JP2007128342A - Image decision device, image decision method and image decision program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately decide a defocus at high speed. <P>SOLUTION: A difference in a luminance value between a comparison pixel and a notice pixel apart by a prescribed reference distance in image data is acquired. A small block having a maximum vale of the difference exceeding a prescribed threshold value is set as an edge block, and a small block having the difference not exceeding the threshold value is set as a non-edge block. A plurality of small blocks belong to a large block, and a component ratio of the edge block in each the large block is calculated. It is decided that it is not the defocus when the component ratio exceeds the prescribed reference value, and it is decided that it is the defocus when the component ratio does not exceed the reference value. That is, when the edge block corresponding to an edge having an extreme color change is widely distributed in some small block, it is decided that it is not the defocus. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image determination apparatus, an image determination method, and an image determination program.

Conventionally, a technique for detecting so-called out-of-focus image data that is out of focus when a photograph is taken has been proposed (see, for example, Patent Document 1).
In such a configuration, extraction is performed using the high-frequency component of the color variation of each pixel of the image data, and it is determined that the image data is not out of focus when there are many extracted high-frequency components.
JP 2000-67554 A

However, in order to analyze the high-frequency component of the color fluctuation in the above-described technique, it is necessary to convert the image data into spatial frequency data by Fourier transform or the like, and there is a problem that the processing load is large. In addition, since minute noise is detected as a high-frequency component, there is a problem that a blurred image including minute noise is erroneously determined to be normal.
SUMMARY An advantage of some aspects of the invention is that it provides an image determination apparatus, an image determination method, and an image determination program capable of accurately determining defocus at high speed.

  In order to solve the above problem, in the invention according to claim 1, the image data is composed of a plurality of pixels having color signals. The block setting means sets a plurality of blocks in the image data. The deviation acquisition means acquires the color signals of the pixels separated by a predetermined reference distance in the image data and calculates a deviation between the color signals. For example, when the color system in which the color of each pixel of the image data is expressed is the RGB color system, the RGB value deviation is calculated, and the color system is the YCbCr color system. The deviation of the value of YCbCr is calculated. The deviation is not limited to calculating a single deviation of each element color, and the deviation may be calculated after combining color signal values of a plurality of element colors by a technique such as linear combination.

  The maximum deviation detecting means detects the maximum value of the deviation for each block. That is, since the plurality of deviations are calculated in each block, the largest one is detected for each block. The determination means determines whether the maximum value of the deviation exceeds a predetermined threshold value for each block, and acquires the distribution of the blocks whose maximum value exceeds the predetermined threshold value. Then, the quality of the image data is determined based on whether or not the distribution of the blocks in which the maximum value of the deviation exceeds a predetermined threshold satisfies a predetermined condition.

  It can be said that the block in which the maximum value of the deviation exceeds a predetermined threshold includes a portion where the color change degree at the reference distance is abrupt. Therefore, it can be determined that there is a high possibility that such a block includes the contour of the focused subject. Further, by grasping such a block distribution, the contour shape in the image data can be estimated. Therefore, if the contour shape in the image data corresponds to the shape of the subject in the photograph, it can be determined that the subject in focus is included in the image data. On the other hand, if the contour shape in the image data is not suitable as the shape of the subject in the photograph, it can be determined that the focused subject is not included in the image data. That is, it can be determined that the image data is out of focus.

  Further, as an example of a specific method for determining the distribution of the blocks in which the maximum value of the deviation exceeds a predetermined threshold, in the invention according to claim 2, the determination means includes a plurality of blocks larger than the blocks in the image data. Set a large block. Then, in any one of the large blocks, it is determined whether or not the composition ratio of the block in which the maximum value of the deviation exceeds a predetermined threshold among the blocks belonging to the large block exceeds a predetermined reference value. When the composition ratio of the block in which the maximum value of the deviation exceeds a predetermined threshold in the large block exceeds a predetermined reference value, it is determined that the image data is non-defective. When the composition ratio of the block estimated to be the contour of the subject in the large block is high, it can be considered that the contour of the subject is widely distributed in the large block.

  In other words, if the composition ratio of the block in which the maximum value of the deviation exceeds a predetermined threshold exceeds a predetermined reference value, the in-focus subject exists across the large block. Can think. On the other hand, when the composition ratio of the block in which the maximum value of the deviation exceeds the predetermined threshold in the large block is low, it can be considered that there are only sparse portions with large color fluctuations in the large block. . Such a block can be considered as sharp noise, not the contour of the subject intended by the photographer. Therefore, the image data is determined to be non-defective when the composition ratio of the block in which the maximum value of the deviation exceeds a predetermined threshold in the large block exceeds a predetermined reference value. The image data can be determined as a non-defective product.

  As a preferred example of the reference distance, in the invention according to claim 3, the reference distance is set to be about 0.3 mm when the image data is printed in the size of the L plate. When visually recognizing the L plate, about 0.3 mm is a limit at which a human can perceive color variation. Therefore, by setting the reference distance to about 0.3 mm on the L plate, it is possible to determine the blur that can be perceived by humans.

  Furthermore, as a preferred example of the size of the large block, in the invention according to claim 4, the size of the large block is set to be about 10 mm when the image data is printed in the size of the L plate. Is done. In the L version, it can be considered that a normal subject has a size of at least 10 mm or more. Therefore, in the L version, when the contour of the subject extending over the large block of about 10 mm is detected, It can be estimated that the image data includes a subject that is not out of focus.

  Furthermore, as a preferred example of the size of the large block, in the invention according to claim 5, a luminance deviation calculated from the color signal is acquired as a deviation of the color signal. Since human perception is sensitive to luminance fluctuations, if the luminance fluctuation is gradual, it is easily recognized as out of focus. Therefore, by performing the determination based on the luminance deviation, it is possible to realize the determination of blur that is easily perceived by humans.

  In the invention according to claim 6, each pixel is arranged in a matrix in the image data. The deviation acquisition unit acquires the deviation of the color signal in each of the vertical direction and the horizontal direction of the image data. Thereby, the deviation of the color variation can be acquired for each of the vertical direction and the horizontal direction of the image data, and the contour in each direction can be detected.

  Of course, the above invention can be realized not only by the apparatus but also by an image determination method as in claim 7, and by an image determination program for executing processing according to the method as in claim 8. It can also be realized. In addition, the idea of the invention is that the apparatus, method, and program according to the present invention may be implemented independently, or may be implemented together with other apparatuses, methods, and programs while being incorporated in a certain device. Is not limited to this, and includes various aspects, and can be changed as appropriate. For example, the image determination apparatus of the present invention may be incorporated in an image input device such as a digital still camera.

  Further, it can be provided as a recording medium on which the program of the present invention is recorded. The recording medium for this program may be a magnetic recording medium, a magneto-optical recording medium, or any recording medium that will be developed in the future. In addition, the duplication stages such as the primary duplication product and the secondary duplication product are equivalent without any question. Further, even when a part is software and a part is realized by hardware, the idea of the invention is not completely different, and a part is stored on a recording medium and is appropriately changed as necessary. It may be in the form of being read. In addition, not all functions are necessarily realized by a single program, but may be realized by a plurality of programs. In this case, what is necessary is just to make each function implement | achieve in a some computer.

Here, embodiments of the present invention will be described in the following order.
(1) Computer configuration:
(2) Flow of image determination processing:
(3) Modification:
(4) Summary:

(1) Computer configuration:
FIG. 1 shows a schematic configuration of a computer as an image determination apparatus of the present invention. In FIG. 1, a computer 10 includes a CPU 11, a RAM 12, an HDD 13, a USB interface (I / F) 14, an input device interface (I / F) 15, and a video interface (I / F) 16 connected by an internal bus 10a. The HDD 13 stores various program data 13a and a plurality of image data 13b, 13b, 13b. The CPU 11 reads out the program data 13a and executes processing based on the program data 13a while using the RAM 12 as a work area. A printer 20 and a digital still camera 30 are connected to the USB I / F 14, and a mouse 40 and a keyboard 50 are connected to the input device interface 15. Further, a display 60 is connected to the video I / F 16.

  FIG. 2 shows a software configuration of a program executed on the computer 10. In the computer 10, an operating system (O / S) (not shown) is executed, and an image management program P1 and a printer driver P2 are executed on the O / S. The image management program P1 is roughly composed of an image determination unit P1a and an image management unit P1b. The image management unit P1b provides a function for managing the image data 13b, 13b, 13b... Stored in the HDD 13. Specifically, thumbnails of the image data 13b, 13b, 13b,... Are displayed on the display 60 for each path where the image data 13b, 13b, 13b,. .., 13b... Based on the header information, etc., search for the image data 13b, 13b, 13b..., Delete or copy the image data 13b, 13b, 13b. To go.

  On the other hand, the image determination unit P1a includes a block setting unit P1a1, a deviation acquisition unit P1a2, a maximum deviation detection unit P1a3, and a determination unit P1a4. The block setting unit P1a1 acquires the image data 13b designated as the determination target from the HDD 13, and acquires the vertical and horizontal pixel numbers of the image data 13b described in the header of the image data 13b. Based on the vertical and horizontal pixel counts of the image data 13b, the vertical and horizontal pixel counts of the small block and large block and the pixel count of the reference distance are calculated. Specifically, the vertical and horizontal pixel numbers are set such that the vertical and horizontal lengths of the large square block are 10 mm when the image data 13b is printed in the L size at the print resolution in the photo mode. As for the reference distance, the number of pixels is set such that the distance is 0.3 mm when the image data 13b is printed in the L size with the print resolution in the photo mode. On the other hand, the small block is set smaller than the large block and corresponds to the block of the present invention. For example, the vertical and horizontal lengths are set to be one-tenth the size of a large block.

The deviation acquisition unit P1a2 selects the target pixel from the image data 13b to be determined, and searches for two comparison pixels located at a reference distance from the target pixel leftward and upward. Then, the color signals of the target pixel and the two comparison pixels are acquired. In the present embodiment, since the color of each pixel of the image data 13b is expressed by the RGB value as the color signal value, the RGB values of the target pixel and the two comparison pixels are acquired. Then, the luminance value Y is calculated from the RGB values for the target pixel and the two comparison pixels. The luminance value Y can be calculated by the following known formula.
Y = 0.299 × R + 0.587 × G + 0.114 × B
Then, the luminance value Y of the two comparison pixels is subtracted from the luminance value Y of the target pixel, and the absolute value is calculated as a deviation. Two deviations are calculated for one pixel of interest. The deviation acquisition unit P1a2 calculates a deviation for the entire image data 13b by shifting the target pixel over the entire image data 13b. The maximum deviation detection unit P1a3 detects the maximum value of the deviation of the target pixel for each small block set in advance for the image data 13b. That is, the maximum deviation is specified for each small block.

  The determination unit P1a4 compares the maximum deviation of each small block with a predetermined threshold value, and specifies a small block whose maximum deviation exceeds the threshold value. And the composition ratio which the small block in which the largest deviation exceeds the threshold value in each large block set beforehand is calculated. Then, the presence / absence of a large block whose composition ratio satisfies the reference value of 40% is determined. If there is at least one large block whose composition ratio satisfies the reference value of 40%, the image data 13b is acceptable. Judge that there is. On the other hand, if there is no large block whose composition ratio satisfies the reference value of 40%, it is determined that the image data 13b is out of focus. By performing such a determination, it is possible to perform the defocus determination without actually looking at the image itself of the image data 13b, and it is possible to designate printing only the image data 13b without the defocus.

  The printer driver P2 acquires the image data 13b and executes a process for printing the image data 13b in L size. Specifically, the size of the image data 13b is converted so that printing can be performed with the L size. In this embodiment, since the printer 20 performs printing at the print resolution in the photo mode, the size conversion of the image data 13b is performed in consideration of the print resolution and the L plate size. In performing size conversion, since it is necessary to increase or decrease the number of pixels with respect to the original image data 13b, interpolation and thinning of pixels are appropriately performed. Next, the image data 13b in which the color of each pixel is expressed by RGB values is color-converted to image data 13b expressed by the color of ink used by the printer 20.

  For example, when the printer 20 is an inkjet printer capable of ejecting CMYK ink, the color of each pixel is converted into image data 13b expressed by CMYK values. Further, halftone processing such as an error diffusion method and a dither method is performed on the color-converted image data 13b, thereby converting the image data 13b into halftone data that specifies whether or not to eject ink for each pixel. Next, the print data that can be output by the printer 20 is generated by rearranging the halftone data in the printing order and attaching a header that specifies the printing paper and the printing resolution. The print data is output to the printer 20 via the USB I / F 14, and the printer 20 performs printing based on the print data.

(2) Flow of image determination processing:
FIG. 3 shows the flow of the image determination process. In step S100, the block setting unit P1a1 acquires image data 13b for image determination from the HDD 13. In step S110, the block setting unit P1a1 acquires the number of vertical and horizontal pixels of the image data 13b described in the header of the image data 13b. In the present embodiment, the following description will be given on the assumption that image data 13b of 2560 pixels wide × 1920 pixels long captured by a digital still camera 30 having about 5 million pixels is designated as a determination target. In this embodiment, in the photo mode for printing, the print resolution in the printer 20 is 2880 dpi horizontal × 2880 dpi vertical. The L version is 127 mm (5.0 inches) wide by 89 mm (3.5 inches) long, and corresponds to the B7 size in the JIS standard.

  In step S120, the block setting unit P1a1 sets a reference distance. The reference distance is set to be 0.3 mm on the L-size printing paper. Since the image data 13b of 2560 pixels wide × 1920 pixels long is printed on the L plate of 127 mm wide × 89 mm long, one pixel of the image data 13b is 0.050 (= 127/2560) mm wide on the printing paper. This corresponds to 0.046 (= 89/1920) mm. Further, 0.3 mm on the printing paper corresponds to 6 (= 0.3 / 0.050) pixels in the horizontal direction of the image data 13b, and 0.3 mm on the printing paper corresponds to the vertical direction of the image data 13b. This corresponds to 6 (≈0.3 / 0.046) pixels. Therefore, in this embodiment, the block setting unit P1a1 sets the horizontal reference distance to 6 pixels and the vertical reference distance to 6 pixels.

  In step S130, the block setting unit P1a1 sets a large block. The large block is set to be 10 mm wide × 10 mm long on the L-size printing paper. Since one pixel of the image data 13b corresponds to 0.050 mm in width and 0.046 mm in length on the printing paper, 10 mm on the printing paper is 200 (≈10 / 0.050) pixels in the horizontal direction of the image data 13b. The vertical 0.3 mm on the printing paper corresponds to 200 (≈10 / 0.046) pixels in the vertical direction of the image data 13b. Therefore, in this embodiment, the block setting unit P1a1 sets the number of horizontal pixels of the large block to 200 pixels and sets the number of vertical pixels to 200 pixels.

  Further, in step S140, the block setting unit P1a1 sets a small block. In this embodiment, the small block is 1/10 the size of the large block. That is. The block setting unit P1a1 sets the number of horizontal pixels of the small block to 20 pixels and sets the number of vertical pixels to 20 pixels. As described above, in the present invention, the vertical and horizontal pixels of the target image data 13b are set because the reference distance between the large block and the small block is set based on the size on the printing paper when the L plate is printed. The large block, small block, and reference distance are set according to the number. In step S150, the deviation acquisition unit P1a2 selects a target pixel from the image data 13b. In the image data 13b, a pixel on a grid point having a 6-pixel cycle of the reference distance is selected as a target pixel.

  FIG. 4 schematically shows the arrangement of each pixel in the image data 13b. In the figure, each pixel is arranged in a matrix, and a pixel that can be selected as a target pixel is shown in black. For example, first, the pixel A1 at the upper left corner is selected as the target pixel. When the target pixel is selected, the deviation acquisition unit P1a2 specifies a comparison pixel to be compared with the target pixel in step S160. Specifically, a pixel located at a position 6 pixels away from the reference pixel in the left direction and the upward direction is specified as a comparison pixel. Accordingly, the pixels that can be selected as the comparison pixels are the same as the pixels that can be selected as the target pixel, and are pixels on lattice points having a period of 6 pixels in the vertical and horizontal directions. When the pixel A1 at the upper left corner is selected as the target pixel, there are no pixels on the left and above the target pixel A1. When there is no comparison pixel as described above, the deviation is assumed to be 0 in step S170. Regarding the target pixel A1, since there is no target pixel in both the left direction and the upward direction, the deviation is assumed to be zero in any direction.

  In step S180, it is determined whether or not the deviation has been calculated for all the target pixels. That is, as shown in FIG. 4, it is determined whether or not all the pixels that can be selected as the target pixel on the grid point of the 6-pixel cycle in the image data 13b are selected in step S150. If not all are selected, the process returns to step S150, and the next pixel of interest is selected. In the present embodiment, it is assumed that the pixel of interest is selected so as to shift sequentially to the right in step S150. Accordingly, the pixel A2 is selected as the next target pixel. In the target pixel A2, although there is no comparison pixel in the upward direction, the pixel A1 is specified as a comparison pixel because the pixel A1 exists at a position 6 pixels away to the left. When the comparison pixel A1 exists in this way, in step S170, the deviation acquisition unit P1a2 acquires the RGB values of the target pixel A2 and the comparison pixel A1, and the luminance of the target pixel A2 and the comparison pixel A1 from the RGB value. Each value Y is calculated. In the calculation of the luminance value Y, the above known formula is used. Further, the deviation acquisition unit P1a2 subtracts the luminance value Y of the target pixel A2 and the comparison pixel A1, and calculates the absolute value as a deviation.

  By repeating steps S150 to S180 as described above, it is possible to acquire the deviation for each target pixel while sequentially shifting the target pixel. When the target pixel is shifted to the right end of the image data 13b, the target pixel at the left end of the next row is selected. For example, after selecting up to the right end of the first row, the target pixel B1 at the left end of the second row is selected. In this way, the target pixel can be selected over the entire image data 13b. Since the comparison pixel exists in both the upward direction and the left direction after the target pixel B2, both the deviation with respect to the comparison pixel in the upward direction and the deviation with respect to the comparison pixel in the left direction are calculated in step S170. It becomes.

  When it is finally confirmed in step S180 that the deviation has been calculated for all the target pixels, in step S190, the maximum deviation detection unit P1a3 detects the maximum deviation in each small block set in step S140. In FIG. 4, a square small block of horizontal 20 pixels × vertical 20 pixels surrounded by a thick line is illustrated. For example, 16 target pixels A1 to A4, B1 to B4 are illustrated in a small block at the upper left corner. Since C1 to C4 and D1 to D4 are included, 2 × 16 deviations in the left direction and the upward direction are calculated in the small block. In step S190, the maximum deviation is detected. Similarly, the maximum deviation is detected for all small blocks.

  When the maximum deviation is detected for each small block, the determination unit P1a4 compares the maximum deviation of each small block with a predetermined threshold in step S200. This threshold value is set so that the luminance deviation between the target pixel and the comparison pixel separated by 0.3 mm when printed in the L size is 4 to 5% of the entire luminance gradation. For example, when the RGB gradation width of the image data 13b is 256 gradations, the deviation of 12 gradations becomes the threshold value. When the deviation in luminance between the target pixel and the comparison pixel exceeds the threshold, there is an abrupt color variation between 0.3 mm when printed in L size, and the contour of the focused subject is the target pixel. It can be considered to exist in the vicinity. By performing step 200, it is possible to generate binary intermediate image data that specifies whether the maximum deviation exceeds or does not exceed the threshold for each small block. A small block whose maximum deviation exceeds a threshold value is hereinafter referred to as an edge block, and a small block whose maximum deviation is below a threshold value is hereinafter referred to as a non-edge block.

  FIG. 5 schematically shows the binary intermediate image data generated in step S200. In the figure, one cell corresponds to each small block, and the small blocks are arranged in a matrix according to the position in the image data 13b. These small blocks are separately colored depending on whether they are edge blocks (black) or non-edge blocks (white). In the same figure, the large block set in step S130 is shown by a bold line. As described above, in this embodiment, the large block is set to a square of horizontal 200 pixels × vertical 200 pixels corresponding to horizontal 10 mm × vertical 10 mm when printed in L size, and each large block has 10 horizontal blocks. X Small blocks of 10 vertical blocks belong. In step S210, the number of edge blocks in each large block is counted and divided by the total number of small blocks (10 × 10 = 100 blocks) belonging to the large block. Thereby, the composition ratio of the edge block in each large block can be calculated.

  When the composition ratio of the edge blocks is calculated for all large blocks, the determination unit P1a4 compares the composition ratio of the edge blocks in each large block with a predetermined reference value in step S210. In this embodiment, the reference value is set as 40%. In step S220, it is determined whether or not the composition ratio of the edge block exceeds the reference value in any one of all large blocks. If the composition ratio of the edge block in any of the large blocks exceeds the reference value, it is determined in step S230 that the determination target image data 13b is not out of focus and is a non-defective product. On the other hand, if the composition ratio of the edge block in any large block among all the large blocks does not exceed the reference value, it is determined in step S230 that the determination target image data 13b is out of focus.

  When a large block corresponding to an area of 10 mm in width and 10 mm in length is printed in L size, and there is a small block with a large color variation at a composition ratio higher than a predetermined reference value, It can be considered that a large outline exists. When taking a picture, it can be said that the possibility of taking a picture so that the size of the subject to be taken is smaller than the size of 10 mm in width and 10 mm in height when converted into the L size is extremely low. Accordingly, when the composition ratio of the edge block is higher than the reference value in any large block, it can be determined that the subject to be photographed is in focus. In many cases, since the subject is larger than the large block, the edge block corresponding to the contour of the subject is distributed so as to span the large block as shown in FIG.

  FIG. 6 shows a large block containing sharp noise with a large color fluctuation. In the case where sharp noise with severe color variation is included, a small block including the noise is determined to be an edge block. However, since the composition ratio of the edge block due to noise does not exceed the reference value in a large block corresponding to an area of 10 mm wide × 10 mm long, it is erroneously determined that the image data 13 b is not out of focus due to sharp noise. Can be prevented. In this way, it is possible to determine whether the image data 13b is out of focus without displaying the image data 13b on the display 60 and the user determining whether the image is good or not, and preventing the binned image data 13b from being printed. it can. Further, since it is possible to determine the defocus by simply calculating a simple deviation, a high-speed determination can be realized.

(3) Modification:
In the above description, the blur determination function of the present invention is illustrated as being incorporated into the image management program P1 executed on the computer 10, but the blur determination function may be incorporated into another program. For example, the blur determination may be performed by the printer driver P2. The printer driver P2 may determine whether the image data 13b is out of focus when the printing conditions and the image data 13b to be printed are specified. If it is determined that the designated image data 13b is out of focus by the above-described method, a warning screen may be displayed on the display 60 or printing may not be executed.

  Further, the printer driver P2 can acquire the paper size to be printed from the designated printing conditions. Accordingly, it is possible to recognize in what size the print-designated image data 13b is printed on the printing paper. That is, it is possible to perform a blur determination according to the print size of the image data 13b. In the above-described embodiment, it is assumed that the print size is the L plate. However, for example, when printing is performed on the entire A4 sheet or when printing is performed on a poster, a blur determination suitable for various print sizes is performed. be able to. In the case of the L size, it is appropriate that the reference distance is 0.3 mm on the printing paper as the minimum distance at which defocusing can be perceived by humans. However, since the spatial frequency characteristic of perception depends on the observation distance, it is desirable to optimize the reference distance according to the observation distance. For example, in the case of A4 paper or a poster, the observation distance is longer than that of the L plate photograph, and minute blurring is less likely to be felt, so that the reference distance can be made larger than 0.3 mm.

  Furthermore, as described above, since the present invention can determine the out-of-focus by simply calculating a simple deviation, it can be easily realized even in a device with poor arithmetic processing capability. For example, the blur determination may be performed with a digital still camera. By doing so, it is possible to prevent image data that has failed to be captured from being stored in a limited storage area of the digital still camera, and thus it is possible to store more image data that has been successfully captured. In addition, the blur determination may be performed by a printer that can print image data from a digital still camera or a memory card without going through a computer. Also in this case, it is possible to prevent the out-of-focus image data from being actually printed, and to reduce waste of consumables such as printing paper and ink. In digital still cameras and printers, it is difficult to provide a display device and a CPU with high computing power sufficient to visually determine defocus. Therefore, it is possible to determine defocus by simple arithmetic processing without looking at the image. It can be said that the significance of applying the present invention is great.

  Of course, the present invention can also be applied to image data in which the color of each pixel is expressed by a color system other than RGB. For example, in the case of the YCbCr color system, the luminance can be used as it is for calculating the deviation. Of course, deviations other than luminance may be calculated. For example, the deviation may be calculated using only the G value in the RGB color system. Since the G channel has the largest contribution ratio to the luminance, it is possible to make a determination close to the case where the luminance difference is calculated and to further reduce the processing load. In the above-described embodiment, the distribution ratio of the edge blocks in the large block is used as the reference for determining the defocus. However, the defocus determination may be performed based on other criteria. For example, the shape of the edge block group may be specified by boundary tracking between the edge block and the non-edge block, and the same shape may be used as a defocus determination criterion. If the shape of the edge block group is small, it can be determined that the noise is sharp, and if the shape of the edge block group is large, it can be determined that the contour of the subject.

(4) Summary:
In the present invention, the deviation of the luminance value between the target pixel and the comparison pixel that are separated by a predetermined reference distance in the image data 13b is acquired. Then, a small block whose maximum deviation exceeds a predetermined threshold is defined as an edge block, and a small block whose deviation does not exceed the threshold is defined as a non-edge block. A plurality of small blocks belong to the large block, and the composition ratio of the edge blocks in each large block is calculated. When the component ratio exceeds a predetermined reference value, it is determined that the image is not out of focus, and when the component ratio does not exceed the reference value, it is determined that the image is out of focus. That is, when an edge block corresponding to an edge having a large color variation is distributed on a large scale in any small block, it is determined that the image is not out of focus.

It is a hardware block diagram of a computer. It is a software block diagram of a computer. It is a flowchart which shows the flow of an image determination process. It is a schematic diagram of image data. It is a schematic diagram of the large block in which an outline is included. It is a schematic diagram of a large block including noise.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 ... Computer (image determination apparatus), 10a ... Bus, 11 ... CPU, 12 ... RAM, 13 ... HDD, 13a ... Program data, 13b ... Image data, 14 ... USB I / F, 15 ... Input apparatus I / F, 16 ... Video I / F, 20 ... Printer, 30 ... Digital still camera, 40 ... Mouse, 50 ... Keyboard, 60 ... Display, P1 ... Image management program, P1a1 ... Block setting part, P1a2 ... Deviation acquisition part, P1a3 ... Maximum deviation Detection unit, P1a4 ... determination unit, P1b ... image management unit, P2 ... printer driver

Claims (8)

In the image determination apparatus for determining the quality of the image data composed of a plurality of pixels having color signals,
Block setting means for setting a plurality of blocks in the image data;
Deviation obtaining means for obtaining a deviation of the color signals between the pixels separated by a predetermined reference distance in the image data;
Maximum deviation detecting means for detecting the maximum value of the deviation for each block;
An image determination apparatus comprising: determination means for determining the quality of the image data according to the distribution of the blocks in which the maximum value of the deviation exceeds a predetermined threshold value. The determination means is
A plurality of large blocks larger than the block are set in the image data, and the composition ratio of the block in which the maximum value of the deviation exceeds a predetermined threshold among the blocks belonging to the large block in any of the large blocks The image determination apparatus according to claim 1, wherein the image data is determined to be non-defective when the image data exceeds a predetermined reference value.   3. The image determination according to claim 1, wherein the reference distance is set to be about 0.3 mm when the image data is printed in L size. apparatus.   4. The image according to claim 1, wherein the size of the large block is set to be about 10 mm when the image data is printed in the L size. Judgment device.   The image determination apparatus according to claim 1, wherein the deviation acquisition unit acquires a luminance deviation calculated from the color signal as a deviation of the color signal. In the image data, each pixel is arranged in a matrix,
The image determination apparatus according to claim 1, wherein the deviation acquisition unit acquires the deviation of the color signal in each of a vertical direction and a horizontal direction of the image data. In the image determination method for determining the quality of image data composed of a plurality of pixels having color signals,
A block setting step for setting a plurality of blocks in the image data;
A deviation acquisition step of acquiring a deviation of the color signals between the pixels separated by a predetermined reference distance in the image data;
A maximum deviation detecting step for detecting the maximum value of the deviation for each block;
A determination step of determining whether the image data is good or bad according to the distribution of the blocks in which the maximum value of the deviation exceeds a predetermined threshold value. In an image determination program for causing a computer to execute a function of determining whether or not image data composed of a plurality of pixels having color signals is acceptable.
A block setting function for setting a plurality of blocks in the image data;
A deviation acquisition function for acquiring a deviation of the color signal between the pixels separated by a predetermined reference distance in the image data;
A maximum deviation detection function for detecting the maximum value of the deviation for each block;
An image determination program that causes a computer to execute a determination function that determines the quality of the image data according to the distribution of the blocks in which the maximum value of the deviation exceeds a predetermined threshold.

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