (C), and black (K), each member and device Y, M, C, and K are added to the end of the symbol. In addition, when explaining the common configuration and operation of members and apparatuses used for each color component, Y, M, C, and K at the end of the reference numerals are omitted as appropriate.

  The image forming unit 3 is an intermediate transfer member that is an intermediate transfer member serving as an image carrier that sequentially transfers (primary transfer) and holds the toner images of the respective color components formed on the photosensitive drum 11 in each image forming unit 10. A belt 15 is provided. Further, the image forming unit 3 is secondary-transferred with a secondary transfer unit 20 as a secondary transfer unit that collectively transfers (secondary transfer) the superimposed toner image transferred onto the intermediate transfer belt 15 onto the paper P. And a fixing unit 46 as fixing means for fixing the toner image on the paper P. The image forming unit 3 also performs image processing based on a control unit 40 serving as a control unit that controls the operation of each device (each unit) and input image data output from an external device such as the image reading unit 2 or a personal computer. And an image processing unit 44 for creating data for formation. In the present embodiment, each image forming unit 10, the intermediate transfer belt 15, the secondary transfer unit 20, and the like constitute an image forming unit that forms an image on the paper P.

  Each of the control unit 40 and the image processing unit 44 can be configured by a memory such as a CPU, a ROM, or a RAM, for example. For example, the CPU expands a computer program stored in the ROM to a RAM, executes the computer program while using the RAM as a work area and a data buffer, and executes various controls and various processes. The control unit 40 can communicate with an external device via a communication interface such as a wired or wireless LAN (Local Area Network) or USB (Universal Serial Bus).

  The image processing unit 44 performs image data processing such as conversion processing for converting the image data read by the image reading unit 2 into predetermined image data that can be used for image forming processing. The image processing unit 44 also functions as an image quality change detection unit that performs various processes performed by the calculation unit 101a of the personal computer main body 101 described in the first embodiment. That is, in the second embodiment, the image processing unit 44 and, if necessary, the control unit 40 function as the image quality evaluation apparatus 100, and execute the image quality evaluation method described in the first embodiment.

  As shown in FIG. 12, each of the four image forming units 10Y, 10M, 10C, and 10K has a similar configuration and includes a photosensitive drum 11 that rotates in a predetermined direction. Further, around the photosensitive drum 11 of each image forming unit 10, a charger as a charging unit that charges the photosensitive drum 11 to a predetermined potential, and an exposure laser beam is scanned and irradiated onto the photosensitive drum 11. And a laser exposure device 13 as an exposure means for writing an electrostatic latent image. Further, around the photosensitive drum 11, a developing device is provided as a developing unit that stores each color component toner and visualizes the electrostatic latent image on the photosensitive drum 11 with the toner. Further, around the photosensitive drum 11, a primary transfer roller 16 as primary transfer means for transferring each color component toner image formed on the photosensitive drum 11 to the intermediate transfer belt 15, residual toner on the photosensitive drum 11. A drum cleaner or the like is also provided.

  The intermediate transfer belt 15 is circulated and driven at a predetermined speed in a direction in which the intermediate transfer belt 15 is rotated around each photosensitive drum 11 by various rollers. As these various rollers, a drive roller that is driven by a constant speed drive motor to drive the intermediate transfer belt 15 in a circulating manner, and the intermediate transfer belt 15 is supported so as to extend linearly along the arrangement direction of the photosensitive drums 11. And a supporting roller. Further, as various rollers, a tension roller that applies a constant tension to the intermediate transfer belt 15 and prevents the intermediate transfer belt 15 from meandering, a backup roller provided in the secondary transfer unit 20, and a secondary transfer unit 20. An idle roller provided on the downstream side of the intermediate transfer belt in the conveying direction is also included.

  Each primary transfer roller 16 is provided inside a stretched portion of the intermediate transfer belt 15 that is stretched so as to extend linearly facing the respective photosensitive drums 11, and has a voltage having a polarity opposite to the charging polarity of the toner. Is applied. As a result, the toner images on the respective photosensitive drums 11 are sequentially electrostatically attracted to the intermediate transfer belt 15 to form a toner image superimposed on the intermediate transfer belt 15.

  The secondary transfer unit 20 includes a secondary transfer roller disposed on the toner image carrying surface side of the intermediate transfer belt 15 and a backup roller. The backup roller is disposed inside the intermediate transfer belt 15 to form a counter electrode of the secondary transfer roller, and a metal power supply roller as a bias application member to which the secondary transfer bias is stably applied is disposed in contact with the backup roller. Has been.

  In addition, a belt cleaner as a cleaning unit for cleaning the surface of the intermediate transfer belt 15 is movable toward and away from the intermediate transfer belt 15 on the downstream side of the secondary transfer portion 20 of the intermediate transfer belt 15 in the belt movement direction. Is provided. The belt cleaner is disposed to face the driving roller with the intermediate transfer belt 15 interposed therebetween, and removes residual toner and paper dust on the intermediate transfer belt 15 after the secondary transfer.

  The fixing unit 46 fixes the toner image on the paper P by heating and pressing. In the second exemplary embodiment, the fixing unit 46 includes a heating roller 46a disposed to face the image forming surface of the paper P, a pressure belt 46b that is disposed in pressure contact with the heating roller 46a to form a fixing nip, and a heating roller 46a. And a halogen lamp 46c serving as a heating source.

  The paper supply unit 4 conveys each paper P stored in the first tray 50, the second tray 51, and the third tray 52 through a predetermined path. In the vicinity of each of the trays 50 to 52, corresponding delivery rollers 53, 54, and 55 are disposed. Each of the feed rollers 53 to 55 nips the paper P separated and taken out one by one from the corresponding trays 50 to 52 and temporarily stops the paper P on the paper transport path, and at the timing based on a predetermined start signal. The sheet P is sent out to the downstream side.

  Above the paper supply unit 4, a display monitor 56 and an input keyboard 56 a that is operated by the user are disposed adjacent to the display monitor 56 in the vicinity of the image reading unit 2. In the second embodiment, the display monitor 56 performs the same function as the display monitor 103 that displays the image quality evaluation result in the above-described embodiment. A power supply 43 that supplies power used in the image forming apparatus 200 is disposed below the third tray 52.

  A series of paper conveyance paths R1 to R5 from the delivery position of the paper P by the delivery rollers 53 to 55 to the discharge tray 57 via the image formation processing position of the image forming unit 3 are respectively for paper conveyance. Conveyance rollers as in-apparatus conveying means are provided as appropriate. The paper P accommodated in the first tray 50 is sent out by the feed roller 53 and then sent to the merging / conveying section 58 via the first paper transport path R1. The paper P stored in the second tray 51 is sent out by the feed roller 54 and then sent to the merging / conveying section 58 via the first paper transport path R1. On the other hand, the paper P stored in the third tray 52 is directly sent to the merging and conveying unit 58 by the delivery roller 55.

  The sheet P sent to the merging / conveying section 58 is sent to the secondary transfer section 20 of the image forming section 3 via the second sheet conveying path R2. Further, the sheet P that has passed through the secondary transfer unit 20 is sent to the fixing unit 46 by the belt conveyance unit 45 and then discharged to the discharge tray 57 via the third sheet conveyance path R3. On the other hand, after the paper P on which images are formed on both sides passes through the fixing unit 46, it is sent to the double-sided reversing unit 59 via the fourth paper transport path R4, where it is turned upside down. Then, it is sent again to the merging / conveying section 58 via the fifth sheet conveying path R5.

  In such paper transport paths R1 to R5, an attitude correction unit 60 and a registration roller 61 are disposed in the second paper transport path R2. The attitude correction unit 60 corrects the attitude of the paper P conveyed on the second paper conveyance path R2. The registration roller 61 is composed of a pair of rollers that are held in pressure contact with each other, and rotates the roller pair at a timing based on a predetermined start signal while nipping the paper P between the pair of rollers. The paper P is fed into the transfer unit 20.

FIG. 13 is a flowchart illustrating the flow of an image quality evaluation method performed by the image forming apparatus according to the second embodiment.
In the image quality evaluation method of the second embodiment, first, a test image is printed under the control of the control unit 40 (S21). This test image is stored in advance in the memory of the control unit 40 or the image processing unit 44, for example. The image forming unit 3 forms a test toner image based on the test image data read from the memory under the control of the control unit 40. In the image forming unit 3, four photosensitive drums 11 are driven to rotate, and the surface of each photosensitive drum 11 is tested with yellow, magenta, cyan, and black by the corresponding charger, laser exposure unit 13, and developing device. A toner image is formed. The test toner images of the respective colors formed in this way are sequentially transferred onto the intermediate transfer belt 15 by the primary transfer roller 16. As a result, a multicolor (full color) test toner image is formed on the intermediate transfer belt 15 by superimposing four color toner images. The test toner image formed on the intermediate transfer belt 15 is sent to the secondary transfer unit 20 while being carried on the intermediate transfer belt 15.

  On the other hand, the tray paper P selected by the user using the keyboard 56a or the tray paper P selected by the automatic selection function is the timing at which the test toner image on the intermediate transfer belt 15 reaches the secondary transfer unit 20. At the same time, it is fed by the registration roller 61. For example, when the selected tray is the first tray 50, the paper P sent out by the feed roller 53 is sent to the merging and transporting unit 58 via the first paper transport path R <b> 1. Further, the posture is corrected by the posture correction unit 60 via the second paper conveyance path R2, and then sent to the secondary transfer unit 20 by the registration roller 61.

  In the secondary transfer unit 20 of the image forming unit 3, the test toner image (full color image) carried on the intermediate transfer belt 15 is collectively transferred (secondary transfer) onto the paper P by the secondary transfer roller. Thereafter, the sheet P on which the test toner image has been transferred is sent to the fixing unit 46 by the belt conveyance unit 45, and after being heated and pressurized, the sheet P is discharged to the discharge tray 57 via the third sheet conveyance path R3. Is done. In this way, the test image is printed on the paper P.

  The paper P on which the test image is printed in this way is set as a document in the image reading unit 2 by a user or the like, and is read by the image reading unit 2. As a result, the image processing unit 44 acquires the image data of the test image, similar to the calculation unit 101a of the personal computer main body 101 of the first embodiment described above (S1). The subsequent processing steps (S2 to S11) are the same as those in the first embodiment. However, the display monitor 56 displays the evaluation result “no abnormality” or the evaluation result “abnormal”.

  In the present embodiment, the user P or the like sets the paper P discharged to the discharge tray 57 in the image reading unit 2 and reads the image data of the test image by the image reading unit 2. Alternatively, the image data of the test image may be read using an image reading unit provided in the image forming apparatus. For example, as shown in FIG. 12, the paper discharge unit 5 may be provided with an image reading means 70 for reading image data of an image on the paper P conveyed on the third paper conveyance path R3. In this case, the image data of the test image on the sheet after fixing can be read without the user's work. Further, as shown in FIG. 14, an image reading means 71 for reading a test toner image transferred onto the intermediate transfer belt 15 may be provided. Alternatively, an image reading unit may be arranged at a position for reading the image data of the unfixed test toner image transferred to the paper P, or an image at a position for reading the image data of the test toner image on each photosensitive drum 11. Reading means may be arranged. The image reading unit may be a scanner similar to the scanner 102 or the image reading unit 2, but is not particularly limited as long as necessary optical data such as a micro densitometer and a CCD camera can be acquired. Never happen.

[Modification]
Next, a modification of the image quality evaluation method in the first and second embodiments will be described.
In this modification, when the evaluation result is determined as “abnormal” in the first and second embodiments, the cause of the abnormality is further specified and notified to the operator. In the following description, an example using the image quality evaluation method of the first embodiment described above will be described, but the same applies to the image quality evaluation method of the second embodiment described above.

FIG. 15 is a flowchart showing the flow of the image quality evaluation method in this modification.
When it is determined by the image quality evaluation method of the first embodiment described above that the sum of the maximum color difference data exceeds the evaluation threshold (Yes in S10), in this modification, first, frequency analysis of the maximum color difference data is performed ( S31). Specifically, for example, frequency analysis is performed on the distribution in the sub-scanning direction of the color space data (for example, L * value) obtained in the processing step S2, the frequency distribution of the color space data is obtained, and a peak is found in the frequency distribution. The peak frequency shown is extracted. The peak frequency extracted in this way corresponds to the generation period of density unevenness in the sub-scanning direction. Since the density unevenness generation period corresponds to the rotation period of the member related to the cause of the density unevenness, the member related to the cause of the density unevenness can be estimated from the extracted peak frequency.

  In the present embodiment, as shown in FIG. 16, table data indicating the correspondence between the density unevenness occurrence period and the density unevenness generation cause member corresponding thereto is stored in the storage unit 101b in advance. After extracting the peak frequency by the frequency analysis, the calculation unit 101a checks whether the density unevenness generation period obtained from the peak frequency exists in the table data in the storage unit 101b. And if this is confirmed, the member corresponding to the generation cycle of the density unevenness is specified as a member causing the density unevenness (S32).

  More specifically, the generation period distribution as shown in FIG. 18 is obtained from the frequency distribution obtained by frequency analysis of the L * value sub-scan direction distribution as shown in FIG. 17, and the peak corresponding to the peak frequency is obtained. Generation periods P1, P2, P3, and P4 are extracted. If any of the peak generation periods P1, P2, P3, and P4 coincides with the generation period in the table data of the storage unit 101b, the member corresponding to the generation period is specified as a member that causes density unevenness. To do. Of the peak generation periods P1, P2, P3, and P4 obtained from FIG. 18, the three peak generation periods P1, P2, and P3 are present in the table data shown in FIG.

  Therefore, in this case, the calculation unit 101a, with respect to the monitor 103, as shown in FIG. 19, together with the evaluation result “abnormal”, the three members identified as the cause of density unevenness (photosensitive member, developing roller, gear) ) Is displayed (S33). As a result, the operator can not only objectively determine whether or not density unevenness exceeding the allowable range has occurred in the evaluation target image by looking at the display content of the monitor 103, but also the cause of the occurrence of density unevenness. It is possible to objectively determine which member is. Therefore, the maintenance work for removing the cause of density unevenness can be performed quickly and appropriately.

What was demonstrated above is an example, and there exists an effect peculiar for every following aspect.
(Aspect A)
Based on specific direction distribution information indicating the distribution in a specific direction such as the sub-scanning direction of optical data such as RGB data and color space data of the image formed by the image forming apparatus 200, the sub-scanning direction and the like on the image are determined. In an image quality change detection apparatus such as an image quality evaluation apparatus 100 provided with an image quality change detection means such as a computing unit 101a or an image processing unit 44 that detects image quality changes such as density unevenness in a specific direction, the image quality change detection means Specific direction distribution information (color space data in the sub-scanning direction) for each of two or more image regions 300-1 to 300-5 obtained by dividing the image in a direction intersecting or orthogonal to the direction (main scanning direction, etc.) The image quality change in the specific direction is detected based on the distribution information of the image data.
Usually, it is possible to detect a change in image quality in a specific direction on the image by detecting a portion showing a change in image quality in a specific direction from the specific direction distribution information of the optical data of the image formed by the image forming apparatus. It is. However, in the conventional image quality change detection device including the image quality evaluation device disclosed in Patent Document 1, the specific direction distribution information used for detecting the image quality change in a specific direction intersects or is orthogonal to the specific direction (non- This is information on the entire image that is not divided in a specific direction. Such specific direction distribution information indicates that for a short specific direction image quality change (short banding, etc.) with a short length in the non-specific direction, Information on a portion where a short image quality change has not occurred. For this reason, it is influenced by the information of the portion where the short image quality change does not occur, and the specific direction distribution information that sufficiently reflects the information of the portion where the image quality change occurs cannot be obtained. In such specific direction distribution information, for a short image quality change, a specific change indicating the image quality change does not appear sufficiently, and there is a possibility of causing a detection omission.
On the other hand, in this aspect, as the specific direction distribution information used for detecting the image quality change in the specific direction, information generated for each of two or more image regions obtained by dividing the image in the non-specific direction is used. . Therefore, when a short image quality change has occurred, specific direction distribution information can be obtained for an image region corresponding to a non-specific direction location where the short image quality change has occurred. The specific direction distribution information of the image area is the information of the information in the non-specific direction where the short image quality change has not occurred, compared to the specific direction distribution information of the image area in which the image is not divided in the non-specific direction, that is, the entire image. There is little influence. Therefore, by using the specific direction distribution information of the image area, even if an image portion in which the image quality change in the specific direction occurs is short in the non-specific direction, it can be detected appropriately. .

(Aspect B)
In the aspect A, the image quality change detection unit is configured to determine an image quality change index such as a color difference between sections obtained by classifying each image area in the specific direction based on the specific direction distribution information for each of the two or more image areas. A value is calculated, and an image quality change in the specific direction is detected based on the calculated image quality change index value.
According to this, it is possible to easily detect the specific direction position where the image quality change occurs, the degree of the image quality change, and the like. As the image quality change index value, for example, color difference can be used if the optical data of the image is color space data including color information, and for example, if the optical data of the image is luminance data of only luminance information, A luminance difference can be used.

(Aspect C)
In the aspect B, the section is set so as to partially overlap an adjacent section.
According to this, it is possible to obtain a more detailed image quality change index value.

(Aspect D)
In the aspect B or C, the image quality change detecting unit detects the image quality change in the specific direction based on an image quality change index value exceeding a predetermined threshold.
According to this, it is possible to appropriately detect a remarkable change in image quality by distinguishing noise components.

(Aspect E)
In any one of the aspects B to D, the image quality change index value is a color difference value between sections of each image area.
By using the color difference value as the image quality change index value, it is possible to extract a change in image quality that is easily perceived by humans with high accuracy from a color image.

(Aspect F)
In any one of the aspects B to E, the image quality change detecting unit is configured to detect, for each position in the specific direction, a maximum image quality change indicating a maximum image quality change among image quality change index values of the two or more image regions. An index value (maximum color difference or the like) is selected, and a change in image quality in the specific direction is detected based on each selected maximum image quality change index value.
According to this, a change in image quality can be detected easily and stably.

(Aspect G)
In the aspect F, the image quality change detection means detects the image quality change in the specific direction based on the sum of the maximum image quality change index values at each position in the specific direction.
According to this, the overall image quality evaluation of the evaluation target image can be performed.

(Aspect H)
In any one of the aspects A to G, the image quality change detection means outputs a quality determination result of the image quality change on the image determined according to a predetermined determination criterion based on the detection result of the image quality change in the specific direction. It is characterized by outputting.
According to this, it is possible to objectively determine whether the image quality is good or bad.

(Aspect I)
In any one of the aspects A to H, the image quality change detection means includes a storage unit such as a storage unit 101b that stores the frequency characteristics of the image quality change in the specific direction and the image quality change occurrence cause information in association with each other. Based on the frequency characteristic (peak frequency or peak generation period, etc.) of the image quality change in the specific direction obtained from the specific direction distribution information, the image quality change occurrence cause information associated with the frequency characteristic is referenced with reference to the storage means Is output.
According to this, when the image quality change exceeding the allowable range occurs, the cause information can be objectively specified.

(Aspect J)
An image quality change detection method for detecting a change in image quality in a specific direction on an image based on specific direction distribution information indicating a distribution in a specific direction of optical data of an image formed by an image forming apparatus. The image quality change in the specific direction is detected based on specific direction distribution information for each of two or more image regions obtained by dividing the image in a direction intersecting or orthogonal to each other.
According to this, even if the image portion in which the image quality change in the specific direction occurs is short in the non-specific direction, it can be appropriately detected.

(Aspect K)
An image quality change detecting device comprising image quality change detecting means for detecting an image quality change in a specific direction on the image based on specific direction distribution information indicating a distribution in a specific direction of optical data of the image formed by the image forming apparatus An image quality change detecting program for causing the computer to function as the image quality change detecting means, wherein the image quality change detecting means is obtained by dividing the image in a direction intersecting or orthogonal to the specific direction. A change in image quality in the specific direction is detected based on specific direction distribution information for each of two or more image regions.
According to this, even if the image portion in which the image quality change in the specific direction occurs is short in the non-specific direction, it can be appropriately detected.

  Note that the above-described program can be distributed or obtained in a state of being recorded on a recording medium such as a CD-ROM. In addition, the above-described program is loaded, and the signal transmitted by a predetermined transmission device is distributed or received via a transmission medium such as a public telephone line, a dedicated line, or another communication network. Available. At the time of distribution, it is sufficient that at least a part of the computer program is transmitted in the transmission medium. That is, it is not necessary for all data constituting the computer program to exist on the transmission medium at one time. The signal carrying the above-described program is a computer data signal embodied on a predetermined carrier wave including a computer program. Further, the transmission method for transmitting a computer program from a predetermined transmission device includes a case where data constituting the program is transmitted continuously and a case where it is transmitted intermittently.

DESCRIPTION OF SYMBOLS 10 Image forming unit 11 Photosensitive drum 15 Intermediate transfer belt 20 Secondary transfer part 40 Control part 44 Image processing part 46 Fixing part 56 Display monitor 70, 71 Image reading means 100 Image quality evaluation apparatus 101 Personal computer main body 101a Arithmetic part 101b Storage part 102 Scanner 103 Monitor 200 Image forming apparatus

JP 2014-238624 A

Claims (11)

An image quality change detecting device comprising image quality change detecting means for detecting an image quality change in a specific direction on the image based on specific direction distribution information indicating a distribution in a specific direction of optical data of the image formed by the image forming apparatus In
The image quality change detection means detects the image quality change in the specific direction based on specific direction distribution information for each of two or more image areas obtained by dividing the image in a direction intersecting or orthogonal to the specific direction. An image quality change detection device characterized by: The image quality change detection device according to claim 1,
The image quality change detecting means calculates an image quality change index value between sections obtained by classifying each image area in the specific direction based on the specific direction distribution information for each of the two or more image areas, and calculates the calculated image quality An image quality change detection apparatus that detects an image quality change in the specific direction based on a change index value. The image quality change detection device according to claim 2,
The image quality change detection apparatus according to claim 1, wherein the section is set so as to partially overlap an adjacent section. In the image quality change detection device according to claim 2 or 3,
The image quality change detecting device, wherein the image quality change detecting means detects an image quality change in the specific direction based on an image quality change index value exceeding a predetermined threshold. The image quality change detection device according to any one of claims 2 to 4,
The image quality change detection device, wherein the image quality change index value is a color difference value between sections of each image area. The image quality change detection device according to any one of claims 2 to 5,
The image quality change detection means selects, for each position in the specific direction, a maximum image quality change index value indicating the maximum image quality change index value among the image quality change index values of the two or more image areas, and selects each selected maximum image quality change An image quality change detection apparatus that detects an image quality change in the specific direction based on an index value. The image quality change detection device according to claim 6,
The image quality change detecting device, wherein the image quality change detecting means detects an image quality change in a specific direction based on a sum of maximum image quality change index values at each position in the specific direction. The image quality change detection device according to any one of claims 1 to 7,
The image quality change detection device, wherein the image quality change detection means outputs a quality determination result of an image quality change on the image determined according to a predetermined criterion based on the detection result of the image quality change in the specific direction. The image quality change detection device according to any one of claims 1 to 8,
Storage means for storing the frequency characteristics of the image quality change in the specific direction and the image quality change cause information in association with each other;
The image quality change detection means refers to the storage means based on the frequency characteristics of the image quality change in the specific direction obtained from the specific direction distribution information, and outputs image quality change cause information associated with the frequency characteristics. An image quality change detection device characterized by the above. In an image quality change detection method for detecting a change in image quality in a specific direction on an image based on specific direction distribution information indicating a distribution in a specific direction of optical data of an image formed by an image forming apparatus,
A change in image quality in the specific direction is detected based on specific direction distribution information for each of two or more image areas obtained by dividing the image in a direction intersecting or orthogonal to the specific direction. Change detection method. An image quality change detecting device comprising image quality change detecting means for detecting an image quality change in a specific direction on the image based on specific direction distribution information indicating a distribution in a specific direction of optical data of the image formed by the image forming apparatus An image quality change detection program for causing the computer to function as the image quality change detection means,
The image quality change detecting means detects image quality change in the specific direction based on specific direction distribution information for each of two or more image areas obtained by dividing the image in a direction intersecting or orthogonal to the specific direction. A program for detecting image quality changes.