JPH09233423A - Image data converting method for digital printer - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a high-quality digital image based on a face area extracted from a film image. SOLUTION: R, G and B signals are converted into luminance signals and chrominance signals by a converting means 11. The face area is extracted by a face area extraction processing means 12. A face area size is found by a face size estimating means 13. Based on a face area size signal, an edge emphasizing means 14 performs edge emphasis processing to the luminance signals. Concerning this edge emphasis processing, the more the face size is reduced, the more the degree of edge emphasis is improved. A gradation correcting means 20 and a color tone correcting means 22 perform correction for eliminating the deviation of input and output systems. The luminance signals and chrominance signals are converted into the R, G and B signals by a converting means 21. Based on these converted image data, an image recording controlled variable converting means 23 converts an image into a recording controlled variable and afterwards, the image is recorded by an image recording means 24. Since the image is processed corresponding to the face area size, the suitable method of picture quality improvement corresponding to scenes can be adopted and picture quality can be improved.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image data conversion method of a digital printer for digitally image-processing original image data of a photograph or digital camera and recording the image.

[0002]

2. Description of the Related Art When an image is recorded on a recording material based on image data obtained by picking up an image of a photographic film, various kinds of image processing are performed to improve the quality of the recorded image. For example, in Japanese Patent Laid-Open No. 7-159904, image quality correction is performed on a photographed image based on photographing information input at the time of photographing. The shooting information includes shooting distance information, continuous shooting information, flash light emission information, shutter speed information, subject brightness information, and edge (contour) enhancement and contrast enhancement are performed as image quality correction. For example, according to the shooting distance information, when the shooting distance is a reference distance, for example, 2 m or more, the image quality is corrected by edge enhancement. This makes it possible to improve the blurring of the image even if the subject distance becomes long and the focus becomes unfocused and the image becomes blurry. In addition, JP-A-4-2844
Japanese Patent Laid-Open No. 42-42 proposes a printer having a means for obtaining a correction amount for changing the gradation according to the photographing information and a means for changing the gradation according to the correction amount.

[0003]

However, since the above-mentioned edge enhancement correction uses shooting information such as shooting distance information stored at the time of shooting, it is applied to a photo film in which shooting information is not recorded. There is a problem that you cannot do it. Further, there is a problem that it cannot be applied to an image of a photographic film taken by a camera that shoots with a fixed shooting distance, shooting magnification, etc., or an image taken by a digital camera or the like.

[0004]

In order to achieve the above object, an image data conversion method of a digital printer according to claim 1 extracts a face image area of a person based on the image data and determines the size of the face image area. Alternatively, the image processing method is changed depending on the presence or absence of the face image area. The image processing method is preferably changed by changing the size of edge enhancement or changing the gradation. In particular, it is preferable to gradually increase the degree of edge enhancement as the face image area becomes smaller. Further, the gradation may be gradually hardened as the face image area becomes smaller.

According to a sixth aspect of the image data conversion method of the digital printer, a face image area of a person is extracted based on the image data, and different image processing is performed on the face image area and the background area excluding the face image area. The method is applied. In this case, it is preferable to increase the degree of edge enhancement as the face image area becomes smaller, or to make the gradation harder as the face image area becomes smaller. In addition, a reference area size is determined for the size of the face image area, and in the case of this reference area size, the degree of edge enhancement for the face image area and the background area is set to be the same, and the face area is larger than the reference area size. If it is small, the edge emphasis degree of the background area is made larger than that of the face image area.If the face area is larger than the reference area size, the edge emphasis degree of the background area is made larger than that of the face image area. It is preferable to make it smaller. Further, a minimum area size and a maximum area size are determined for the size of the face image area, and if the face image area size is between the minimum area size and the reference area size, the face image area size is the minimum area size or The difference between the edge enhancement degrees for both areas is set to gradually decrease as the area approaches the reference area size. If the face image area size is between the reference area size and the maximum area size, the face image area size is set to the maximum area. It is preferable to set such that the difference between the edge enhancement degrees for both areas gradually increases as the size approaches. In addition to the edge enhancement, the above setting may be performed when changing the degree of hardness of gradation. Further, it is preferable that the image data is separated into a luminance signal and a color signal, and the edge enhancement is performed on the luminance signal. In this case, a change in color tone due to the edge enhancement can be suppressed.

[0006]

1 is a functional block diagram showing a digital printer embodying the present invention. The R, G, B image signals digitized from a recording medium such as MD or MO, a digital camera, a color film scanner, etc. are input to the image signal input means 10, and the R, G, B image signals are converted by the conversion means. Sent to 11. In addition, analog R,
The G and B image signals are A / D converted by the built-in A / D converter.

The converting means 11 separates the R, G and B image signals into a luminance signal and a color signal. The conversion to the luminance and color signals is performed by a known conversion method, for example, in addition to the luminance signal and the color difference signal, L, a, b space, L, u ^* , v ^* space, L, H, S.
You may perform by the conversion method using etc. The separated luminance signal and color signal are sent to the face area extraction processing means 12.

The face area extraction processing means 12 extracts a face area. The extraction of the face area is performed, for example, in Japanese Patent Laid-Open No. 52-15
As described in Japanese Patent No. 6624 and Japanese Patent Application Laid-Open No. 52-156625, the range of the luminance signal and the color signal corresponding to the skin color area is determined in advance, and the luminance signal and the color signal of each pixel are set to the skin color area. When it is inside, the point is judged to be skin color. Similarly, it is determined whether or not the other points are flesh-colored, and one group of areas having the flesh-color is extracted as the flesh-colored area based on the determination result. Further, whether or not the extracted skin color area includes areas different from the skin color due to eyes, nose, mouth, eyebrows, etc. is determined by a predetermined pattern (this pattern statistically represents various shooting scenes). It is determined that the person's face area is provided when these different areas are arranged in a predetermined pattern. The face area may be determined only from the skin color area without performing the complicated algorithm for face determination as described above. Further, as in JP-A-5-100328 and JP-A-5-165120, a cluster is obtained from a two-dimensional histogram of hue and saturation, and the face area is determined from the internal structure and shape of the cluster and the external structure to be connected. You may use the method of doing.

The face size estimating means 13 specifies the size of the face area and generates a face area size signal. As the face area size, the length in one direction (X direction, Y direction, arbitrary direction) of the area specified as a face is used. In addition, the number of pixels in one direction, the maximum value of the length or the number of pixels in one direction, the average value of the length or the number of pixels in two orthogonal directions, the area of the face area, the number of pixels of the face area, The area or the 1/2 power of the number of pixels can be used. Furthermore, the ratio to the screen size (for example, the length of the face area in the long side direction of the screen: the length in the long side direction of the screen),
It may be expressed as a ratio with the actual face. Further, when there are a plurality of faces, an average value of face area sizes in all face areas may be used. Furthermore, a weighted average value may be used in which the weighted coefficient is increased as the position is closer to the center position of the screen. The face area size signal and the brightness signal of the face size estimating means 13 are sent to the edge enhancing means 14.

As shown in FIG. 2, the edge enhancing means 14
Is an unsharp signal generator 15, a look-up table memory (LUT) 16, multipliers 17 and 18, an adder 1
9 is provided. The unsharp signal creation unit 15 creates an unsharp signal U by averaging the luminance signal. L
The UT 16 is a weighting coefficient generating means, and based on the face area size signal F, the weighting coefficients P (F) and Q (F).
Occurs. These unsharp signal U, luminance signal Y,
The weighting factors P (F), Q (F) are calculated by the multipliers 17, 18
After being multiplied by, the result is added by the adder 19 to obtain the luminance signal T after the edge enhancement processing. This brightness signal T is sent to the gradation correction means 20.

The brightness signal T is expressed by the following equation 1, for example.

[Equation 1] T = P (F) · U + Q (F) · Y

When K is set as follows in the equation 1, it can be replaced by the following equation 2.

## EQU00002 ## T = Y + K (Y-U) P (F) =-K (where K is an edge enhancement coefficient, -1
≦ K ≦ 1) Q (F) = 1 + K When set as above, P (F) + Q (F) is 1
However, the value of Q (F) (1 + K) may be changed to "1". In this case, P (F) + Q
(F) does not become 1.

FIG. 3 is a diagram showing an example of table data stored in the LUT 16. The horizontal axis represents the face area size f, and the vertical axis represents the edge emphasis coefficient K. The edge emphasis coefficient K increases as the face area size f decreases. Further, when there is no face, a predetermined value a is given. Conversely, as the face area size f increases, the edge emphasis coefficient K decreases. Then, when the face area size f exceeds a certain size, a predetermined value b (b <a) is given. By doing this, the face area size f
As becomes smaller, the degree of edge enhancement gradually increases, and the nose and eyes become clearer. Further, when no person is photographed, the maximum edge enhancement in the system is performed regardless of the shooting distance. Further, as the face area size f increases, the degree of edge enhancement gradually decreases accordingly, and noise of the input device, facial pores, etc. are not conspicuous, and the skin feeling is not lost. If the face area size f is large and the edge is emphasized too much, noise and pores of the input device may be noticeable.
Since the skin feel is lost, b is preferably smaller than "0".

As shown in FIG. 1, the gradation correction means 20 includes
Gradation correction is performed on the edge-emphasized luminance signal T.
This gradation correction is performed in order to correct a shift or the like caused by a difference between the input recording medium and the output recording medium.
The gradation-corrected luminance signal is sent to the conversion means 21. Further, the color tone correction unit 22 performs color tone correction. This color tone correction is performed in order to correct a color tone shift or the like caused by a difference between the input system and the output system recording medium. These gradation correction processing and color tone correction processing are performed using known methods. The color tone-corrected luminance signal is sent to the conversion means 21. If these gradation correction and color tone correction are performed with reference to the average density and color tone of the face area extracted by the face area extraction processing means 12, the finish will be further improved.

The conversion means 21 converts the luminance signal and the color signal into R, G and B signals. The R, G, B signals are sent to the image recording control amount conversion means 23. The image recording control amount conversion means 23 converts the R, G, B signals into image recording control amounts and also performs D / A conversion. These R,
Well-known methods are used for the conversion processing into G and B signals, the image recording control amount conversion processing, and the like. The converted image recording control amount is sent to the image recording means 24, where the image recording control amount is converted into the optical signal intensity of laser light or the like and the aperture ratio of the liquid crystal shutter, whereby an image is recorded on the color photosensitive material. To be done. The conversion unit 21 may directly convert the main scan image data into the image recording control amount.

In the above embodiment, the gradation correction and the color tone correction are performed before the conversion into the R, G, B signals by the conversion means 21. Tone conversion and color correction may be performed. Further, in the above-described embodiment, when edge enhancement is performed, the corresponding weighting factors P (F) and Q are calculated from the LUT 16 based on the face area size signal F.
(F) was obtained, but instead of using this LUT16,
The functional expressions of P (F) and Q (F) may be calculated by a calculator. Further, in the above-described embodiment, the maximum edge enhancement is performed when no person is shown, but in addition to this, an appropriate edge enhancement degree may be set separately. Further, in the above embodiment, the conversion means 11 for converting the R, G, B signals into the luminance signal and the color signal is provided. However, in the case where the luminance signal and the color signal are input in the separated state from the beginning, The luminance signal and the color signal are input to the face area extraction processing means 12 without using the conversion means 11.

Next, another embodiment for picking up an image recorded on a negative film and printing the image will be described.
FIG. 4 shows a functional block diagram of the digital printer in this embodiment. This digital printer is roughly divided into an image signal input unit 30, an image data storage unit 31, a gradation balance detection unit 32, a gradation conversion characteristic setting unit 33, and a conversion table creation unit 34.
Face area extraction processing means 12 and face size estimation means 1
3, image signal processing means 35, image recording control amount converting means 23, and image recording means 24. In addition,
The same components as those in the embodiment shown in FIG. 1 are designated by the same reference numerals.

The image signal input means 30 is composed of a well-known film scanner and reads an image of a negative film and converts it into an image signal. This image signal input means 3
In 0, the main scan and the prescan can be performed. In the prescan, the image of the negative film is read as the image data of several thousand points. Note that the number of image data in the pre-scan is not limited to several thousand, and several hundred to tens of thousands of image data may be read out in response to a request such as shortening of processing time or improvement of print quality.
In this scan, the image of the negative film is in the hundreds of thousands.
Read out as millions of image data. In addition to performing the prescan and the main scan, the image data of the main scan may be combined to reduce the number of pixels from hundreds of pixels to tens of thousands of pixels, and this may be used as the prescan image data.

In FIG. 4, the flow of image data of the main scan is shown by a broken line, and the flow of image data of other prescans is shown by a solid line. The image data of the main scan from the image signal input means 30 is sent to the face area extraction processing means 12 and the image signal processing means 35. The prescan image data from the image signal input means 30 is sent to the image data storage means 31.

The film type identifying means 40 is composed of a bar code reader, and reads the DX bar code of the color negative film to be read to identify the type of film. This film type signal is sent to the image data storage means 31 and the gradation characteristic data storage means 41. A magnetic reader is used for a negative film on which magnetic information is recorded.

The image data storage means 31 comprises a data selection section and a data storage section. The data selection unit selects the prescan image data for each film type according to a predetermined selection criterion. Then, the selected image data is sent to the data storage unit. As the selection criterion, the average value of the image data of the corresponding film type stored in the data storage unit is used. Therefore, only the image data within the predetermined range is selected based on the average value, and this is stored in the data storage unit. Instead of the average value, a value determined by a statistical method such as the least square method may be used as the selection criterion. The image data selected in this way has an image density of a subject color of a gray or a certain range close to gray.

The data storage section stores the R density corresponding to the G density of the image data, the B density corresponding to the G density, and the number of these image data in the corresponding storage area based on the film type signal. In this embodiment, the G density is used as a classification standard for image data. Then, it is determined to which level the G density value of the image data corresponds to, for example, a level classified at 0.01 intervals or 0.1 intervals, and R density and B density are accumulated at the corresponding levels. At the same time, the number of accumulated data is also counted and stored. Next, the accumulated image data is divided by the number of accumulated data to obtain an average value. The method of accumulating image data is described in detail, for example, in Japanese Patent Application Laid-Open No. 3-53235. The average value of a large number of accumulated data obtained in this way is constant and becomes gray or a color close to gray. As the accumulation progresses, the unique data of this film species can be obtained with high accuracy.

The tone balance detecting means 32 obtains tone balance characteristics based on the average value from the image data accumulating means 31. FIG. 5 shows an example of the detected gradation balance characteristics, and shows the relationship between the R density and the G density as an average value of accumulated data at each density level. When represented by the average value of each density level, a large number of points are arranged on a line as shown in FIG. 5, but a known smoothing process is performed on each of these points to form a straight line or a smooth curve. Fix it. Similarly, the relationship between the B concentration and the G concentration is created.

FIG. 6 is an example of the gradation balance characteristic data showing the relationship between the R density and the G density, which is obtained by smoothing the data shown in FIG. In FIG.
The three-color average density of the maximum density value in the recording target original image
The high density side reference value DXG is set, the R density for DXG is obtained from the gradation balance characteristics based on this DXG, and this is set as DXR. Similarly, DXB is obtained from the relationship between the G concentration and the B concentration. DXG, DXR, and DXB are R, G, and B densities for obtaining a gray density in DXG. Similarly, the G concentration DIG of the low concentration side reference value
DIR and DIB are obtained using (the three-color average density of the minimum density value in the original image to be recorded) as the low density side reference value. DXR, DXG, DXB, DIR, D obtained in this way
IG and DIB represent the color balance of the high-density gray subject and the low-density gray subject in the original image, and these are defined as the high-density side reference balance value and the low-density side reference balance value. In this embodiment, the three-color average density is used as the high-density side reference value and the low-density side reference value, but the corresponding colors of maximum density and minimum density may be used. Each of the obtained reference balance values DXR, DXG, DXB, DIR, DIG,
The DIB is sent to the gradation conversion characteristic setting means 33.

The gradation conversion characteristic setting means 33 includes the gradation characteristic data from the gradation characteristic data storage means 41 and the reference balance values DXR and DX from the gradation balance detecting means 32.
The gradation conversion characteristic is set based on G, DXB, DIR, DIG, and DIB. First, as shown in FIG. 7, the high-density side reference balance value DXi (i is one of R, G, and B)
3) and the low-density-side reference balance value DIi are used to create a gradation balance conversion table. That is, the recording density determined in advance with respect to the reference balance values DXR and DIR is Dh.
r and Dsr, and DXR and Dhr, DIR and Ds
A gradation balance conversion table is created by connecting the coordinate points determined by r and. Similarly, other B concentration, G
A tone balance conversion table is also created for the density.

FIG. 7 shows an example of this gradation balance conversion table, in which the abscissa axis represents the R density which is the input value, and the ordinate axis represents the R density which is the output value. As described above, since the recording densities Dhi and Dsi are determined and uniformly assigned to all the densities in the meantime, it is not always possible to record a negative image of underexposure as a natural image. Therefore, a gradation conversion table is created using the gradation characteristic data shown below.

The gradation characteristic data is stored in the gradation characteristic data storage means 41 shown in FIG. The gradation characteristic data is stored for each film type, and the corresponding gradation characteristic data is sent to the gradation conversion characteristic setting unit 33 by the film type identification signal from the film type identification unit 40. FIG. 8 shows an example of the gradation characteristic data. The gradation characteristic data is composed of a conversion table corresponding to the characteristic curve of the color negative film. In this conversion table, the horizontal axis represents the output value Dout and the vertical axis represents the input value Din. Then, the output value Dout is obtained from the input value Din based on this conversion table. As can be seen from the gradation characteristic data, the foot portion and the shoulder portion of the characteristic curve are not straight lines, and the image density is compressed. The shape of the characteristic curve varies depending on the light-sensitive color developing layer and the color film type, but due to the progress of the film latitude and the exposure technology of the camera, it is rarely used even on the shoulder. Since the characteristics of the foot portion are similar for each film, an average conversion table may be used, and there is no particular need for each color. In order to obtain accurate gradation characteristics, the film density is measured for each film type and this measured value is used. Alternatively, a gradation conversion table may be set by trial and error and selection may be made based on the film type signal. Further, the characteristic curve may be expressed by a functional expression instead of being expressed in the form of a conversion table.

Next, the gradation conversion characteristic setting means 33 specifies the use range of the gradation characteristic data shown in FIG. 8 from the high density side reference balance value DXi and the low density side reference balance value DIi of the original image, The gradation characteristics in this range and the gradation balance conversion table shown in FIG. 7 are combined to create a gradation conversion table as shown in FIG. That is, by replacing the value on the horizontal axis of the gradation balance conversion table with the value on the vertical axis of the corresponding characteristic curve using the gradation characteristic data shown in FIG. 8, the gradation conversion table as shown in FIG. To create.
The solid line display in FIG. 9 is the underexposure negative image, and the broken line display is the proper exposure negative image. In the case of an underexposed negative image of a solid line display, the contrast (difference between DXi and DIi) becomes small with respect to the gradation balance characteristic of the image by proper exposure, and the recorded image has no shadow portion, It can be seen that the image is improved when the density of the low density portion image is enlarged and recorded. As another method, each value of DIR to DXR is set to Din and converted to Dout, and the same effect can be obtained by using the horizontal axis of the gradation balance table of FIG. The correction of the gradation conversion table may be performed for each image, or a plurality of corrected tables may be prepared and selected. In addition, as another method, since the gradation characteristic data does not require high accuracy, a known method,
For example, the density histogram or density cumulative distribution may be automatically obtained from the prescan image data of the original image and used.

The conversion table creating means 34 is a recording condition and image recording basic amount calculating means 4 from the recording condition storing means 42.
The gradation conversion table from the gradation conversion characteristic setting means 33 is corrected based on the image recording basic amount from 7. This correction is performed by vertically shifting the gradation conversion characteristic based on the image recording basic amount along the vertical axis of the gradation conversion table. This corrected gradation conversion table is written in the LUT 45 of the image processing signal means 35. The reason why the gradation conversion table is modified based on the image recording basic amount is as follows. If the maximum reference value, the minimum reference value, or the highlight point and the shadow point to be reproduced are accurate, the correction by the image recording basic amount is not necessary. A typical example of such a scene is a portrait in a photo studio. The highlight point is, for example, white of clothes, and the shadow point is, for example, black hair. On the other hand, the portrait against the background of the natural world is not necessarily so. There are many highlights, such as the sky and clouds, white walls and windows that reflect light, and white foreground in flash photography. Except for them, it is very difficult to accurately extract the white of clothes, and in many cases, correction based on the image recording basic amount is necessary.

The image recording basic amount calculation means 47 obtains the image recording basic amount based on the prescan image data from the image signal input means 30. The image recording basic amount is a value obtained from the image density of the original image for each original image to be recorded. For example, based on the prescan image data, the entire screen area,
A simple average value in each area such as a specific area and a selected area is calculated, and these are selectively used. In addition to this, as the image recording basic amount, an average value of weighted addition for pixel positions, an average value of selected pixels, an average value of weighted addition, and the like are used. The basic amount of image recording is disclosed in JP-A-55-26569 and JP-A-61-223731.
Japanese Patent Laid-Open No. 2-90140, Japanese Patent Laid-Open No. 3-53
It can be determined using a known method such as those described in JP-A No. 235, JP-A No. 5-289207, and the like. Further, the image recording basic amount is a weighted average value of the maximum value (or the density of the highlight portion) and the minimum value (or the density of the shadow portion), or a weighted average value obtained by multiplying each pixel by the weight (for example, the density histogram A value that characterizes the image of the original image, such as a weighted average value obtained by multiplying each class by a weight), a value corresponding to the specific frequency or the selected frequency of the cumulative density histogram, or the like can be used as the image recording basic amount. Alternatively, a density control value may be used. In this case,
JP-A-51-138435, JP-A-53-145
It can be determined by known methods such as those described in JP-A No. 621, JP-A-54-28131, JP-A-59-164547 and the like.

Further, the image signal processing means 35 is provided with an edge enhancing means 46, and performs edge enhancing processing on the main scan image data. The edge enhancing means 46 has the same structure as the edge enhancing means 14 shown in FIG.
In the above embodiment, the edge enhancement processing is performed on the luminance signal Y, whereas the present embodiment is different only in that it is performed on the main scan image data.
Detailed description is omitted. The edge-enhanced main scan image data is converted into recorded image data by the LUT 45. By this conversion, the R, G, and B signals are made equal in the case of a gray image, and a recorded image with excellent color balance can be obtained. The recorded image data is converted into an image recording control amount by the image recording control amount conversion unit 23, and then an image is recorded on the recording material by the image recording unit 24.

In the above embodiment, the image recording basic amount calculation means 47 calculates the image recording basic amount and the gradation conversion characteristic is corrected based on the obtained basic amount. The conversion table creating means 34 may correct the conversion table using the average density value of the face area. In this case, when the size of the face area is smaller than a predetermined value, or when the face area is not extracted, the face area extraction processing unit 12 may obtain the average density of all the areas of the screen and use this average density. preferable.

In the above embodiment, the edge emphasis means 46 changes the degree of edge emphasis according to the size of the face area. However, in addition to this, the conversion table creating means 34 shown in FIG. The signal F may be input to change the gradation according to the size of the face area. This is because the effective MTF (modulation transfer function) of the system is expressed by “the MTF of the system” × “the gamma of the system”, so that the MTF may be hardened instead of the sharpness (MTF). Depends on going up. Therefore, as the face size becomes smaller, the gradation becomes harder, and a predetermined value is used when the face does not exist or is too small for detection. Further, the gradation is set softer as the face size increases. The gradation is changed by multiplying the gradation characteristic curve by a coefficient determined from the size of the face size. In addition to this, it may be determined by interpolation from a gradation characteristic curve that is determined and stored in advance.

Further, the gradation may be changed in a specific density range. For example, as shown in FIG.
In the case of correction by the main part density DpO, the gradation conversion table is corrected as indicated by the chain double-dashed line. In addition, Dp
O represents the main part density of the original image, and DpR represents the data necessary to obtain the proper main part density of the recorded image. FIG.
This is an example in which the density of the main part is increased to prevent the reproduction of the image in the highlight part from changing as much as possible and the gradation is hardened. Further, FIG. 11 shows an example in which the density of the main part is not changed and the image density of the highlight part is lowered to harden the gradation. In addition to this, the gradation of the highlight part may be changed rather than the density of the main part without changing the gradation of the main part density much. In addition, practically, the conversion table is used after being modified so as to have a smooth curve.

Further, instead of the main part densities DpO and DpR, a value consisting of the correction amount of the recorded image density estimated from the image feature amount of the original image and the added value of the average densities of all the recorded images is DpO, It may be DpR.

The edge emphasis coefficient and the gradation parameter may be changed between the face area in one image and the background area excluding this face area. For example, the edge emphasis coefficient of the face area or the gradation parameter is changed according to the face area size signal. Or, depending on the face area size signal,
Change the edge enhancement coefficient of the background area or the gradation parameter.

FIG. 12 shows an example in which the edge emphasis coefficients of the face area and the background area are individually changed. A reference area size fs is determined with respect to the face area size f, and in the case of this reference area size fs, the edge enhancement coefficient K for the face area and the background area is set to the same value c, and the face area size fs is larger than the reference area size fs. When the area size f is small, the edge emphasis coefficient K of the background area is made larger than the edge emphasis coefficient K of the face area, and when the face area size f is larger than the reference area size fs, the edge emphasis coefficient K of the background area. Is set to be smaller than the edge emphasis coefficient K of the face area. Further, a minimum area size fmin and a maximum area size fmax are determined for the face area size f, and the face area size f is the minimum area size fmin.
And between the reference area sizes fs, the difference between the edge enhancement coefficients K for both areas is set to gradually decrease as the face area size f approaches the minimum area size fmin or the reference area size fs. Further, when the face area size f is between the reference area size fs and the maximum area size fmax, the difference between the edge emphasis coefficients K for both areas gradually increases as the face area size f approaches the maximum area size fmax. Set to.

In this case, when the face area size f is larger than the reference area size fs, the background edge is not emphasized. Further, as the face area size f becomes smaller than the reference area size fs and approaches the predetermined value fd, the edge of the background area is emphasized more than the face area. Then, when the face area size f exceeds the predetermined value fd and becomes smaller, the difference between the two gradually disappears, and when there is no face area (when the face area size f becomes fmin), the edge emphasis degree of both is the same. become. It should be noted that if the edge emphasis coefficient changes greatly at the boundary between the face area and the background area, an unnatural image will result, so it is advisable to smoothly change these boundary areas. Further, it is preferable that the edge emphasis coefficient of the face area and the background area can be set in the apparatus from the outside. Further, the same can be done when changing the gradation parameter instead of edge enhancement.

Next, with reference to FIG. 13, another embodiment relating to conversion by gradation characteristic data will be described. The same components as those in the embodiment shown in FIG. 4 are designated by the same reference numerals. In this embodiment, the gradation characteristic conversion means 50
Thus, the main scan data is converted to linearly correct the non-linear characteristic of the negative film. After this conversion, the face area extraction processing means 12 extracts the face area. The conversion table creating means 51 creates a data conversion table for correcting the three-color density balance and performing gradation correction according to the face area size. The image signal processing means 52 uses this data conversion table to convert the main scan data. Instead of the gradation correction according to the face area size, the image signal processing unit 52 may perform edge enhancement according to the face size.
In addition, the conversion table creating means 51 may create a density correction data conversion table for the face area in addition to the gradation correction data conversion table according to the face area size, thereby further improving the finish of the face area. You can get better.

In the present invention, the density is not limited to the optical density and includes a conversion value corresponding to the lightness in chromatics, a photometric output value of the original image, a halftone dot area ratio and the like. Alternatively, the antilogarithmic value of the concentration may be used. Further, instead of emphasizing the edges, the image or the edges may be smoothed.

Further, in the above embodiment, the face area extraction processing means automatically extracts the face area based on the skin color density. However, in addition to this, the face extraction is performed by using an image simulating the finish. Display it on a display such as a CRT,
This may be done by observing the displayed image and designating the face area using a light pen, a mouse or the like. Further, in the above embodiment, the image data of the digital camera and the image data from the negative film are used.
The present invention may be applied to a positive film or a reflective original. Further, the present invention may be applied to an image display device.

When information such as the magnification between the subject and the image and the subject distance is recorded corresponding to the image,
As described in detail in Japanese Unexamined Patent Publication No. 1-111086, it is effective to use these pieces of information in order to determine the face area.

[0043]

According to the present invention, since image processing such as edge enhancement and gradation correction is performed according to the size of the face area, an appropriate image suitable for the scene is obtained even for an image having no shooting distance information. Image processing can be performed. Moreover, it is possible to surely perform appropriate image processing suitable for the scene, as compared with the conventional one that performs image processing such as edge enhancement according to the shooting distance information. That is, in the conventional art, the shooting distance information is often coarse due to the limitation of the memory capacity and the cost of the camera, and it is difficult to perform appropriate image processing suitable for the scene. Since this is performed, accurate shooting distance information can be obtained.

Since image processing such as edge enhancement and gradation correction is performed based on the size of the face area, an image quality improving method suitable for each image can be adopted. For example, the contour can be emphasized for an image in which the subject is small such as a distant view without deteriorating the image quality of an image taken at a short distance such as a close-up of the face. In addition, it is possible to emphasize microscopic light and shade in a landscape where no person is captured, or to emphasize a person in a group photo. Furthermore, even at a short distance, the shape of an object can be made clearer by performing edge enhancement and gradation correction on an image in which no person is captured.

Further, since the degree of edge enhancement or gradation correction is changed based on the size of the face area, the image quality can be diversified. As a result, the texture of the skin can be improved by slightly unsharpening the face up. At the same time, by further unsharpening the background, it is possible to obtain the effect of defocusing the background. Further, by performing different image processing on the face area and the background area excluding the face area, it is possible to further diversify the image quality improvement.

A reference area size is determined with respect to the size of the face area. In the case of this reference area size, the degree of edge enhancement for the face area and the background area is set to be the same, and the face area is smaller than the reference area size. In this case, the edge emphasis degree of the background area is made larger than the edge emphasis degree of the face area, and when the face area is larger than the reference area size, the edge emphasis degree of the background area is made smaller than the edge emphasis degree of the face area. As a result, it is possible to automatically perform an appropriate edge enhancement process suitable for the scene. Similarly, the same effect can be obtained by changing the gradation hardness level instead of changing the edge enhancement level.

Further, the minimum area size and the maximum area size are determined for the size of the face image area. If the face image area size is between the minimum area size and the reference area size, the face image area size is the minimum. The difference between the edge enhancement degrees for both areas is set to gradually decrease as the area size or the reference area size is approached. If the face image area size is between the reference area size and the maximum area size, the face image area size is set. By setting so that the difference between the edge enhancement degrees for both areas gradually increases as is approaching the maximum area size, the edge enhancement degree and the gradation hard / soft degree can be changed more finely.

[Brief description of drawings]

FIG. 1 is a functional block diagram showing a main part of a digital printer embodying the present invention.

FIG. 2 is a functional block diagram showing edge enhancement means.

FIG. 3 is a diagram showing a relationship between a face area size and an edge enhancement coefficient.

FIG. 4 is a functional block diagram showing a main part of another embodiment.

FIG. 5 is a diagram showing an example of gradation balance characteristic data showing a relationship between R density and G density.

FIG. 6 is a diagram showing an example of gradation balance characteristic data after smoothing the data of FIG.

FIG. 7 is a diagram illustrating how to obtain a high-density and low-density side reference balance value from a gradation balance characteristic.

FIG. 8 is a diagram showing an example of gradation characteristic data.

FIG. 9 is a diagram showing an example of a gradation conversion table.

FIG. 10 is a diagram showing an example of correction of a data conversion table.

FIG. 11 is a diagram showing an example of correction of a data conversion table.

FIG. 12 is a diagram showing a relationship between a face area size and an edge enhancement coefficient in an embodiment in which different edge enhancement coefficients are used for a face area and a background area.

FIG. 13 is a functional block diagram showing a main part of another embodiment.

[Explanation of symbols]

 10 image signal input means 11, 21 conversion means 12 face area extraction processing means 13 face size estimation means 14 edge enhancement means 20 gradation correction means 22 color tone correction means 23 image recording control amount calculation means 24 image recording means 35 image signal processing means

Claims (11)

[Claims] 1. An image data conversion method of a digital printer for recording an image on a recording material based on image data, wherein a face image area of a person is extracted from the image data, and the size of the face image area or the face image area An image data conversion method for a digital printer, characterized in that the image processing method is changed depending on the presence or absence. 2. An image data conversion method of a digital printer for recording an image on a recording material based on image data, wherein a face image area of a person is extracted from the image data, and the size of the face image area or the face image area With or without,
An image data conversion method for a digital printer, characterized in that the degree of edge enhancement is changed. 3. A method of converting image data of a digital printer for recording an image on a recording material based on image data, wherein a face image area of a person is extracted from the image data, and the degree of edge enhancement as the face image area becomes smaller. A method for converting image data of a digital printer, which is characterized by gradually increasing. 4. An image data conversion method for a digital printer, which records an image on a recording material based on image data, extracts a face image area of a person from the image data, and determines the size of the face image area or the face image area. With or without,
An image data conversion method for a digital printer, characterized by changing gradation. 5. An image data conversion method of a digital printer for recording an image on a recording material based on image data, wherein a face image area of a person is extracted from the image data, and gradation is gradually increased as the face image area becomes smaller. An image data conversion method for a digital printer, which is characterized by making it hard. 6. An image data conversion method of a digital printer for recording an image on a recording material based on image data, wherein a face image area of a person is extracted from the image data, and the face image area and a background image area excluding the face image area are extracted. In contrast, a different image processing method is applied to the image data conversion method of the digital printer. 7. The image data conversion method for a digital printer according to claim 6, wherein the degree of edge enhancement is gradually increased as the face image area becomes smaller, or the gradation is gradually made smaller as the face image area becomes smaller. An image data conversion method for a digital printer, which is characterized by making it hard. 8. The digital printer image data conversion method according to claim 6, wherein a reference area size is determined in advance for the size of the face image area, and in the case of this reference area size, a face image area and a background area are set. When the face area is smaller than the reference area size, the edge emphasis degree for the background area is set larger than the edge emphasis degree for the face image area, and the face area is larger than the reference area size. In this case, the image data conversion method for a digital printer is characterized in that the edge emphasis degree of the background area is made smaller than the edge emphasis degree of the face image area. 9. The image data conversion method for a digital printer according to claim 6, wherein the gradation of the face image area and the background area is made harder as the face image area becomes smaller, and the reference area is larger than the size of the face image area. Determine the size, set the gradation for the face image area and background area to be the same for this reference area size, and if the face area is smaller than the reference area size, set the gradation for the background area to the face image area. An image data conversion method for a digital printer, which is harder than the gradation of the area and is softer than the gradation of the face image area when the face area is larger than the reference area size. 10. The image data conversion method for a digital printer according to claim 8, wherein a minimum area size and a maximum area size are determined for the size of the face image area, and the face image area size is the minimum area size and the minimum area size. If it is between the reference area sizes, set so that the difference in the degree of edge enhancement or the difference in the degree of hard and soft gradation is gradually reduced for both areas as the face image area size approaches the minimum area size or the reference area size. , If the face image area size is between the reference area size and the maximum area size, as the face image area size approaches the maximum area size, the difference in edge emphasis degree or the difference in the degree of hard and soft gradation is gradually increased for both areas. Image data conversion of a digital printer characterized by being set to be large Law. 11. The image data conversion method for a digital printer according to claim 2, 3, or 8, wherein the image data is separated into a luminance signal and a color signal, and the edge enhancement is performed on the luminance signal. An image data conversion method for a digital printer, characterized by performing the following.