JP2006293898A - Image processing method, image processing apparatus, and image processing program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To divide photographic image data into groups on the basis of information relevant to a light distribution condition at the time of photographing to stabilize correction processing of the whole of a series of photographic image data in the groups. <P>SOLUTION: Image data of one order is acquired (step S1), and light distribution condition determination processing of each image data is performed (step S2). Then image data is divided into groups on the basis of light distribution conditions and a photographing sequence (step S3). Next, face extraction processing of each image data included in M groups is performed (step S5), and an average density (group average face density) of extracted face areas is calculated (step S6). If an N-th image data in M groups has a face area (step S8; YES), density correction processing of correcting an average density of the face area in the image data to a target density value is performed (step S10). If the N-th image data in M groups does not have a face area (step S8; NO), density correction processing of correcting the group average face density to the target density value is performed (step S12). <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing method, an image processing apparatus, and an image processing program for performing image processing on image data.

  In recent years, digital still cameras (including general-purpose applications for general users, high-performance professional applications, toys, built-in devices such as mobile phones and laptop computers, hereinafter abbreviated as DSC) have become widespread. Images taken by DSC, like color photographic film, are output as hard copy images or displayed on output media such as CRT (Cathode Ray Tube) for viewing. In addition, a technique is widely used in which an image formed on a color photographic film is photoelectrically read by a CCD (Charge Coupled Device) sensor or the like and converted into an image signal.

  Such an image signal is subjected to various image processing represented by negative / positive reversal, luminance adjustment, color balance adjustment, grain removal, and sharpness enhancement, and then CD-R (CD-Recordable), CD-RW ( CD-ReWritable), floppy (registered trademark) disk, memory card and other recording media, distributed over the Internet, output as hard copy on silver halide photographic paper, inkjet printer, thermal printer, etc., CRT It can be viewed on an output medium such as a liquid crystal display or a plasma display.

  By the way, in any output form, the viewer's attention is high and the evaluation standard is strict in a scene in which a person is photographed as a subject, and in particular, the face is focused. However, in actual image shooting, it is often the case that the face of a person is not photographed as an image having an appropriate color, brightness, sharpness, noise, and stereoscopic effect. In order to obtain a high-quality image for a scene including a person in response to such a background, a technique for extracting a face area from captured image data and performing a correction process is required. Many techniques and techniques for improving the determination accuracy of face determination processing are disclosed.

  Further, when a general user prints a photographed image by himself or a contractor, he / she usually requests a series of images photographed at a trip or an event at the same time. In such a case, the image quality of the face area in each image as described above is of course, but when viewing a series of multiple images, the finish such as density and color reproduction is consistent in similar shooting scenes. It is required to have sex.

For example, when processing images of a plurality of related frames, a specific area (whole person, face, clothes, etc.) is specified in the first frame image, and the image of the specific area is corrected. When image features are stored and image processing of subsequent frames is performed, a similar region having an image feature amount similar to that of the pre-processed image of the specific region of the first frame is extracted, and There has been disclosed a technique for suppressing variation in processing between frames by performing image correction similar to that for a specific area of one frame (see Patent Document 1).
JP-A-11-275351

  However, the above prior art focuses on the main subject, particularly a person, and ensures the stability of the finish of the person. However, since the image area other than the main subject is not considered, the same person is photographed. However, when shooting in different environments, there is a problem in that stability between shooting scenes cannot be obtained and variations occur. In addition, it is difficult to ensure the finish stability for a scene in which a person is not photographed.

  In particular, an image shot by a general user includes many scenes where shooting conditions such as exposure conditions are not good. In such a case, there is a risk that the extraction accuracy of the person region performed according to a predetermined extraction algorithm may be reduced. In addition, even for similar photographed images, there is a possibility that a large difference may occur in the processing results when the person extraction succeeds and when the person extraction fails.

  The present invention has been made in view of the above-described problems in the related art, and an object of the present invention is to achieve stability of correction processing for a whole series of images.

  In order to solve the above-mentioned problem, the invention according to claim 1 is an image processing method for generating a corrected image by performing correction processing on a plurality of captured image data, and based on information on light distribution conditions at the time of shooting. Grouping the plurality of photographed image data, and for a group including two or more photographed image data, based on the reference correction processing condition in the group and / or information on the main subject region of the photographed image data to be corrected, A correction processing condition for the photographic image data to be corrected is determined.

  The invention according to claim 2 is an image processing method for performing correction processing on a plurality of photographed image data and generating a corrected image, based on the information on the light distribution condition at the time of photographing and the information on the main subject region. For the group including two or more pieces of photographed image data, the correction is performed based on the reference correction processing condition in the group and / or information on the main subject region of the photographed image data to be corrected. It is characterized in that a correction processing condition for the target captured image data is determined.

  According to a third aspect of the present invention, in the image processing method according to the first or second aspect, when the plurality of photographed image data are grouped, the photographed image data in which the photographing order is continued is further grouped. It is characterized by.

  According to a fourth aspect of the present invention, in the image processing method according to any one of the first to third aspects, the main subject area is a human face area.

  According to a fifth aspect of the present invention, in the image processing method according to any one of the first to fourth aspects, information relating to a main subject area referred to when determining the correction processing condition is information on the main subject area. It is characterized by the presence or absence.

  According to a sixth aspect of the present invention, in the image processing method according to any one of the first to fifth aspects, the light distribution condition at the time of photographing includes at least one of a backlight state, a flash light utilization state, and an under state. One or more are included.

  According to a seventh aspect of the present invention, in the image processing apparatus that performs correction processing on a plurality of photographed image data and generates a corrected image, the plurality of photographed image data are grouped based on information on light distribution conditions at the time of photographing. Grouping means to be grouped and a group including two or more photographed image data, the correction target based on the reference correction processing condition in the group and / or information on the main subject region of the photographed image data to be corrected Correction processing condition determining means for determining the correction processing condition of the captured image data.

  According to an eighth aspect of the present invention, in the image processing apparatus that performs correction processing on a plurality of captured image data and generates a corrected image, the plurality of the plurality of captured image data is based on information on a light distribution condition at the time of shooting and information on a main subject region. Grouping means for grouping the photographic image data and a group including two or more photographic image data, the reference correction processing condition in the group and / or information on the main subject area of the photographic image data to be corrected. And correction processing condition determining means for determining a correction processing condition for the photographic image data to be corrected.

  According to a ninth aspect of the present invention, in the image processing device according to the seventh or eighth aspect, the grouping unit further groups the captured image data in which the capturing order is continuous into the same group. .

  According to a tenth aspect of the present invention, in the image processing device according to any one of the seventh to ninth aspects, the main subject area is a human face area.

  According to an eleventh aspect of the present invention, in the image processing apparatus according to any one of the seventh to tenth aspects, information on the main subject area referred to when the correction processing condition is determined includes the main subject area. It is characterized by the presence or absence.

  According to a twelfth aspect of the present invention, in the image processing apparatus according to any one of the seventh to eleventh aspects, the light distribution condition at the time of photographing includes at least one of a backlight state, a flash light utilization state, and an under state. One or more are included.

  According to a thirteenth aspect of the present invention, in an image processing program for causing a computer to perform a correction process on a plurality of photographed image data and to generate a corrected image, the computer relates to a light distribution condition at the time of photographing. The grouping function for grouping the plurality of photographed image data based on the information, and the group including two or more photographed image data, the reference correction processing condition in the group and / or the photographed image data to be corrected And a correction processing condition determination function for determining a correction processing condition of the photographic image data to be corrected based on information on the main subject area.

  According to a fourteenth aspect of the present invention, in an image processing program for causing a computer to perform a correction process on a plurality of captured image data and to generate a corrected image, the computer relates to a light distribution condition at the time of shooting. A grouping function for grouping the plurality of captured image data and a group including two or more captured image data based on the information and information on the main subject area, and a reference correction processing condition and / or correction in the group And a correction processing condition determination function for determining a correction processing condition of the photographic image data to be corrected based on information on a main subject area of the photographic image data to be corrected.

  According to a fifteenth aspect of the present invention, in the image processing program according to the thirteenth or fourteenth aspect, when the grouping function is realized, the photographic image data in which the photographing order is continuous is further made the same group. It is characterized by.

  According to a sixteenth aspect of the present invention, in the image processing program according to any one of the thirteenth to fifteenth aspects, the main subject area is a human face area.

  According to a seventeenth aspect of the present invention, in the image processing program according to any one of the thirteenth to sixteenth aspects, the information on the main subject region referred to when determining the correction processing condition is the main subject region information. It is characterized by the presence or absence.

  According to an eighteenth aspect of the present invention, in the image processing program according to any one of the thirteenth to seventeenth aspects, the light distribution condition at the time of photographing includes at least one of a backlight state, a flash light utilization state, and an under state. One or more are included.

  According to the first, seventh, and thirteenth aspects of the present invention, the photographic image data is grouped based on the information regarding the light distribution condition at the time of photographing, and the stability of the correction process for the entire series of photographic image data in the group is improved. be able to.

  According to the invention described in claims 2, 8, and 14, the photographed image data is grouped based on the information on the light distribution condition at the time of photographing and the information on the main subject region, and correction of the entire series of photographed image data in the group is performed. Processing stability can be achieved.

  According to the third, ninth, and fifteenth aspects of the present invention, the captured image data in which the imaging order is continuous are grouped, so that the effect of selecting similar images is enhanced.

  According to the fourth, tenth, and sixteenth aspects of the present invention, it is possible to determine the correction processing condition of the photographic image data to be corrected based on the information related to the face area of the person whose viewer's attention is high.

  According to the fifth, eleventh and seventeenth aspects of the present invention, it is possible to determine the correction processing conditions for the photographic image data to be corrected based on the presence or absence of the main subject region.

  According to the sixth, twelfth, and eighteenth aspects, a plurality of captured image data can be grouped based on information relating to light distribution conditions such as a backlight state, a flash light utilization state, an under state, and the like.

[First Embodiment]
Hereinafter, a first embodiment of the present invention will be described in detail with reference to the drawings. However, the scope of the invention is not limited to the illustrated examples.

<Appearance Configuration of Image Processing Apparatus 1>
First, the image processing apparatus 1 according to the embodiment of the present invention will be described.
FIG. 1 is a perspective view showing a general configuration of the image processing apparatus 1.

  As shown in FIG. 1, the image processing apparatus 1 is provided with a magazine loading unit 3 for loading a photosensitive material on one side of a main body 2. Inside the main body 2, there are provided an exposure processing unit 4 for exposing the photosensitive material and a print creating unit 5 for developing and drying the exposed photosensitive material to create a print. The created print is discharged to a tray 6 provided on the other side of the main body 2.

  In addition, a CRT (Cathode Ray Tube) 8 serving as a display device, a film scanner unit 9 serving as a device for reading a transparent original, a reflective original input device 10, and an operation unit 11 are provided on the upper portion of the main body 2. Furthermore, the main body 2 includes an image reading unit 14 that can read image information recorded on various digital recording media, and an image writing unit 15 that can write (output) image signals to various digital recording media. . In addition, a control unit 7 that centrally controls these units is provided inside the main body 2.

  The image reading unit 14 includes a PC card adapter 14a and a floppy (registered trademark) disk adapter 14b, and a PC card 13a and a floppy (registered trademark) disk 13b can be inserted therein. The PC card 13a has a memory in which a plurality of image data captured by a digital camera is recorded. For example, a plurality of image data captured by a digital camera is recorded on the floppy disk 13b. In addition, examples of the recording medium having image data include a multimedia card, a memory stick, and a CD-ROM (Compact Disc Read Only Memory).

  The image writing unit 15 includes a floppy disk adapter 15a, an MO adapter 15b, and an optical disk adapter 15c. The FD 16a, the MO 16b, and the optical disk 16c can be inserted into the image writing unit 15, respectively. You can write. Examples of the optical disk 16c include a CD-R (Compact Disc-Recordable), a DVD-R (Digital Versatile Disk-Recordable), and the like.

  In FIG. 1, the operation unit 11, the CRT 8, the film scanner unit 9, the reflection original input device 10, and the image reading unit 14 are integrally provided in the main body 2, but any one of these is provided. Two or more may be provided separately.

  In the image processing apparatus 1 shown in FIG. 1, an example is illustrated in which a photosensitive material is exposed and developed to create a print, but the print creation method is not limited to this, and for example, an inkjet method, an electronic A method such as a photographic method, a thermal method, or a sublimation method may be used.

<Internal Configuration of Image Processing Apparatus 1>
FIG. 2 is a block diagram showing the internal configuration of the image processing apparatus 1. As shown in FIG. 2, the image processing apparatus 1 includes a control unit 7, an exposure processing unit 4, a print creation unit 5, a CRT 8, a film scanner unit 9, a reflective original input device 10, an operation unit 11, an image reading unit 14, and an image. The writing unit 15 includes a communication unit (input) 32, a communication unit (output) 33, and a data storage unit 71.

  The control unit 7 includes a microcomputer, and various control programs such as an image processing program stored in a storage unit (not shown) such as a ROM (Read Only Memory), and a CPU (Central Processing Unit) (not shown). The operation of each part constituting the image processing apparatus 1 is comprehensively controlled in cooperation with the above.

  The control unit 7 includes an image processing unit 70, and reads image data acquired by the film scanner unit 9 or the reflection original input device 10 from the image reading unit 14 based on an input signal (command information) from the operation unit 11. The processed image data and image data input from an external device via the communication means (input) 32 are subjected to image processing to generate output image data, which are output to the exposure processing unit 4. Further, the image processing unit 70 performs a conversion process corresponding to the output form on the image processed image data, and outputs the converted image data. Output destinations of the image processing unit 70 include the CRT 8, the image writing unit 15, the communication means (output) 33, and the like.

  The exposure processing unit 4 exposes an image to the photosensitive material and outputs the photosensitive material to the print creating unit 5. The print creating unit 5 develops and exposes the exposed photosensitive material to create prints P1, P2, and P3. The print P1 is a service size, high-definition size, panoramic size print, the print P2 is an A4 size print, and the print P3 is a business card size print.

  The film scanner unit 9 reads an image recorded on a transparent original such as a developed negative film N or a reversal film taken by an analog camera.

  The reflection original input device 10 reads an image formed on a print P (photo print, document, various printed materials) by a flat bed scanner (not shown).

  The operation unit 11 includes information input means 12. The information input unit 12 is configured by a touch panel, for example, and outputs a pressing signal of the information input unit 12 to the control unit 7 as an input signal. Note that the operation unit 11 may be configured to include a keyboard, a mouse, and the like. The CRT 8 displays image data and the like according to the display control signal input from the control unit 7.

  The image reading unit 14 includes, as the image transfer means 30, a PC card adapter 14a, a floppy disk adapter 14b, and the like, and is inserted into the PC card 13a inserted into the PC card adapter 14a or the floppy disk adapter 14b. The image data recorded on the floppy disk 13b is read out and transferred to the control unit 7. For example, a PC card reader or a PC card slot is used as the PC card adapter 14a.

  The image writing unit 15 includes a floppy disk adapter 15a, an MO adapter 15b, and an optical disk adapter 15c as the image transport unit 31. The image writing unit 15 is inserted into the floppy disk 16a inserted into the floppy disk adapter 15a, the MO 16b inserted into the MO adapter 15b, and the optical disk adapter 15c in accordance with the write signal input from the control unit 7. The generated image data is written on the optical disc 16c.

  The communication means (input) 32 receives image data representing a captured image and a print command signal from another computer in the facility where the image processing apparatus 1 is installed, or a remote computer via the Internet or the like.

  The communication means (output) 33 includes image data representing a photographed image after image processing and order information (information on how many prints are to be created from images of which frames, print size information, etc.) 1 is transmitted to other computers in the facility where 1 is installed or to a distant computer via the Internet or the like.

  The data storage unit 71 stores the image data and order information corresponding to the image data, and sequentially stores them.

<Configuration of Image Processing Unit 70>
FIG. 3 is a block diagram illustrating a functional configuration of the image processing unit 70 of the image processing apparatus 1. As shown in FIG. 3, the image processing unit 70 includes a film scan data processing unit 701, a reflection original scan data processing unit 702, an image data format decoding processing unit 703, an image adjustment processing unit 704, a CRT specific processing unit 705, a printer specific A processing unit (1) 706, a printer specific processing unit (2) 707, and an image data format creation processing unit 708 are configured.

  A film scan data processing unit 701 performs proofing operations specific to the film scanner unit 9 on the image data input from the film scanner unit 9, negative reversal in the case of a negative document, dust flaw removal, gray balance adjustment, contrast adjustment, granular noise Removal, sharpening, and the like are performed, and the result is output to the image adjustment processing unit 704. The film scan data processing unit 701 also includes information on film size, negative / positive type, ISO (International Organization for Standardization) sensitivity recorded on the film optically or magnetically, manufacturer name, information on main subject, and shooting conditions ( For example, the description information content of APS (Advanced Photo System) is also output to the image adjustment processing unit 704.

  The reflection document scan data processing unit 702 performs a calibration operation unique to the reflection document input device 10, negative / positive reversal in the case of a negative document, dust flaw removal, gray balance adjustment, and contrast adjustment for the image data input from the reflection document input device 10. , Noise removal, sharpening enhancement, and the like, and output to the image adjustment processing unit 704.

  The image data format decoding processing unit 703 performs compression code restoration, color data expression method conversion, and the like as necessary according to the data format of the image data input from the image transfer means 30 or the communication means (input) 32. Then, the data is converted into a data format suitable for calculation in the image processing unit 70 and output to the image adjustment processing unit 704.

  The image adjustment processing unit 704 performs various processes on the images received from the film scanner unit 9, the reflective original input device 10, the image transfer unit 30, and the communication unit (input) 32 based on the command from the operation unit 11 or the control unit 7. Performs image processing, and outputs processed image signals to the CRT specific processing unit 705, printer specific processing unit (1) 706, printer specific processing unit (2) 707, image data format creation processing unit 708, and data storage means 71. .

  The CRT specific processing unit 705 performs processing such as changing the number of pixels and color matching on the image data input from the image adjustment processing unit 704 as necessary, and combines the information with information that needs to be displayed, such as control information. Image data is output to the CRT 8.

  A printer-specific processing unit (1) 706 performs printer-specific calibration processing, color matching, pixel number change, and the like on the image data input from the image adjustment processing unit 704 as necessary. Output.

  When an external printer 34 such as a large-format ink jet printer is connected to the image processing apparatus 1, a printer specific processing unit (2) 707 is provided for each connected printer. The printer-specific processing unit (2) 707 performs appropriate printer-specific calibration processing, color matching, pixel number change, and the like on the image data input from the image adjustment processing unit 704.

  The image data format creation processing unit 708 applies JPEG (Joint Photographic Experts Group), TIFF (Tagged Image File Format), and Exif (Exchangeable Image File Format) to the image data input from the image adjustment processing unit 704 as necessary. ) And the like, and the image is converted to various general-purpose image formats and output to the image transport unit 31 and the communication means (output) 33.

  A film scan data processing unit 701, a reflection original scan data processing unit 702, an image data format decoding processing unit 703, an image adjustment processing unit 704, a CRT specific processing unit 705, a printer specific processing unit (1) 706, a printer specific processing unit. (2) The category 707 and the image data format creation processing unit 708 are provided to help understanding of the function of the image processing unit 70, and need not be realized as a physically independent device. Alternatively, it may be realized as a type of software processing in a single CPU. The image processing apparatus 1 according to the present embodiment is not limited to the above-described contents, and can be applied to various forms such as a digital photo printer, a printer driver, and various image processing software plug-ins. .

Next, the operation of the image processing apparatus 1 will be described.
First, with reference to FIG. 4, the correction process performed in the image adjustment process part 704 is demonstrated.

  First, one-order captured image data (hereinafter simply referred to as image data) input from the image transfer means 30 or the communication means (input) 32 is acquired (step S1). One order of image data includes a plurality of pieces of image data ordered at one time.

  Here, additional information (tag information or the like) added to the image data is acquired together with the image data. Such additional information may be added as a unique information format or an independent information file or data, but existing tag information defined in general-purpose image formats represented by JPEG, TIFF, Exif, etc. It is preferable to use an area that can be freely used, such as a maker note or a user note.

  Tag information includes, for example, exposure time, F value, shutter speed, zoom ratio, shooting light source, strobe usage (presence / absence, forced flash, forced non-flash, etc.), white balance, shooting date / time, shooting location, resolution, subject position / The size, subject distance range (distant view, near view, etc.), shooting mode (portrait, night view, landscape, etc.), manufacturer name / model name, etc. of the image input device are described.

  Next, a light distribution condition determination process for each image data is performed (step S2). Shooting scenes such as forward light, backlight, strobe (flash light use state), under, etc. are determined as light distribution conditions. Moreover, it is good also as including the over state as a light distribution condition discriminated.

Here, the light distribution condition determination processing will be described with reference to FIG.
First, image data is divided into predetermined image areas, and an occupancy ratio calculation process is performed to calculate an occupancy ratio (first occupancy ratio, second occupancy ratio) indicating the ratio of each divided area to the entire image data. (Step S21). Details of the occupation rate calculation process will be described later with reference to FIGS.

  Next, the occupancy ratio (first occupancy ratio, second occupancy ratio) calculated in step S21, at least the average luminance value of the skin color in the center of the screen of the image data, and the shooting conditions are set in advance. Based on the coefficients, indexes (indexes 1 to 6) for specifying light distribution conditions (quantitatively representing light source conditions and exposure conditions) are calculated (step S22). The calculation method of each index in step S22 will be described in detail later.

  Next, the light distribution condition of the image data is determined based on the index calculated in step S22 (step S23), and the main light distribution condition determination process ends. A method for determining the light distribution condition will be described in detail later.

  Next, the first occupancy rate calculation process executed in step S21 of FIG. 5 will be described in detail with reference to FIG.

  First, RGB (Red, Green, Blue) values of image data are converted into the HSV color system (step S31). Next, the image data is divided into regions composed of combinations of predetermined brightness and hue, and a two-dimensional histogram is created by calculating the cumulative number of pixels for each divided region (step S32).

  Lightness (V) is 0-25 (v1), 26-50 (v2), 51-84 (v3), 85-169 (v4), 170-199 (v5), 200-224 (v6) , 225 to 255 (v7). Hue (H) is a skin hue hue area (H1 and H2) with a hue value of 0 to 39, 330 to 359, a green hue area (H3) with a hue value of 40 to 160, and a blue hue area with a hue value of 161 to 250 It is divided into four areas (H4) and a red hue area (H5). Note that the red hue region (H5) is not used in the following calculation because it is found that the contribution to the discrimination of the shooting scene is small. The flesh color hue area is further divided into a flesh color area (H1) and other areas (H2). Hereinafter, among the flesh-colored hue areas (H = 0 to 39, 330 to 359), the hue '(H) that satisfies the following formula (2) is defined as the flesh-colored area (H1), and the area that does not satisfy the formula (2) is ( H2). However, the values of the input image data are InR, InG, and InB.

10 <Saturation (S) <175,
Hue '(H) = Hue (H) + 60 (when 0 ≤ Hue (H) <300),
Hue '(H) = Hue (H)-300 (when 300 ≤ Hue (H) <360),
Luminance (Y) = InR x 0.30 + InG x 0.59 + InB x 0.11 (1)
As
Hue '(H) / Luminance (Y) <3.0 × (Saturation (S) / 255) + 0.7 (2)

  Therefore, the number of divided areas of the image data is 4 × 7 = 28. In addition, it is also possible to use the brightness (V) in the expressions (1) and (2).

  When the two-dimensional histogram is created, a first occupancy ratio indicating the ratio of the cumulative number of pixels calculated for each divided region to the total number of pixels (the entire captured image) is calculated (step S33). Let Rij be the first occupancy calculated in the divided area composed of the combination of the lightness area vi and the hue area Hj.

Next, a method for calculating the index 1 and the index 2 will be described.
Table 1 shows, for each divided area, the first coefficient necessary for calculating the index 1 that quantitatively indicates the accuracy of strobe shooting, that is, the brightness state of the face area at the time of strobe shooting. The coefficient of each divided area shown in Table 1 is a weighting coefficient by which the first occupation ratio Rij of each divided area is multiplied, and is set in advance according to the shooting conditions.

When the first coefficient in the lightness region vi and the hue region Hj is Cij, the index 1 is defined as in Expression (3).

Table 2 shows, for each divided region, the second coefficient necessary for calculating the index 2 that quantitatively indicates the accuracy as backlight photographing, that is, the brightness state of the face region at the time of backlight photographing. The coefficient of each divided area shown in Table 2 is a weighting coefficient by which the first occupancy rate Rij of each divided area is multiplied, and is set in advance according to the shooting conditions.

When the second coefficient in the lightness area vi and the hue area Hj is Dij, the index 2 is defined as in Expression (4).

  Next, the second occupancy rate calculation process executed to calculate the index 3 will be described in detail with reference to FIG.

  First, the RGB values of the image data are converted into the HSV color system (step S41). Next, the image data is divided into regions each composed of a combination of the distance from the outer edge of the captured image screen and the brightness, and a two-dimensional histogram is created by calculating the cumulative number of pixels for each divided region (step S42).

  8A to 8D show four areas n1 to n4 divided according to the distance from the outer edge of the screen of the image data. A region n1 shown in FIG. 8A is an outer frame, a region n2 shown in FIG. 8B is a region inside the outer frame, and a region n3 shown in FIG. An inner area, an area n4 shown in FIG. 8D, is an area at the center of the captured image screen. Further, the lightness is divided into seven regions v1 to v7 as described above. Therefore, when the image data is divided into regions each having a combination of the distance from the outer edge of the captured image screen and the brightness, the number of divided regions is 4 × 7 = 28.

  When the two-dimensional histogram is created, a second occupancy ratio indicating the ratio of the cumulative number of pixels calculated for each divided region to the total number of pixels (the entire captured image) is calculated (step S43). The second occupancy calculated in the divided area composed of the combination of the brightness area vi and the screen area nj is defined as Qij.

Next, a method for calculating the index 3 will be described.
Table 3 shows the third coefficient necessary for calculating the index 3 for each divided region. The coefficient of each divided area shown in Table 3 is a weighting coefficient by which the second occupancy rate Qij of each divided area is multiplied, and is set in advance according to the shooting conditions.

If the third coefficient in the lightness area vi and the screen area nj is Eij, the index 3 is defined as shown in Expression (5).

Next, a method for calculating the index 4 will be described.
First, the luminance Y is calculated from the RGB (Red, Green, Blue) values of the image data using Equation (1). Also, the average luminance value x1 of the skin color area in the center of the screen of the image data is calculated. Here, the center of the screen is, for example, an area configured by an area n3 and an area n4 in FIG. Next, a difference value x2 between the maximum luminance value and the average luminance value of the image data is calculated.

Next, the standard deviation x3 of the luminance of the image data is calculated, and the average luminance value x4 at the center of the screen is calculated. Also, a comparison value x5 between the difference value between the maximum luminance value Yskin_max and the minimum luminance value Yskin_min of the skin color area in the image data and the average luminance value Yskin_ave of the skin color area is calculated. This comparison value x5 is expressed as the following equation (6).
x5 = (Yskin_max−Yskin_min) / 2−Yskin_ave (6)

Next, the index 4 is calculated by multiplying each of the calculated values x1 to x5 by a fourth coefficient set in advance according to the photographing condition and taking the sum. The index 4 is defined as the following formula (7).
Index 4 = 0.06 × x1 + 1.13 × x2 + 0.02 × x3 + (− 0.01) × x4 + 0.03 × x5−6.50 (7)

  Further, the average luminance value of the skin color area in the center of the screen of the image data is set as an index 4 '. Here, the center of the screen is, for example, an area composed of the area n2, the area n3, and the area n4 in FIG.

In addition, the index 5 is defined as in Expression (8) using the index 1, index 3, and index 4 ′, and the index 6 is defined as in Expression (9) using the index 2, index 3, and index 4 ′. Defined in
Index 5 = 0.46 × Index 1 + 0.61 × Index 3 + 0.01 × Index 4′−0.79 (8)
Indicator 6 = 0.58 x Indicator 2 + 0.18 x Indicator 3 + (-0.03) x Indicator 4 '+ 3.34 (9)
Here, the weighting coefficient by which each index is multiplied in Expression (8) and Expression (9) is set in advance according to the shooting conditions.

Next, a method for determining the light distribution condition in step S23 in FIG. 5 will be described.
In FIG. 9A, 60 images are taken under each light source condition of normal light, backlight, and strobe, and index 5 and index 6 are calculated for a total of 180 digital image data. The values of index 6 are plotted. According to FIG. 9A, when the value of the index 5 is larger than 0.5, there are many flash shooting scenes, the value of the index 5 is 0.5 or less, and the value of the index 6 is larger than −0.5. When there are many backlight scenes, the value of the index 5 is 0.5 or less, and the value of the index 6 is −0.5 or less, it is understood that there are many backlight scenes. In this way, the shooting scene can be determined quantitatively based on the values of the index 5 and the index 6.

  FIG. 9B is a graph in which index 4 and index 5 of an image with index 5 larger than 0.5 are calculated and plotted among 60 captured images of the strobe shooting scene and the under shooting scene. According to FIG. 9B, it can be seen that when the value of the index 4 is greater than 0, there are many flash shooting scenes, and when the value of the index 4 is 0 or less, there are many under shooting scenes.

Note that the information regarding the light distribution conditions at the time of shooting is not limited to the shooting scene, and may be further subdivided according to the degree (intensity) (for example, strong backlight / weak backlight, proximity strobe / non-proximity strobe, etc.).
Moreover, it is good also as determining light distribution conditions from the shape using a brightness | luminance histogram.

  Tag information including Exif (exposure time, F value, shutter speed, zoom ratio, photographing light source, use of strobe (existence, forced flash, forced non-flash, etc.), white balance, subject position / size, subject distance range Information on light distribution conditions at the time of shooting may be acquired or inferred from (far view, near view, etc.) and shooting mode (portrait, night view, landscape, etc.).

  Returning to FIG. 4, after the light distribution condition determination process is performed (step S <b> 2), the image data is grouped based on the light distribution condition and the photographing order (step S <b> 3).

  FIG. 10 shows an example when there is an order for five sheets. By the light distribution condition determination process, the images of the first frame to the fourth frame are determined to be backlight, and the image of the fifth frame is determined to be forward light. In addition, since the images in the first frame to the fourth frame are sequentially photographed, the images in the first frame to the fourth frame are grouped into the same group.

  As for the shooting order, for example, an image file name (in an imaging device such as a digital camera, a file name is often assigned as a serial number. The name given by the user also includes a date, OO-1, OO -2, etc., a number is often assigned to a related image), a folder name, and tag information such as Exif (shooting date / time and shooting location).

  Next, it is determined whether or not the image data included in the M group among the plurality of groups is 2 or more (step S4).

  When the image data included in the M group is 2 or more (step S4; YES), face extraction processing of each image data is performed (step S5).

  In the face extraction process, first, various characteristic values are calculated from image data, and a human face candidate area (skin color area) is extracted. For example, additional information such as a mean value of pixel signal values, a statistical value such as dispersion, a lens focal length, a focus position, and light source information at the time of photographing is acquired as a characteristic value.

  When a human face candidate area is extracted, a hierarchical neural network (hereinafter simply referred to as a neural network) that has learned human face determination processing using a signal indicating the face candidate area as an input signal is used. Processing for detecting a face area from the extracted face candidate areas is performed. For face detection, for example, [area area / peripheral length] representing the form of the skin color area, [shortest diameter / longest diameter], and various characteristic values such as pixel signal value variance are extracted for each face candidate. Calculated for the region. Then, the reaction intensity of the neural network is calculated, and when the reaction intensity is greater than a predetermined value, it is determined that the face is “face”.

  Note that the face determination processing is not limited to a method using a neural network, but is a template matching or a learning method by self-organization of Kohonen described in Japanese Patent Laid-Open Nos. 5-282457 and 6-214970. It is determined whether the feature pattern extracted from the face candidate area is included in the feature pattern of eyes and mouth learned using, and whether or not it is a face by determining the positional relationship of the feature part May be determined.

  Next, the average density (group average face density) of the face area extracted from each image data included in the M group is calculated (step S6). Here, the correction processing condition based on the group average face density is set as the reference correction processing condition.

  Next, the process proceeds to correction processing of each image. First, the Nth image data of the M group is acquired (step S7), and it is determined whether or not there is a face area as a main subject in the image (step S8).

  When there is a face area in the Nth image data of the M group (step S8; YES), the average density of the face area of the image data is acquired (step S9), and the average density of the face area is determined in advance. A gradation conversion curve (correction curve) that creates a target density value is created, and density correction processing is performed based on the gradation conversion curve (step S10).

  When there is no face area in the Nth image data of the M group (step S8; NO), the group average face density calculated in step S6 is acquired (step S11), and the group average face density is determined in advance. A gradation conversion curve that creates a target density value is created, and density correction processing is performed based on the gradation conversion curve (step S12).

  After step S10 or step S12, gradation compression processing is performed if necessary when the distribution of density values is wide (step S13). For example, in the case of backlighting, the main subject, including the face, is often dark and the background etc. is bright, so when correcting with a gradation conversion curve, The gradation compression processing that is generally used is performed.

  Next, when there is the next image data in the M group (step S14; YES), the process returns to step S7, and the processes of steps S7 to S13 are repeated.

  In step S4, when there is one image data included in the M group (step S4; NO), correction processing suitable for the image data is performed (step S15).

  When all the processing of the image data in the M group is completed (step S14; NO), or after step S15 is completed, it is determined whether there is a next image group (step S16). If there is a next image group (step S16; YES), the process returns to step S4, and the processes of steps S4 to S15 are repeated.

  When the processing is completed for all the image groups (step S16; NO), this processing ends.

  FIG. 10 shows an example in which the image data of the first, second, and fourth frames are determined to have a face area, and the image data of the third frame is determined to have no face area among the groups determined to be backlit. It is. Since the first frame of image data has a face area, density correction processing is performed to set the average density of the face area to a target density value, and gradation compression processing is further performed. Since the image data of the second frame also has a face area, density correction processing is performed to set the average density of the face area of the second frame to the target density value, and gradation compression processing is further performed. Since there is no face area for the image data of the third frame, density correction processing is performed to set the group average face density (average density of the face areas of the first, second, and fourth frames) to the target density value. Tone compression processing is performed. Since the image data of the fourth frame has a face area, density correction processing is performed to set the average density of the face area to a target density value, and gradation compression processing is further performed.

  As described above, according to the image processing apparatus 1 of the first embodiment, when there is a face area, the density correction process is performed to set the density of the face area to the target density value. Thus, it is possible to perform correction processing for setting the face area to the target density value. When there is no face area, correction processing (reference correction processing conditions) for setting the group average face density to the target density value is performed, so that the stability of the process can be achieved. Therefore, the stability of the correction process for the entire series of image data can be achieved.

  In addition, when grouping image data, the image data in which the shooting order is continuous are grouped, so that the effect of selecting similar images is enhanced.

  Note that when determining the correction processing conditions, processing based on the reference correction processing conditions (correction processing for setting the group average face density to the target density value) may be performed on all the image data in the group. . Further, for the image data from which the face area is extracted, correction processing may be performed in which the average value of the face average density and the group average face density of the frame is set to the target density value.

  Further, the face average density of the first frame in the group may be used as the reference correction processing condition. Also in this case, it is possible to perform processing based on the face average density of the first frame for all other image data in the group, and when a face region is extracted, the face of that frame When the average density is used and the face area is not extracted, the face average density of the first frame may be used. For the image data from which the face area is extracted, the face average density of the frame is used. Correction processing for setting the average value of the face average density of the first frame to the target density value may be performed.

  In the correction process shown in FIG. 4, the light distribution conditions are collectively determined for the image data for one order, and the groups are grouped for one order. However, the correction process is performed one frame at a time. Indicates whether or not the n-th frame image to be corrected is similar to the (n−1) -th frame image or the (n−1) -th frame images that have already been corrected. If they are judged and similar, they can be handled as one group.

  Similarly, the case of performing face extraction processing on image data for one order has been described, but face extraction processing may be performed frame by frame and correction processing may be performed. In this case, in the example shown in FIG. 10, since there is a face area for the image data of the first frame and the second frame, density correction processing is performed to set the average density of each face area to the target density value. Since the image data of the third frame has no face area, density correction processing is performed to set the average density of the face areas of the first and second frames to the target density value as the group average face density.

  In addition, the continuity of the shooting order is also used as an index for grouping, but non-continuous image data (for example, the first, third, and fifth frames) may be set as the same group.

  In the first embodiment, the presence / absence of a face area obtained by face extraction processing is used as information on the main subject. However, tag information such as Exif (for example, shooting mode (portrait, landscape, macro), focal length, etc. It is also possible to infer from (such as a person who is a distant view).

<Modification>
In the first embodiment, the correction processing conditions are determined based on the presence / absence of a face area in the image. However, when the light distribution condition is a front light scene, the appearance frequency is higher, and the person is more likely to be compared to backlight or strobe light. There are many scenes that are not photographed, and the face orientation is undefined and the skin color area is easy to extract, but since face determination is often difficult, in addition to the presence or absence of the face area, the face candidate area (skin color area) It is preferable to determine the correction processing condition based on the position.

  FIG. 11 shows an example of the case where the first to fourth frame images are determined to be forward light and the fifth frame image is determined to be strobe light by the light distribution condition determination processing. Since the images of the first frame to the fourth frame are consecutively photographed, the images of the first frame to the fourth frame are grouped into the same group. Among the groups determined to have the following light, the image data for the first and second frames are determined to have a face area, and the image data for the third frame are determined to have no face area. A skin color area (face candidate area) is extracted at substantially the same position as the face area of the image data, and it is determined that there is no face area in the fourth frame image data, which is substantially the same as the face area of the first and second frame image data. It is determined that there is no skin color area at the position.

  In this case, since there is a face area for the image data of the first frame, a gradation conversion curve with the average density of this face area as a target density value is created and density correction processing is performed. Since the image data of the second frame also has a face area, similarly, a gradation conversion curve that creates the average density of the face area of the second frame as a target density value is created, and density correction processing is performed. The image data for the third frame has no face area, but since the skin color area is at the same position as the face area of the image data for the first and second frames, the group average face density (the face area for the first and second frames) A gradation conversion curve with the average density) as a target density value is created, and density correction processing is performed. The image data of the fourth frame has neither a face area nor a skin color area, and therefore a predetermined density correction process based on the light distribution condition is performed. Alternatively, the density correction process may be performed on the image data of the fourth frame so as to be similar to the average luminance distribution of the image data of the first, second, and third frames.

[Second Embodiment]
Next, a second embodiment to which the present invention is applied will be described.
In the image processing apparatus shown in the second embodiment, the same components as those in the image processing apparatus 1 shown in the first embodiment are denoted by the same reference numerals, and the illustration and description thereof are omitted. . Hereinafter, processing characteristic of the second embodiment will be described.

  In the second embodiment, image data is grouped based on information on main subject information (presence / absence of a face candidate region) in addition to information on light distribution conditions.

  FIG. 12 is a flowchart illustrating correction processing executed in the image adjustment processing unit 704 of the image processing apparatus according to the second embodiment.

  First, one-order image data input from the image transfer means 30 or the communication means (input) 32 is acquired (step S51).

  Next, a light distribution condition determination process for each image data is performed (step S52). Since the light distribution condition determination process has been described in step S2 of the first embodiment, the description thereof is omitted.

  Next, a face candidate area (skin color area) is extracted from each image data (step S53). When a human face candidate area is extracted, the extracted face candidate area is a face area by using a neural network that has learned a human face determination process using a signal indicating the face candidate area as an input signal. Is determined (step S54). Since the face candidate area extraction process and the face determination process have been described in step S5 of the first embodiment, description thereof will be omitted.

  Next, the image data is grouped based on the light distribution condition, the presence / absence of the face candidate region, and the photographing order (step S55).

  FIG. 13 shows an example of the case where the first to fourth frame images are determined to be forward light and the fifth frame image is determined to be strobe light by the light distribution condition determination processing. Among the groups determined to have the following light, the image data for the first and second frames are determined to have a face area, and the image data for the third frame are determined to have no face area. A skin color area (face candidate area) is extracted at substantially the same position as the face area of the image data, and it is determined that there is no face area in the fourth frame image data, which is substantially the same as the face area of the first and second frame image data. It is determined that there is no skin color area at the position. Furthermore, since the images of the first frame to the third frame are in the order of shooting, the images of the first frame to the third frame are grouped as a group with a face candidate area in the front light.

  Next, when the image data included in the M group is 2 or more (step S56; YES), the average density (group average face density) of the face area of each image data included in the M group is calculated ( Step S57).

  Next, the process proceeds to correction processing of each image. First, the Nth image data of the M group is acquired (step S58), and it is determined whether or not there is a face area in the image (step S59).

  When there is a face area in the Nth image data of the M group (step S59; YES), the average density of the face area of the image data is acquired (step S60), and the average density of the face area is determined in advance. A gradation conversion curve for creating the target density value is created, and density correction processing is performed based on the gradation conversion curve (step S61).

  When there is no face area in the Nth image data of the M group (step S59; NO), the group average face density calculated in step S57 is acquired (step S62), and the group average face density is determined in advance. A gradation conversion curve for creating the target density value is created, and density correction processing is performed based on the gradation conversion curve (step S63).

  After step S61 or step S63, gradation compression processing is performed if necessary when the width of the density value distribution is wide (step S64).

  Next, when there is the next image data in the M group (step S65; YES), the process returns to step S58, and the processes of steps S58 to S64 are repeated.

  In step S56, when there is one image data included in the M group (step S56; NO), correction processing suitable for the image data is performed (step S66).

  When all the processing of the image data in the M group is completed (step S65; NO), or after step S66 is completed, it is determined whether there is a next image group (step S67). If there is a next image group (step S67; YES), the process returns to step S56, and the processes of steps S56 to S66 are repeated.

  When the processing is completed for all the image groups (step S67; NO), this processing ends.

  As described above, according to the image forming apparatus of the second embodiment, information regarding the main subject region (especially the face of a person) with a high degree of attention of the viewer, and the status and atmosphere of the entire image are shown to the viewer. By setting two groups of image data within one order using two pieces of information related to the light distribution conditions of the images responsible for transmission, a group setting close to the sensitivity that the viewer feels that the images are similar is set. It can be performed with high accuracy.

  If there is a face area, density correction processing is performed to set the density of the face area to the target density value. If there is no face area, correction processing to set the group average face density to the target density value (reference correction processing). Therefore, the stability of the correction process for the entire series of image data can be improved.

  In the second embodiment, the presence / absence of the face candidate area and the position of the face candidate area are used as the information on the main subject used for grouping, but the number of faces (0, 1, 2,... Alternatively, none, one, several (2-5), 6 or more, etc.), face size (large, medium, small), etc. may be used.

  The description in each of the above embodiments is an example of the image processing apparatus according to the present invention, and the present invention is not limited to this. The detailed configuration and detailed operation of each part constituting the apparatus can be changed as appropriate without departing from the spirit of the present invention.

  For example, image data may be grouped or image processing conditions may be determined based on image composition, density distribution, and chromaticity distribution.

  In each of the above embodiments, the case where density correction processing (tone correction processing) is performed as correction processing has been described. However, tone correction processing, density correction processing, contrast adjustment processing, color balance adjustment processing, saturation, and the like are described. Correction processing known in the art, such as adjustment processing, color correction processing such as hue correction, dodging processing, sharpness adjustment processing, and noise suppression processing, may be performed alone or in combination.

1 is a perspective view illustrating an overview configuration of an image processing apparatus 1 according to a first embodiment of the present invention. 2 is a block diagram showing an internal configuration of the image processing apparatus 1. FIG. 2 is a block diagram illustrating a functional configuration of an image processing unit 70 of the image processing apparatus 1. FIG. 6 is a flowchart illustrating a correction process executed in an image adjustment processing unit 704. It is a flowchart which shows a light distribution condition discrimination | determination process. It is a flowchart which shows a 1st occupation rate calculation process. It is a flowchart which shows a 2nd occupation rate calculation process. It is a figure which shows the area | region n1-n4 determined according to the distance from the outer edge of the screen of image data. It is a plot figure which shows the relationship between an imaging | photography scene (forward light, strobe, backlight, under) and the indices 4-6. It is a figure for demonstrating the determination method of the correction process conditions of the image data in 1st Embodiment. It is a figure for demonstrating the determination method of the correction process conditions of the image data in the modification of 1st Embodiment. It is a flowchart which shows the correction process performed in the image adjustment process part 704 of the image processing apparatus of 2nd Embodiment. It is a figure for demonstrating the determination method of the correction process condition of the image data in 2nd Embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Image processing apparatus 4 Exposure processing part 5 Print preparation part 7 Control part 8 CRT
DESCRIPTION OF SYMBOLS 9 Film scanner part 10 Reflective original input device 11 Operation part 14 Image reading part 15 Image writing part 30 Image transfer means 31 Image conveyance part 32 Communication means (input)
33 Communication means (output)
34 External Printer 70 Image Processing Unit 701 Film Scan Data Processing Unit 702 Reflected Original Scan Data Processing Unit 703 Image Data Format Decoding Processing Unit 704 Image Adjustment Processing Unit 705 CRT Specific Processing Unit 706 Printer Specific Processing Unit (1)
707 Printer-specific processing unit (2)
708 Image data format creation processing unit 71 Data storage means

Claims (18)

In an image processing method for performing correction processing on a plurality of captured image data and generating a corrected image,
Based on the information on the light distribution conditions at the time of shooting, the plurality of shot image data are grouped,
For a group including two or more photographed image data, the correction of the photographed image data to be corrected is performed based on the reference correction processing condition in the group and / or information on the main subject region of the photographed image data to be corrected. An image processing method characterized by determining a processing condition. In an image processing method for performing correction processing on a plurality of captured image data and generating a corrected image,
Based on the information on the light distribution conditions at the time of shooting and the information on the main subject area, the plurality of shot image data are grouped,
For a group including two or more photographed image data, the correction of the photographed image data to be corrected is performed based on the reference correction processing condition in the group and / or information on the main subject region of the photographed image data to be corrected. An image processing method characterized by determining a processing condition. The image processing method according to claim 1 or 2,
An image processing method characterized in that, when grouping the plurality of photographed image data, the photographed image data in which the photographing order is continued is made into the same group. In the image processing method as described in any one of Claims 1-3,
The image processing method according to claim 1, wherein the main subject area is a human face area. In the image processing method according to any one of claims 1 to 4,
The image processing method characterized in that the information regarding the main subject area referred to when determining the correction processing condition is the presence or absence of the main subject area. In the image processing method according to any one of claims 1 to 5,
The image processing method according to claim 1, wherein the light distribution condition at the time of photographing includes at least one of a backlight state, a flash light utilization state, and an under state. In an image processing apparatus that performs correction processing on a plurality of captured image data and generates a corrected image,
Grouping means for grouping the plurality of photographed image data based on information on light distribution conditions at the time of photographing;
For a group including two or more photographed image data, the correction of the photographed image data to be corrected is performed based on the reference correction processing condition in the group and / or information on the main subject region of the photographed image data to be corrected. Correction processing condition determining means for determining processing conditions;
An image processing apparatus comprising: In an image processing apparatus that performs correction processing on a plurality of captured image data and generates a corrected image,
Grouping means for grouping the plurality of photographed image data based on information on light distribution conditions at the time of photographing and information on a main subject area;
For a group including two or more photographed image data, the correction of the photographed image data to be corrected is performed based on the reference correction processing condition in the group and / or information on the main subject region of the photographed image data to be corrected. Correction processing condition determining means for determining processing conditions;
An image processing apparatus comprising: The image processing apparatus according to claim 7 or 8,
The image processing apparatus according to claim 1, wherein the grouping unit further groups the captured image data in which the imaging order is continuous into the same group. In the image processing device according to any one of claims 7 to 9,
The image processing apparatus according to claim 1, wherein the main subject area is a human face area. In the image processing device according to any one of claims 7 to 10,
The image processing apparatus according to claim 1, wherein the information on the main subject area referred to when determining the correction processing condition is the presence or absence of the main subject area. In the image processing device according to any one of claims 7 to 11,
The image processing apparatus according to claim 1, wherein the light distribution condition at the time of photographing includes at least one of a backlight state, a flash light utilization state, and an under state. In an image processing program for realizing a function of performing correction processing on a plurality of captured image data and generating a corrected image on a computer,
In the computer,
A grouping function for grouping the plurality of photographed image data based on information on light distribution conditions at the time of photographing;
For a group including two or more photographed image data, the correction of the photographed image data to be corrected is performed based on the reference correction processing condition in the group and / or information on the main subject region of the photographed image data to be corrected. Correction processing condition determination function for determining processing conditions;
An image processing program characterized by realizing the above. In an image processing program for realizing a function of performing correction processing on a plurality of captured image data and generating a corrected image on a computer,
In the computer,
A grouping function for grouping the plurality of photographed image data based on information on light distribution conditions at the time of photographing and information on a main subject area;
For a group including two or more photographed image data, the correction of the photographed image data to be corrected is performed based on the reference correction processing condition in the group and / or information on the main subject region of the photographed image data to be corrected. Correction processing condition determination function for determining processing conditions;
An image processing program characterized by realizing the above. The image processing program according to claim 13 or 14,
An image processing program characterized in that, when realizing the grouping function, photographed image data in which the photographing order is continued are made into the same group. In the image processing program as described in any one of Claims 13-15,
An image processing program characterized in that the main subject area is a human face area. The image processing program according to any one of claims 13 to 16,
An image processing program characterized in that the information on the main subject area referred to when determining the correction processing condition is the presence or absence of the main subject area. In the image processing program as described in any one of Claims 13-17,
The image processing program characterized in that the light distribution condition at the time of photographing includes at least one of a backlight condition, a flash light utilization condition, and an under condition.

Images