JP2009151825A - Image processor and image processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a technology for acquiring a more preferable deformation processing result when regions of deformed objects are overlapped with each other. <P>SOLUTION: This image processor includes: a deformed region setting part for analyzing an object image TI and setting a plurality of deformed regions TA1, TA2 on the object image TI, and a deformation processing part for deforming images in the deformed regions TA1, TA2. The deformation processing part reduces the deformation amount of a partial region of part of each of the plurality of deformed regions TA1, TA2 including an overlapped portion of the plurality of deformed regions TA1, TA2 when the plurality of deformed regions TA1, TA2 are overlapped with each other. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an image processing technique for deforming a partial area on a target image.

  An image processing technique for deforming an image for a digital image is known (for example, Patent Document 1). In Patent Document 1, a partial area (an area representing a cheek image) on a face image is set as a correction area, the correction area is divided into a plurality of small areas according to a predetermined pattern, and set for each small area. Image processing for deforming the shape of a face by enlarging or reducing the image at a specified magnification is disclosed.

JP 2004-318204 A

  In the above-described conventional image processing for image deformation, since the correction area where the image is deformed is set to an area representing the cheek image, these correction areas usually do not overlap. Therefore, no consideration is given to the case where the correction areas to be deformed overlap. This problem is common not only in image processing for correcting a face but also in general image processing for correcting a part of an image.

  The present invention has been made in order to solve the above-described conventional problems, and an object of the present invention is to provide a technique that makes the deformation processing result more preferable when the areas to be deformed overlap.

  In order to solve at least a part of the above problems, an image processing apparatus of the present invention analyzes a target image and sets a plurality of deformation regions on the target image, and an image in the deformation region. A deformation processing unit that performs the deformation of the plurality of deformation regions, and when the plurality of deformation regions overlap, the deformation processing unit includes a part of each of the plurality of deformation regions including an overlapping portion of the plurality of deformation regions. The amount of deformation of the partial region is reduced.

  According to this configuration, since the amount of deformation of the partial area including the overlapping portion is reduced, even if the deformation processing for deforming each of the plurality of deformation regions is performed on the overlapping portion, the overlapping portion of the individual deformation processing The effect on is reduced. Therefore, since unnatural deformation of an image caused by repeating the deformation process on the overlapping portion can be suppressed, the deformation process result can be made more preferable.

  The deformation processing unit performs deformation of an image in the deformation area by deforming a small area obtained by dividing the deformation area into a plurality of areas, and the partial area overlaps the overlapping portion of the plurality of small areas. It is good also as what is the whole or one part area | region.

  According to this configuration, by setting the deformation amount for each small region, the deformation amount of the small region overlapping the overlapping portion can be reduced. Therefore, the deformation amount of the partial area can be reduced more easily.

  The partial area may include a partial area obtained by further dividing a small area overlapping the overlapping part.

  According to this configuration, the partial region can be made smaller by dividing the small region that overlaps the overlapping portion. Therefore, the range in which the deformation amount in the deformation region is reduced can be further reduced.

  The deformation processing unit may set the deformation amount of the partial region to zero.

  According to this configuration, since the partial area is not deformed, the image of the overlapping portion is maintained in the state before the deformation process. Therefore, it is possible to suppress unnatural deformation of the image caused by repeating the deformation process, and to make the deformation process result more preferable.

  The target image may be an image including a person's face, and the deformation area setting unit may set an area including images of a plurality of organs of the person's face as the deformation area.

  When a plurality of organs included in a person's face are included as the deformation area, the deformation areas tend to overlap. In general, the face of a person is a region having a high degree of attention in the image. For this reason, when a person's face is deformed, it is desirable to obtain a more natural deformation result, so that the effect of performing the deformation process based on the priority order is further increased.

[Means for performing deformation processing]
In order to perform deformation processing, the image processing device is an image processing device that performs image deformation, and includes a deformation area setting unit that sets at least a partial area on the target image as a deformation area; A plurality of dividing points are arranged in the area, and a deformation area dividing unit that divides the deformation area into a plurality of small areas using a straight line connecting the dividing points, and the position of at least one of the dividing points is moved to the small area. A deformation processing unit that deforms an image in the deformation area by deforming the area.

  In this image processing apparatus, a plurality of division points are arranged in a deformation area set on the target image, and the deformation area is divided into a plurality of small areas using straight lines connecting the division points. Also, the position of the dividing point is moved, and the small area is deformed, whereby the deformation process of the image in the deformed area is executed. As described above, in this image processing apparatus, it is possible to perform image deformation by simply arranging the dividing points in the deformation area and moving the arranged dividing points, and image deformation images corresponding to various deformation modes. Processing can be realized easily and efficiently.

  The image processing apparatus further includes a deformation mode setting unit that selects one of a plurality of predetermined deformation types and sets it as a deformation type to be applied to the deformation of the image in the deformation area. The unit may arrange the plurality of division points according to a predetermined arrangement pattern associated with the set deformation type.

  In this way, for example, the arrangement of division points suitable for each deformation type, such as the deformation type that sharpens the face and the deformation type that enlarges the eyes, that is, the division of the deformation area is performed. Further simplification of image processing for image deformation can be realized.

  In the image processing apparatus, the deformation mode setting unit selects one of a plurality of predetermined deformation degrees and sets it as a deformation degree to be applied to the deformation of the image in the deformation area, and the deformation process The unit may move the position of the division point according to a predetermined movement direction and movement amount associated with the combination of the set deformation type and the deformation degree.

  In this way, if the deformation type and the degree of deformation are set, image deformation according to the combination thereof is executed, so that it is possible to further facilitate image processing for image deformation.

  In the image processing apparatus, the deformation mode setting unit includes a designation obtaining unit that obtains a user designation regarding a movement direction and a movement amount of the division point for at least one of the division points, and the deformation processing unit includes: The position of the division point may be moved according to the acquired user designation.

  In this way, it is possible to easily realize image processing for image deformation in a manner closer to the user's desire.

  In the image processing apparatus, the deformation area setting unit may set the deformation area so that at least a part of an image of a face is included in the deformation area.

  In this way, it is possible to easily and efficiently realize image processing for image deformation corresponding to various deformation modes for a face image.

  In the image processing apparatus, the deformation region dividing unit arranges the plurality of division points so that at least one set of the division points is arranged at positions symmetrical to each other with respect to a predetermined reference line, The deformation processing unit may move the at least one set of division points while maintaining a positional relationship that is symmetrical with respect to the predetermined reference line.

  In this way, image deformation that is bilaterally symmetric with respect to a predetermined reference line is performed, and image processing for image deformation of a more natural and preferable face image can be realized.

  In the image processing apparatus, the deformation processing unit may not perform deformation on at least one of the small regions.

  In this way, it is possible to perform desired image deformation without greatly changing the impression of the face, and it is possible to realize image processing for more natural and preferable face image deformation.

  In the image processing apparatus, the deformation processing unit may not perform deformation on the small region including the eye image.

  In this way, it is possible to realize image processing for image deformation of a more natural and preferable face image by not performing deformation on a small region including an eye image.

  The image processing apparatus further includes a face area detection unit that detects a face area representing a face image on the target image, and the deformation area setting unit is configured to detect the deformation area based on the detected face area. May be set.

  In this way, image processing for image deformation corresponding to various deformation modes can be realized easily and efficiently for image deformation of the deformation area set based on the face area detected from the target image. can do.

  The image processing apparatus may further include a printing unit that prints the target image on which the image in the deformation area has been deformed. In this way, it is possible to easily and efficiently realize printing of the image after image deformation corresponding to various deformation modes.

  Note that the present invention can be realized in various modes, for example, an image processing method and apparatus, an image deformation method and apparatus, an image correction method and apparatus, and a function of these methods or apparatuses. The present invention can be realized in the form of a computer program, a recording medium recording the computer program, a data signal including the computer program and embodied in a carrier wave, and the like.

1 is an explanatory diagram schematically showing a configuration of a printer to which an image processing apparatus as an embodiment of the present invention is applied. It is explanatory drawing which shows an example of the user interface containing the list display of an image. 7 is a flowchart illustrating a face shape correction printing routine executed when face shape correction printing is performed in a printer. The flowchart which shows the face shape correction process routine in 1st Example. Explanatory drawing which shows an example of the user interface for setting the type and degree of image deformation. Explanatory drawing which shows an example of the detection result of a face area | region. Explanatory drawing which shows the setting result of a deformation | transformation area | region. Explanatory drawing which shows a mode that each of two deformation | transformation area | regions was divided | segmented into the small area | region. Explanatory drawing which shows a mode that the small area | region which belongs to each of two deformation | transformation area | regions is deform | transformed. Explanatory drawing which shows the result by which the deformation | transformation process was performed in 1st Example. Explanatory drawing which shows a mode that a deformation | transformation process is performed to both a non-overlapping small area | region and an overlapping small area | region. Explanatory drawing which shows the result of performing a deformation | transformation process to any of the two deformation area | regions which overlap in a comparative example. Explanatory drawing which shows an example of the state of the display part in which the target image after face shape correction | amendment was displayed. Explanatory drawing which shows schematically the structure of the printer in 2nd Example. The flowchart which shows the face shape correction process routine in 2nd Example. Explanatory drawing which shows the division | segmentation result of a deformation | transformation area | region at the time of changing a division | segmentation form. Explanatory drawing which shows a mode that the small area | region of two deformation | transformation areas is deform | transformed in 2nd Example. Explanatory drawing which shows the result by which the deformation | transformation process was performed in 2nd Example. Explanatory drawing which shows another example of the detection result of face area FA. The flowchart which shows the flow of a setting process of a deformation | transformation area | region. The flowchart which shows the flow of the position adjustment process of the height direction of face area FA. Explanatory drawing which shows an example of specific area | region SA. Explanatory drawing which shows an example of the calculation method of an evaluation value. Explanatory drawing which shows an example of the selection method of evaluation object pixel TP. Explanatory drawing which shows an example of the determination method of height reference point Rh. Explanatory drawing which shows an example of the calculation method of rough inclination angle RI. Explanatory drawing which shows an example of the position adjustment method of the height direction of face area FA. The flowchart which shows the flow of the inclination adjustment process of face area FA. Explanatory drawing which shows an example of the calculation method of the evaluation value for inclination adjustment of the face area FA. Explanatory drawing which shows an example of the calculation result of the dispersion | distribution of the evaluation value about each evaluation direction. Explanatory drawing which shows an example of the inclination adjustment method of face area FA. Explanatory drawing which shows an example of the setting method of deformation | transformation area | region TA. Explanatory drawing which shows an example of the division | segmentation method into the small area | region of the deformation | transformation area | region TA. Explanatory drawing which shows an example of the content of the dividing point movement table. Explanatory drawing which shows an example of the movement of the position of the dividing point D according to the dividing point movement table 420. FIG. FIG. 3 is an explanatory diagram showing a concept of an image deformation processing method by a divided region deformation unit 260. Explanatory drawing which shows the concept of the deformation | transformation processing method of the image in a triangular area | region. Explanatory drawing which shows an example of the aspect of face shape correction | amendment.

Next, embodiments of the present invention will be described in the following order based on examples.
A. First embodiment:
B. Second embodiment:
C. Deformation area settings:
D. Division point arrangement:
E. Small area transformation:
F. Variations:

A. First embodiment:
FIG. 1 is an explanatory diagram schematically showing the configuration of a printer 100 to which an image processing apparatus as an embodiment of the present invention is applied. The printer 100 is a color inkjet printer compatible with so-called direct printing, in which an image is printed based on image data acquired from a memory card MC or the like. The printer 100 includes a CPU 110 that controls each unit of the printer 100, an internal memory 120 configured by, for example, a ROM and a RAM, an operation unit 140 configured by buttons and a touch panel, a display unit 150 configured by a liquid crystal display, A printer engine 160 and a card interface (card I / F) 170 are provided. The printer 100 may further include an interface for performing data communication with other devices (for example, a digital still camera or a personal computer). Each component of the printer 100 is connected to each other via a bus.

  The printer engine 160 is a printing mechanism that performs printing based on print data. The card interface 170 is an interface for exchanging data with the memory card MC inserted in the card slot 172. In the first embodiment, image data as RGB data is stored in the memory card MC, and the printer 100 acquires the image data stored in the memory card MC via the card interface 170.

  The internal memory 120 stores a face shape correction unit 200, a display processing unit 310, and a print processing unit 320. The face shape correction unit 200 is a computer program for executing a face shape correction process described later under a predetermined operating system. The display processing unit 310 is a display driver that controls the display unit 150 to display processing menus and messages on the display unit 150. The print processing unit 320 is a computer program for generating print data from image data, controlling the printer engine 160, and printing an image based on the print data. The CPU 110 implements the functions of these units by reading and executing these programs from the internal memory 120.

  The face shape correction unit 200 includes, as program modules, a deformation mode setting unit 210, a face region detection unit 220, a face region adjustment unit 230, a deformation region setting unit 240, a deformation region dividing unit 250, and a divided region deformation unit. 260 and the overlapping small area detection unit 270. The deformation mode setting unit 210 includes a designation acquisition unit 212. As will be described later, the deformation region dividing unit 250, the divided region deforming unit 260, and the overlapping small region detecting unit 270 perform image deformation. Therefore, the deformation area dividing unit 250, the divided area deformation unit 260, and the overlapping small area detection unit 270 can be collectively referred to as a “deformation processing unit”. The functions of these units will be described later.

  The internal memory 120 also stores a dividing point arrangement pattern table 410 and a dividing point movement table 420. The contents of the dividing point arrangement pattern table 410 and the dividing point movement table 420 will be described in detail in the description of the face deformation process described later.

  The printer 100 prints an image based on the image data stored in the memory card MC. When the memory card MC is inserted into the card slot 172, the display processing unit 310 displays a user interface including a list display of images stored in the memory card MC on the display unit 150. FIG. 2 is an explanatory diagram illustrating an example of a user interface including a list display of images. In the first embodiment, the list display of images is realized using thumbnail images included in image data (image files) stored in the memory card MC. In the user interface shown in FIG. 2, eight thumbnail images TN1 to TN6 and five buttons BN1 to BN5 are displayed.

  When the user selects one (or a plurality of) images and the normal print button BN3 in the user interface shown in FIG. 2, the printer 100 prints the selected image as usual. Execute. On the other hand, in the user interface, when one (or a plurality) of images is selected by the user and the face shape correction print button BN4 is selected, the printer 100 displays the face of the image in the selected image. A face shape correction printing process for correcting the shape and printing the corrected image is executed. In the example of FIG. 2, the thumbnail image TN1 and the face shape correction print button BN4 are selected. Therefore, the printer 100 corrects the face shape of the image corresponding to the thumbnail image TN1, and prints the corrected image.

  FIG. 3 is a flowchart illustrating a face shape correction printing routine executed when the printer 100 performs face shape correction printing. In step S100, the face shape correction unit 200 (FIG. 1) executes face shape correction processing. The face shape correction process is a process for correcting at least a part of a face in the image (for example, a face outline shape or an eye shape). A part of the face such as eyes and nose is generally called an organ.

  FIG. 4 is a flowchart showing the face shape correction processing routine executed in step S100 of FIG. In step S110, the face shape correction unit 200 (FIG. 1) sets a target image to be subjected to face shape correction processing. The face shape correction unit 200 sets an image corresponding to the thumbnail image TN1 selected by the user in the user interface shown in FIG. 2 as a target image. The set image data of the target image is acquired by the printer 100 from the memory card MC via the card interface 170 and stored in a predetermined area of the internal memory 120. Hereinafter, the image data acquired from the memory card MC and stored in the internal memory 120 of the printer 100 is also referred to as “original image data”. An image represented by the original image data is also referred to as “original image”.

  In the first embodiment, the target image is set according to the selection result of the user in the user interface shown in FIG. 2, but the target image can be set by other methods. For example, an image (face image) including a face is extracted from a plurality of images stored in the memory card MC based on information such as Exif information stored in the image data or a scene determination result of the image data. In addition, the extracted face image can be set as the target image. In addition, in a user interface including a list display of extracted face images, the user may select one or a plurality of face images and set the target image according to the selection result. When a plurality of images are set as target images, face shape correction may be performed on the plurality of images at the same time. Priorities are assigned to the plurality of images, and the face shapes are applied to the plurality of images according to the priorities. May be corrected.

  In step S120 (FIG. 4), the deformation mode setting unit 210 (FIG. 1) sets the type of image deformation and the degree of image deformation for face shape correction. The deformation mode setting unit 210 instructs the display processing unit 310 to display a user interface for setting the type and degree of image deformation on the display unit 150, and the image deformation type designated by the user through the user interface. And the degree are selected and set as the image deformation type and degree used for processing.

  FIG. 5 is an explanatory diagram showing an example of a user interface for setting the type and degree of image deformation. As shown in FIG. 5, the user interface includes an interface for setting an image deformation type. In the first embodiment, for example, a deformation type “type A” that sharpens the shape of the face, a deformation type “type B” that increases the shape of the eyes, and the like are set in advance as options. The user specifies the type of image deformation via this interface. The deformation mode setting unit 210 sets the image deformation type designated by the user as the image deformation type used for actual processing.

  The user interface shown in FIG. 5 includes an interface for setting the degree (degree) of image deformation. As shown in FIG. 5, in the first embodiment, it is assumed that three levels of strong (S), medium (M), and weak (W) are preset as options as the degree of image deformation. The user designates the degree of image deformation through this interface. The deformation mode setting unit 210 sets the degree of image deformation designated by the user as the degree of image deformation used for actual processing. A check box provided in the user interface is checked when the user desires detailed designation of the deformation mode.

  Thereafter, the deformation type “type A” for sharpening the face shape is set as the image deformation type, the degree of “medium” is set as the degree of image deformation, and there is no desire for detailed designation by the user. The explanation will be made assuming that

  In step S130 (FIG. 4), the face area detection unit 220 (FIG. 1) detects a face area in the target image. Here, the face area is an image area on the target image and means an area including at least a partial image of the face. The detection of the face area by the face area detection unit 220 is executed using a known face detection method such as a pattern matching method using a template (see Japanese Patent Application Laid-Open No. 2004-318204).

  FIG. 6 is an explanatory diagram illustrating an example of a face area detection result. In the example of FIG. 6, the target image TI includes two persons. Therefore, two face areas FA1 and FA2 corresponding to two persons are detected from the target image TI by the face detection in step S130. As shown in FIG. 6, these face areas are rectangular areas including respective eyes, nose, and mouth images.

  If no face area is detected in the detection of the face area in step S130, the fact is notified to the user through the display unit 150. In this case, normal printing without face shape correction may be performed. Further, the face area detection process using another face detection method may be performed again.

  In step S130, a face is detected from the target image by pattern matching using a template. Known face detection methods such as a pattern matching method using a template generally do not detect in detail the position and inclination (angle) of the entire face or part of the face (eyes, mouth, etc.) An area that is considered to include a face image from the target image is set as a face area.

  In step S500, the printer 100 sets an area (deformation area) to be subjected to image deformation processing for face shape correction based on the detected face area. Specifically, the deformation area is set by performing position adjustment and inclination adjustment on the face area detected in step S130 so that natural and preferable face shape correction is realized. By setting the deformation area in this way, a face image that generally has a high degree of attention of the observer is unnaturally deformed depending on the position and angle relationship between the set deformation area and the face image. Is suppressed. The method for setting the deformation area will be described in detail in the description of the deformation area setting described later.

  FIG. 7 is an explanatory diagram showing the setting result of the deformation area in step S500. The broken lines in FIG. 7 indicate the two face areas FA1 and FA2 detected from the target image TI in step S130. The thick lines in FIG. 7 indicate the deformation areas set for each of the two face areas FA1 and FA2. As shown in FIG. 7, in step S500, two deformation areas TA1, TA2 corresponding to each of these two face areas FA1, FA2 are set.

  In the first embodiment, the deformation mode is set in step S120 before face detection (step S130 in FIG. 4), but after step S130 or step S500, the same processing as step S120 is performed. Thus, the deformation mode may be set. In this way, by making it possible to set the deformation mode after the face detection in step S130, the face detection process is omitted when the deformation mode set in step S120 does not suit the user's preference and the deformation mode is set again. It becomes possible to do.

  In step S140 of FIG. 4, division points (described later) are arranged for each of the two set deformation areas TA1 and TA2, and each of the deformation areas TA1 and TA2 is divided into 15 rectangular small areas. Is done. FIG. 8 is an explanatory diagram showing a state in which each of the two deformation areas TA1, TA2 set in step S500 of FIG. 4 is divided into small areas. In addition, the division | segmentation into deformation | transformation area | region TA1, TA2 by arrange | positioning a dividing point to a small area | region is explained in full detail in description of the aspect of the dividing point arrangement | positioning mentioned later.

  FIG. 8A shows the arrangement of the two deformation areas TA1 and TA2 set in step S500 of FIG. FIG. 8B shows how each of the two deformation areas TA1 and TA2 is divided into small areas in step S140. As shown in FIG. 8A, the two deformation areas TA1 and TA2 set in step S500 are overlapped with each other. Therefore, among the small areas of the deformation area TA1, the small area hatched from the upper right to the lower left overlaps the deformation area TA2. On the other hand, the small area hatched from the upper left to the lower right of the deformation area TA2 overlaps the deformation area TA1. Hereinafter, a small region that belongs to a certain deformation region and overlaps another deformation region is also referred to as an “overlapping small region”. As is apparent from FIG. 8B, the overlapping small areas of the deformation areas TA1 and TA2 include overlapping portions of the deformation areas TA1 and TA2. Since the overlapping small area is a partial area of the deformation area, it can also be referred to as a “partial area”.

  In step S150, the overlapping small area detection unit 270 (FIG. 1) overlaps with other deformation areas as shown by hatching in FIG. 8B among the small areas belonging to the individual deformation areas divided in step S140. Detect small area. Whether or not a small area belonging to each deformation area overlaps with another deformation area can be determined using various algorithms for determining whether or not there is an overlap of plane figures. For example, it can be determined by examining whether or not the contour lines of the small region and the other deformation region intersect. It can also be determined by examining whether or not a point in the small area is included in another deformation area. If the small area and the other deformation area are both convex polygons, whether the vertex of the small area falls within the other deformation area, or whether the vertex of the other deformation area is within the small area Can be determined by examining the above.

  Next, in step S160, the divided region deformation unit 260 (FIG. 1) performs a deformation process on a small region (non-overlapping small region) that does not overlap the other deformation region among the small regions of the deformation regions TA1 and TA2. Do. The deformation process of the non-overlapping small area is performed by moving the dividing points arranged when the deformation area is divided into small areas. The specific content of the deformation process will be described in detail in the description of the deformation of the small area described later.

  As shown in FIG. 8, when there are a plurality of deformation areas TA1, TA2, deformation processing for each deformation area is performed on the original image. The deformation process for the plurality of deformation areas may be executed by repeating the deformation process for each of the deformation areas, or the deformation process may be simultaneously performed for the plurality of deformation areas.

  FIG. 9 is an explanatory diagram showing how the small areas belonging to each of the two deformation areas TA1 and TA2 are deformed in step S160. Black circles DA11, DA12, DA21 and white circles DA22, DA31, DA32, DA41, DA42 in the deformation area TA1 indicate division points arranged when the deformation area TA1 is divided into small areas. Similarly, black circles DB41 and DB42 and white circles DB11, DB12, DB21, DB22, DB31, and DB32 in the deformation area TA2 indicate division points arranged when the deformation area TA2 is divided into small areas. In FIG. 9, the overlapping small areas in the deformation areas TA1 and TA2 are shown with hatching.

  In the example of FIG. 9, the dividing points that are the vertices of the overlapping small area of the deformation area TA1 are five dividing points DA22, DA31, DA32, DA41, DA42 indicated by white circles. Therefore, in the deformation process in step S160, these division points DA22, DA31, DA32, DA41, DA42 are not moved. On the other hand, the dividing points DA11, DA12, DA21 indicated by black circles that are not the vertices of the overlapping small areas are moved from the positions of the black circles to the positions of the stars. By moving the dividing points DA11, DA12, DA21 in this way, the small area indicated by the dotted line is deformed as indicated by the solid line.

  Similarly, the division points that are the vertices of the overlapping small area of the deformation area TA2 are six division points DB11, DB12, DB21, DB22, DB31, and DB32 indicated by white circles. Therefore, in the deformation process in step S160, these division points DB11, DB12, DB21, DB22, DB31, and DB32 are not moved. On the other hand, the dividing points DB41 and DB42 indicated by the black circles that are not the vertices of the overlapping small areas are moved from the black circle positions to the star positions. By moving the dividing points DB41 and DB42 in this way, the small area indicated by the dotted line is deformed as indicated by the solid line.

  FIG. 10 is an explanatory diagram illustrating a result of the deformation process performed in the first embodiment. FIG. 10A shows the target image TI before the deformation processing in steps S140 to S160 in FIG. FIG. 10B shows the target image TI after the deformation process. As described above, the two deformation areas TA1 and TA2 set on the faces of two persons in the target image TI overlap each other. Therefore, only the non-overlapping small areas of the two deformation areas TA1 and TA2 are deformed, and the overlapping small areas are not deformed. Therefore, as shown in FIG. 10B, the face of the left person included in the non-overlapping small area in the deformation area TA1 becomes thin. Further, a part of the face of the right person included in the non-overlapping small area in the deformation area TA2 is deformed, and the outline of the face is slightly narrowed. On the other hand, a portion where the two deformation areas TA1 and TA2 overlap is included in the overlapping small area. Therefore, the overlapping portions of the deformation areas TA1 and TA2 are in the same state as before the deformation process (FIG. 10A).

  FIG. 11 is an explanatory diagram showing a state in which deformation processing is performed on both the non-overlapping small region and the overlapping small region as a comparative example. When the deformation process is performed on both the non-overlapping small area and the overlapping small area, the dividing points DA11 to DA42 and DB11 to DB42 of the deformation areas TA1 and TA2 are all objects to be moved. Therefore, these division points DA11 to DA42 and DB11 to DB42 are moved to positions indicated by asterisks, respectively. In the example of FIG. 11, as shown in FIG. 5, a deformation type “type A” for sharpening the shape of the face is set as the image deformation type. For this reason, since the deformation process is performed so as not to deform the size of the eyes, the four division points DA22, DA32, DB22, DB32 are not moved.

  FIG. 12 is an explanatory diagram illustrating a result of performing the deformation process on both of the two deformation areas TA1 and TA2 that overlap in the comparative example. FIG. 12A shows a target image TI (original image) before the deformation process is performed. FIG. 12B shows a deformation process result in the comparative example in which the deformation process is performed on the overlapping small area. FIG. 12C shows the result of the deformation process of the first embodiment in which the deformation process is not performed on the overlapping small area. As described above, the image after the deformation process in the deformation area is an image obtained by performing the deformation process on the original image. Therefore, in the overlapping part of the two deformation areas TA1 and TA2, the first deformation result is overwritten with the later deformation processing result. For this reason, in the comparative example in which the deformation process is performed also on the overlapping small areas, a discontinuous boundary line BL is generated as shown by a thick line in FIG.

  On the other hand, according to the first embodiment, since the deformation process is not performed on the overlapping small regions, a discontinuous boundary does not occur in the image after the deformation process as shown in FIG. As described above, in the first embodiment, it is possible to suppress the occurrence of a discontinuous boundary in the image after the deformation process and the image after the deformation process from being an unnatural image.

  In step S160 of FIG. 4, after the non-overlapping small region deformation process is performed, control is returned to the face shape correction printing routine of FIG.

  When the control returns from the face shape correction processing routine of FIG. 4, an image (corrected image) after the deformation processing is displayed in step S200 of FIG. Specifically, the face shape correction unit 200 (FIG. 1) instructs the display processing unit 310 to display the target image after the face shape correction on the display unit 150. FIG. 13 is an explanatory diagram illustrating an example of the state of the display unit 150 on which the target image TI after the face shape correction is displayed. The display unit 150 displaying the target image TI after the face shape correction allows the user to check the correction result. If the user is not satisfied with the correction result and selects the “Return” button, for example, the display unit 150 displays a screen for selecting the deformation type and the deformation degree shown in FIG. The setting is performed again. When the user is satisfied with the correction result and selects the “print” button, the following corrected image printing process is started. In the first embodiment, the corrected image is displayed on the display unit 150. However, the original image and the corrected image can be displayed on the display unit 150 at the same time.

  In step S300, the print processing unit 320 (FIG. 1) controls the printer engine 160 to print the target image after the face shape correction process. The print processing unit 320 generates print data by performing processing such as resolution conversion and halftone processing on the image data of the target image after the face shape correction processing. The generated print data is supplied from the print processing unit 320 to the printer engine 160, and the printer engine 160 prints the target image. Thereby, the printing of the target image after the face shape correction is completed.

B. Second embodiment:
FIG. 14 is an explanatory diagram schematically showing the configuration of the printer 100a in the second embodiment. The printer 100a of the second embodiment is different from the printer 100 of the first embodiment shown in FIG. 1 in that the face shape correction unit 200a includes an area overlap detection unit 280 and a division form change unit 290. Yes. Other points are the same as those of the printer 100 of the first embodiment.

  FIG. 15 is a flowchart showing a face shape correction processing routine in the second embodiment. This face shape correction processing routine is executed in step S100 of the face shape correction printing routine (FIG. 3) in the same manner as the face shape correction processing routine (FIG. 4) of the first embodiment. The face shape correction processing routine of the second embodiment is different from the face shape correction processing routine of the first embodiment shown in FIG. 4 in that two steps S132 and S134 are added before step S140. The other points are the same as the face shape correction printing routine of the first embodiment.

  In step S132, the region overlap detection unit 280 detects the presence / absence of overlap of the deformation regions set in step S500. The presence / absence of overlapping deformation areas can be determined using various algorithms for determining the presence / absence of overlapping planar figures, as in the detection of overlapping small areas (step S150). As a result of the detection, if it is determined that the deformation areas overlap, the control is moved to step S134. On the other hand, if it is determined that the deformation areas do not overlap, control is transferred to step S140.

  In step S134, the division form changing unit 290 changes the division form of the deformation area. Specifically, by changing the deformation type set in step S120 (FIG. 15), the deformation area division form in step S140 is changed. As will be described later, the division point arrangement mode that defines the division form of the deformation area is stored in the division point arrangement pattern table 410 (FIG. 14) in association with the deformation type. Therefore, the division form changing unit 290 may change the division form by either changing the correspondence relationship between the deformation type and the division point arrangement mode or changing the division point arrangement mode.

  FIG. 16 is an explanatory diagram illustrating a result of dividing the deformation area when the division form is changed. FIG. 16A shows the result of division of the deformation area when the division form is not changed, and FIG. 16B shows the result of division of the deformation area when the division form is changed. By changing the division form, each of the two deformation areas TA1 and TA2 is divided into 18 small areas, which are larger than when the division form shown in FIG. 16A is not changed. In this way, by changing the division form and increasing the small areas, the area of the overlapping small areas (hatched portions) in the deformation areas TA1 and TA2 can be further reduced.

  FIG. 17 is an explanatory diagram showing how the small areas of the two deformation areas are deformed in the second embodiment. FIG. 17 shows that the division points DA51, DA52, DB51, and DB52 are added to the two deformation areas TA1 and TA2 by changing the division form, and the overlapping small areas indicated by hatching are small. This is different from FIG. 9 in that the division points DA22, DB31, and DB32 that are not the objects of movement due to the reduction of the overlapping small area are the objects of movement. The other points are the same as in FIG. As shown in FIG. 17, the area occupied in the deformation area of the overlapping small area that is not deformed can be reduced by changing the division form of the deformation area to further subdivide the small areas in the deformation area.

  FIG. 18 is an explanatory diagram illustrating a result of the deformation process performed in the second embodiment. FIG. 18A shows the target image TI before the deformation processing in steps S140 to S160 in FIG. FIG. 18B shows the target image TI after the deformation process. Also in the second embodiment, only the non-overlapping small regions are deformed, and the overlapping small regions are not deformed. Therefore, the overlapping portions of the deformation areas TA1 and TA2 are in the same state as before the deformation process (FIG. 18A), and the discontinuous boundary line BL (FIG. 12B) generated by performing the deformation of the overlapping small area. Can be suppressed. Further, the face of the right person is narrowed by further subdividing the small area in the deformation area to reduce the overlapping small area area in the deformation area.

  Thus, in the second embodiment, when a plurality of deformation areas overlap, the area of the overlapping small areas in the deformation areas is reduced by subdividing the small areas. Therefore, the area of the non-overlapping region that is deformed in the deformation region is widened, and the influence on the deformation processing result of not deforming the overlapping small region can be further reduced. Thus, the second embodiment is preferable to the first embodiment in that the influence on the deformation processing result can be further reduced. On the other hand, the first embodiment is preferable to the second embodiment in that processing is easier.

  In the second embodiment, the sub-region is divided by subdividing the sub-region by changing the division mode. In general, if the overlapping small area can be divided, the influence on the deformation processing result can be further reduced. For example, when an overlapping small area is detected, the overlapping small area may be divided into two or more small areas. Further, the deformation area may be divided into sufficiently small small areas regardless of whether or not the deformation areas overlap. However, since the amount of deformation processing can be reduced, the deformation area is subdivided when the deformation area overlap is detected, and the deformation area is not subdivided when the deformation area overlap is not detected. Is more preferable.

C. Deformation area settings:
FIG. 19 is an explanatory diagram showing another example of the detection result of the face area FA from FIG. In the following description, it is assumed that the image TN2 (FIG. 2) including only one face is selected in the user interface for selecting an image. As shown in FIG. 19, in step S130 of FIG. 4, one face area FA is detected from the target image TI. When a plurality of face areas are detected from the target image TI, the deformation area setting process described below is performed on each detected face area. A reference line RL shown in FIG. 19 is a line that defines the height direction (vertical direction) of the face area FA and indicates the center in the width direction (horizontal direction) of the face area FA. That is, the reference line RL is a straight line that passes through the center of gravity of the rectangular face area FA and is parallel to the boundary line along the height direction (vertical direction) of the face area FA.

  FIG. 20 is a flowchart showing the flow of deformation area setting processing. The process shown in the flowchart of FIG. 20 is executed in step S500 of FIG. In step S510, the face area adjustment unit 230 (FIG. 1) adjusts the position of the face area FA detected in step S130 (FIG. 4) in the height direction. Here, the adjustment of the position of the face area FA in the height direction means that the position of the face area FA along the reference line RL (see FIG. 19) is adjusted to reset the face area FA in the target image TI. I mean.

  FIG. 21 is a flowchart showing the flow of position adjustment processing in the height direction of the face area FA. In step S511, the face area adjustment unit 230 (FIG. 1) sets the specific area SA. Here, the specific area SA is an area on the target image TI and includes an image of a predetermined reference subject that is referred to when the position adjustment of the face area FA in the height direction is executed. The reference subject can be set to, for example, “eyes”. In this case, the specific area SA is set as an area including an image of “eyes”.

  FIG. 22 is an explanatory diagram illustrating an example of the specific area SA. The face area adjustment unit 230 sets the specific area SA based on the relationship with the face area FA. Specifically, the size of the face area FA is an area having a size reduced (or enlarged) at a predetermined ratio in a direction orthogonal to the reference line RL and a direction parallel to the reference line RL. An area having a predetermined positional relationship with the position is set as the specific area SA. That is, if the specific area SA is set based on the relationship with the face area FA detected by the face area detection unit 220, the predetermined ratio or the predetermined ratio is set so that the specific area SA is an area including both eye images. The positional relationship is preset. The specific area SA is preferably set as small as possible as long as the images of both eyes are included so that an image that is confusing with the image of the eyes (for example, an image of the hair) is included as much as possible.

  As shown in FIG. 22, the specific area SA is set as a rectangular area that is symmetrical with respect to the reference line RL. The specific area SA is defined as an area on the left side (hereinafter also referred to as “left divided specific area SA (l)”) and an area on the right side (hereinafter referred to as “right divided specific area SA (r)”) by the reference line RL. Called). The specific area SA is set so that the image of one eye is included in each of the left divided specific area SA (l) and the right divided specific area SA (r).

  In step S512 (FIG. 21), the face area adjustment unit 230 (FIG. 1) calculates an evaluation value for detecting the position of the eye image in the specific area SA. FIG. 23 is an explanatory diagram illustrating an example of an evaluation value calculation method. For the calculation of the evaluation value, it is preferable to use the R value (R component value) of each pixel of the target image TI as RGB image data. This is because the difference in the R value is large between the skin image and the eye image, and thus the detection accuracy of the eye image can be improved by using the R value for calculating the evaluation value. Because it is. In addition, since the data of the target image TI is acquired as RGB data, it is possible to increase the efficiency of calculation of the evaluation value by using the R value for calculation of the evaluation value. As shown in FIG. 23, the evaluation value is calculated individually for each of the two divided specific areas (the right divided specific area SA (r) and the left divided specific area SA (l)).

  As shown in FIG. 23, the face area adjustment unit 230 includes n straight lines (right division specific area SA (r) and left division specific area SA (l)) orthogonal to the reference line RL ( (Hereinafter referred to as “target pixel specifying lines PL1 to PLn”). The target pixel specifying lines PL1 to PLn are straight lines that equally divide the height (the size along the reference line RL) of the divided specific region into (n + 1). That is, the intervals between the target pixel specifying lines PL are all equal intervals s.

  The face area adjustment unit 230 selects, for each of the target pixel specifying lines PL1 to PLn, a pixel (hereinafter referred to as “evaluation target pixel TP”) that is used to calculate an evaluation value from among pixels that form the target image TI. FIG. 24 is an explanatory diagram illustrating an example of a method for selecting the evaluation target pixel TP. The face area adjustment unit 230 selects a pixel that overlaps the target pixel specifying line PL from among the pixels constituting the target image TI as the evaluation target pixel TP. FIG. 24A shows a case where the target pixel specifying line PL is parallel to the row direction (X direction in FIG. 24) of the pixels of the target image TI. In this case, the pixel on the pixel row that overlaps with each target pixel specifying line PL (the pixel marked with a circle in FIG. 24A) is selected as the evaluation target pixel TP for each target pixel specifying line PL. .

  On the other hand, depending on the detection method of the face area FA and the setting method of the specific area SA, as shown in FIG. 24B, the target pixel specific line PL is parallel to the row direction (X direction) of the pixels of the target image TI. There may be cases where this is not possible. Even in such a case, in principle, a pixel that overlaps each target pixel specifying line PL is selected as the evaluation target pixel TP for each target pixel specifying line PL. However, for example, as in the relationship between the target pixel specifying line PL1 and the pixels PXa and PXb in FIG. 24B, a certain target pixel specifying line PL is located in the same column of the pixel matrix of the target image TI (that is, the Y coordinate). In the case where two pixels overlap with each other, the pixel having the shorter overlap distance (for example, the pixel PXb) is excluded from the evaluation target pixel TP. That is, for each target pixel specifying line PL, only one pixel is selected as the evaluation target pixel TP from one column of the pixel matrix.

  When the inclination of the target pixel specifying line PL exceeds 45 degrees with respect to the X direction, the relationship between the column and the row of the pixel matrix is reversed in the above description, and one pixel from one row of the pixel matrix is reversed. Only the pixel to be evaluated TP is selected. Further, depending on the size relationship between the target image TI and the specific area SA, one pixel may be selected as the evaluation target pixel TP for a plurality of target pixel specific lines PL.

  The face area adjustment unit 230 calculates an average value of R values of the evaluation target pixels TP as an evaluation value for each of the target pixel specifying lines PL. However, for each target pixel specifying line PL, out of a plurality of selected evaluation target pixels TP, some pixels having a large R value are excluded from the evaluation value calculation target. Specifically, for example, when k evaluation target pixels TP are selected for a certain target pixel specifying line PL, the evaluation target pixel TP includes a 0.75k pixel having a relatively large R value. An average value of R values as an evaluation value is calculated only for pixels that are divided into two groups, one group and a second group composed of 0.25k pixels having a relatively small R value. It becomes a target. The reason why some of the evaluation target pixels TP are excluded from the evaluation value calculation target will be described later.

  As described above, the face area adjustment unit 230 calculates an evaluation value for each target pixel specifying line PL. Here, since the target pixel specifying line PL is a straight line orthogonal to the reference line RL, it can be expressed that the evaluation value is calculated for a plurality of positions (evaluation positions) along the reference line RL. In addition, the evaluation value can be expressed as a value representing the feature of the distribution of pixel values along the direction orthogonal to the reference line RL for each evaluation position.

  In step S513 (FIG. 21), the face area adjustment unit 230 (FIG. 1) detects the position of the eye in the specific area SA, and determines the height reference point Rh based on the detection result. First, as shown on the right side of FIG. 23, the face area adjustment unit 230 creates a curve representing the distribution of evaluation values (average values of R values) along the reference line RL for each divided specific area, and the evaluation values A position along the reference line RL direction at which is a minimum value is detected as the eye position Eh. The eye position Eh in the left divided specific area SA (l) is represented as Eh (l), and the eye position Eh in the right divided specific area SA (r) is represented as Eh (r).

  In the case of the yellow race, the portion representing the skin image in the divided specific region has a large R value, while the portion representing the image of the eye (more specifically, the black eye portion at the center of the eye) has a small R value. . Therefore, as described above, the position along the reference line RL where the evaluation value (average value of R values) takes the minimum value can be determined as the eye position Eh. However, when other races (white race or black race) are targeted, other evaluation values (for example, luminance, brightness, B value) are used.

  As shown in FIG. 23, the divided specific region may include other images having a small R value (for example, images of eyebrows and hairs) in addition to the eye image. Therefore, when the curve representing the distribution of evaluation values along the reference line RL has a plurality of minimum values, the face area adjustment unit 230 determines the lowest position among the positions where the minimum values are taken as the eye position. Judge as Eh. In general, an image with a small R value, such as eyebrows or hair, is often located above the eye image, while an image with a small R value is less likely to be located below the eye image. Therefore, such a determination becomes possible.

  Even if the curve is below the position of the eye image (mainly the position corresponding to the image of the skin), the evaluation value is large, but may have a minimum value. Of these, those larger than a predetermined threshold may be ignored. Alternatively, the position of the target pixel specifying line PL corresponding to the minimum value among the evaluation values calculated for each target pixel specifying line PL may be simply set as the eye position Eh.

  Note that, as a minimum subject for position adjustment of the face area FA, an eye (a black eye portion at the center of the eye), which is a part of the face that is considered to have a relatively large color difference from the surroundings, is used. However, since the average value of the R values as the evaluation values is calculated for a plurality of evaluation target pixels TP on the target pixel specifying line PL, for example, due to the influence of the image of the white part of the periphery of the black eye, the black eye part There is a fear that the accuracy of detection will be reduced. Therefore, as described above, some evaluation target pixels TP that are considered to have a large color difference from the reference subject (for example, pixels having a relatively large R value belonging to the first group described above) are to be evaluated value calculation targets. Therefore, the reference subject detection accuracy is further improved.

  Next, the face area adjustment unit 230 determines a height reference point Rh based on the detected eye position Eh. FIG. 25 is an explanatory diagram illustrating an example of a method for determining the height reference point Rh. The height reference point Rh is a point used as a reference when adjusting the position of the face area FA in the height direction. As the height reference point Rh, as shown in FIG. 25, a point on the reference line RL located between the positions Eh (l) and Eh (r) of the two left and right eyes is set. That is, the intersection of the straight line EhL (l) indicating the left eye position Eh (l) and the reference line RL, and the intersection of the straight line EhL (r) indicating the right eye position Eh (r) and the reference line RL. The midpoint is set as the height reference point Rh.

  Note that the face area adjustment unit 230 calculates an approximate inclination angle of the face image (hereinafter referred to as “approximate inclination angle RI”) based on the detected eye position Eh. The approximate inclination angle RI of the face image is an angle obtained by estimating how much the face image in the target image TI is inclined with respect to the reference line RL of the face area FA. FIG. 26 is an explanatory diagram showing an example of a method for calculating the approximate inclination angle RI. As shown in FIG. 26, the face area adjustment unit 230 first sets an intersection IP (l) between a straight line and a straight line EhL (l) that divides the width Ws (l) of the left divided specific area SA (l) in half. Then, the straight line that divides the width Ws (r) of the right division specific area SA (r) in half and the intersection IP (r) of the straight line EhL (r) are determined. Then, an angle formed by the straight line IL orthogonal to the straight line connecting the intersection point IP (l) and the intersection point IP (r) and the reference line RL is calculated as the approximate inclination angle RI.

  In step S514 (FIG. 21), the face area adjustment unit 230 (FIG. 1) adjusts the position of the face area FA in the height direction. FIG. 27 is an explanatory diagram showing an example of a method for adjusting the position of the face area FA in the height direction. The position adjustment of the face area FA in the height direction is performed by resetting the face area FA so that the height reference point Rh is positioned at a predetermined position in the face area FA after the position adjustment. Specifically, as shown in FIG. 27, the face area FA is such that the height reference point Rh is located at a position where the height Hf of the face area FA is divided by a predetermined ratio r1 to r2. Is vertically adjusted along the reference line RL. In the example of FIG. 27, the face area FA after adjustment indicated by the solid line is reset by moving the face area FA before adjustment indicated by the broken line upward.

  After the position adjustment of the face area FA, in step S520 (FIG. 20), the face area adjustment unit 230 (FIG. 1) performs inclination adjustment (angle adjustment) of the face area FA. Here, the tilt adjustment of the face area FA means that the face area FA is adjusted by adjusting the tilt of the face area FA in the target image TI to match the tilt of the face image, and the face area FA is reset. The predetermined reference subject to be referred to when the inclination adjustment of the face area FA is executed is set to “both eyes”, for example. In the inclination adjustment of the face area FA, a plurality of evaluation directions representing options of adjustment angles for inclination adjustment are set, and an evaluation specific area ESA corresponding to each evaluation direction is set as an area including images of both eyes. Then, an evaluation value is calculated based on the pixel value of the image in the evaluation specific area ESA for each evaluation direction, and the inclination of the face area FA is adjusted using the adjustment angle of the inclination adjustment determined based on the evaluation value.

  FIG. 28 is a flowchart showing the flow of the inclination adjustment process of the face area FA. FIG. 29 is an explanatory diagram showing an example of an evaluation value calculation method for adjusting the inclination of the face area FA. In step S521 (FIG. 28), the face area adjustment unit 230 (FIG. 1) sets an initial evaluation specific area ESA (0). The initial evaluation specific area ESA (0) is an evaluation specific area ESA associated with a direction (hereinafter also referred to as “initial evaluation direction”) parallel to the reference line RL (see FIG. 27) after the position adjustment of the face area FA. is there. The specific area SA (see FIG. 27) corresponding to the face area FA after the position adjustment is set as the initial evaluation specific area ESA (0) as it is. Note that the evaluation specific area ESA in the adjustment of the inclination of the face area FA is not divided into two areas on the left and right, unlike the specific area SA in the position adjustment of the face area FA. 29 shows the set initial evaluation specific area ESA (0).

  In step S522 (FIG. 28), the face area adjustment unit 230 (FIG. 1) sets a plurality of evaluation directions and evaluation specific areas ESA corresponding to the respective evaluation directions. The plurality of evaluation directions are set as directions representing options of adjustment angles for tilt adjustment. Specifically, a plurality of evaluation direction lines EL whose angles with the reference line RL are within a predetermined range are set, and a direction parallel to the evaluation direction line EL is set as the evaluation direction. As shown in FIG. 29, a straight line determined by rotating the reference line RL counterclockwise and clockwise around the center point (center of gravity) CP of the initial evaluation specific area ESA (0) at a predetermined angle α, It is set as a plurality of evaluation direction lines EL. Note that the evaluation direction line EL whose angle with the reference line RL is φ degrees is represented as EL (φ).

  The predetermined range about the angle formed by each evaluation direction line EL and the reference line RL described above is set to ± 20 degrees. Here, in this specification, the rotation angle when the reference line RL is rotated clockwise is represented by a positive value, and the rotation angle when the reference line RL is rotated counterclockwise is represented by a negative value. Is done. The face area adjustment unit 230 rotates the reference line RL counterclockwise and clockwise while increasing the rotation angle within a range not exceeding α degrees, 2α degrees,..., 20 degrees, and a plurality of evaluation direction lines EL. Set. FIG. 29 shows evaluation direction lines EL (EL (−α), EL (−2α), EL (α)) determined by rotating the reference line RL by −α degrees, −2α degrees, and α degrees, respectively. ing. The reference line RL can also be expressed as an evaluation direction line EL (0).

  The evaluation specific area ESA corresponding to the evaluation direction line EL representing each evaluation direction rotates the initial evaluation specific area ESA (0) around the center point CP at the same angle as the rotation angle when setting the evaluation direction line EL. This is the area that was The evaluation specific area ESA corresponding to the evaluation direction line EL (φ) is represented as the evaluation specific area ESA (φ). In FIG. 29, evaluation specific areas ESA (ESA (−α), ESA (−2α), ESA (α) corresponding to the evaluation direction lines EL (−α), EL (−2α), and EL (α), respectively. )It is shown. Note that the initial evaluation specific area ESA (0) is also treated as one of the evaluation specific areas ESA.

  In step S523 (FIG. 28), the face area adjustment unit 230 (FIG. 1) calculates an evaluation value for each of the set plurality of evaluation directions based on the pixel value of the image of the evaluation specific area ESA. As the evaluation value in the inclination adjustment of the face area FA, the average value of the R values is used in the same manner as the evaluation value in the position adjustment of the face area FA described above. The face area adjustment unit 230 calculates evaluation values for a plurality of evaluation positions along the evaluation direction.

  The evaluation value calculation method is the same as the evaluation value calculation method in the position adjustment of the face area FA described above. That is, as shown in FIG. 29, the face area adjustment unit 230 sets target pixel specifying lines PL1 to PLn orthogonal to the evaluation direction line EL in each evaluation specifying area ESA, and sets the target pixel specifying lines PL1 to PLn. The evaluation target pixel TP is selected for and the average value of the R values of the selected evaluation target pixel TP is calculated as the evaluation value.

  The setting method of the target pixel specifying line PL and the selection method of the evaluation target pixel TP in the evaluation specific area ESA are different depending on whether the area is divided into right and left, but the face area FA shown in FIGS. This is the same as the method for position adjustment. As in the position adjustment of the face area FA, a part of the selected evaluation target pixels TP (for example, 0.75k pixels having a relatively large R value among the k evaluation target pixels TP). May be excluded from the evaluation value calculation target. The right side of FIG. 29 shows the distribution of the calculated evaluation values along the evaluation direction line EL for each evaluation direction.

  Since the target pixel specifying line PL is a straight line orthogonal to the evaluation direction line EL, it can be expressed that the evaluation value is calculated for a plurality of positions (evaluation positions) along the evaluation direction line EL. In addition, the evaluation value can be expressed as a value representing the feature of the distribution of pixel values along the direction orthogonal to the evaluation direction line EL for each evaluation position.

  In step S524 (FIG. 28), the face area adjustment unit 230 (FIG. 1) determines an adjustment angle used for adjusting the inclination of the face area FA. The face area adjustment unit 230 calculates the variance along the evaluation direction line EL of the evaluation value calculated in step S523 for each evaluation direction, and selects the evaluation direction that maximizes the variance value. Then, an angle formed by the evaluation direction line EL corresponding to the selected evaluation direction and the reference line RL is determined as an adjustment angle used for tilt adjustment.

  FIG. 30 is an explanatory diagram illustrating an example of a calculation result of evaluation value dispersion for each evaluation direction. In the example of FIG. 30, the variance takes the maximum value Vmax in the evaluation direction where the rotation angle is −α degrees. Therefore, a rotation angle of −α degrees, that is, α degrees counterclockwise is determined as an adjustment angle used for adjusting the inclination of the face area FA.

  The reason why the angle corresponding to the evaluation direction when the variance of the evaluation values is maximized is determined as the adjustment angle used for the inclination adjustment will be described. As shown in the second row from the top in FIG. 29, in the evaluation specific area ESA (−α) when the rotation angle is −α degrees, the image of the center portion (black-eye portion) of the left and right eyes is substantially the target pixel. The arrangement is arranged in a direction parallel to the specific line PL (that is, a direction orthogonal to the evaluation direction line EL). At this time, the left and right eyebrows are similarly arranged in a direction substantially orthogonal to the evaluation direction line EL. Therefore, the evaluation direction corresponding to the evaluation direction line EL at this time is considered to be a direction that generally represents the inclination of the face image. At this time, the positional relationship between the image of the eye or eyebrow generally having a small R value and the image of the skin portion generally having a large R value is a small positional relationship of the overlapping portion along the direction of the target pixel specifying line PL. . For this reason, the evaluation value at the position of the image of the eyes and eyebrows is relatively small, and the evaluation value at the position of the image of the skin portion is relatively large. Therefore, as shown in FIG. 29, the distribution of evaluation values along the evaluation direction line EL is a distribution with relatively large variation (amplitude is large), and the variance value is large.

  On the other hand, as shown in the uppermost stage, the third stage, and the fourth stage in FIG. 29, the evaluation specific areas ESA (0), ESA (-2α) when the rotation angles are 0 degree, −2α degree, and α degree. , ESA (α), the center portions of the left and right eyes and the images of the left and right eyebrows are not arranged in a direction perpendicular to the evaluation direction line EL, but are shifted. Therefore, the evaluation direction corresponding to the evaluation direction line EL at this time does not represent the inclination of the face image. At this time, the positional relationship between the image of the eyes and eyebrows and the image of the skin portion is a large positional relationship of the portion where both overlap along the direction of the target pixel specifying line PL. Therefore, the distribution of evaluation values along the evaluation direction line EL is a distribution with relatively small variation (small amplitude) as shown in FIG. 29, and the value of variance is small.

  As described above, when the evaluation direction is close to the inclination direction of the face image, the evaluation value variance along the evaluation direction line EL is large, and the evaluation direction is far from the inclination direction of the face image. In this case, the variance of the evaluation values along the evaluation direction line EL becomes small. Therefore, if the angle corresponding to the evaluation direction when the variance of the evaluation values is maximized is determined as the adjustment angle used for the inclination adjustment, the face area in which the inclination of the face area FA matches the inclination of the face image. FA tilt adjustment can be realized.

  In addition, when the calculation result of the variance of the evaluation values is a critical value in the angle range, that is, the maximum value at −20 degrees or 20 degrees, the face inclination is not accurately evaluated. Since the possibility is high, the inclination of the face area FA is not adjusted.

  Further, the determined adjustment angle is compared with the approximate inclination angle RI calculated at the time of adjusting the position of the face area FA described above. If the difference between the adjustment angle and the approximate inclination angle RI is larger than a predetermined threshold value, it is considered that some error has occurred during the evaluation and determination in the position adjustment and inclination adjustment of the face area FA. Position adjustment and tilt adjustment are not performed.

  In step S525 (FIG. 28), the face area adjustment unit 230 (FIG. 1) adjusts the inclination of the face area FA. FIG. 31 is an explanatory diagram showing an example of a method for adjusting the inclination of the face area FA. The inclination adjustment of the face area FA is performed by rotating the face area FA about the center point CP of the initial evaluation specific area ESA (0) by the adjustment angle determined in step S524. In the example of FIG. 31, the adjusted face area FA indicated by the solid line is set by rotating the face area FA before adjustment indicated by the broken line by α degrees counterclockwise.

  In step S530 (FIG. 20) after completion of the inclination adjustment of the face area FA, the deformation area setting unit 240 (FIG. 1) sets the deformation area TA. The deformation area TA is an area on the target image TI and is an area to be subjected to image deformation processing for face shape correction. FIG. 32 is an explanatory diagram showing an example of a method for setting the deformation area TA. As shown in FIG. 32, the deformation area TA is set as an area in which the face area FA is expanded (or shortened) in a direction parallel to the reference line RL (height direction) and in a direction perpendicular to the reference line RL (width direction). Is done. Specifically, assuming that the size in the height direction of the face area FA is Hf and the size in the width direction is Wf, the face area FA is extended by k1 · Hf in the upward direction and k2 · Hf in the downward direction, A region extended by k3 · Wf to the left and right is set as the deformation region TA. Note that k1, k2, and k3 are predetermined coefficients.

  When the deformation area TA is set in this way, the reference line RL, which is a straight line parallel to the contour line in the height direction of the face area FA, becomes a straight line parallel to the contour line in the height direction of the deformation area TA. . The reference line RL is a straight line that divides the width of the deformation area TA in half.

  As shown in FIG. 32, the deformation area TA is set as an area that generally includes an image from the jaw to the forehead in the height direction and includes images of the left and right cheeks in the width direction. That is, the above-described coefficients k1, k2, and k3 are set in advance based on the relationship with the size of the face area FA so that the deformation area TA is an area that includes an image in such a range.

D. Division point arrangement:
FIG. 33 is an explanatory diagram showing an example of a method of dividing the deformation area TA into small areas. The deformation area dividing unit 250 arranges a plurality of division points D in the deformation area TA, and divides the deformation area TA into a plurality of small areas using a straight line connecting the division points D.

  The arrangement mode of the dividing points D (the number and positions of the dividing points D) is defined in association with the deformation type set in step S120 (FIG. 4) by the dividing point arrangement pattern table 410 (FIG. 1). . The deformation area dividing unit 250 refers to the dividing point arrangement pattern table 410 and arranges the dividing points D in a manner associated with the deformation type set in step S120. As described above, when the deformation “type A” (see FIG. 5) for sharpening the face is set as the deformation type, the division point D is arranged in a manner associated with the deformation type. The

  As shown in FIG. 33, the dividing points D are arranged at the intersections of the horizontal dividing line Lh and the vertical dividing line Lv and the intersections of the horizontal dividing line Lh and the vertical dividing line Lv and the outer frame of the deformation area TA. . Here, the horizontal dividing line Lh and the vertical dividing line Lv are reference lines for arranging the dividing points D in the deformation area TA. As shown in FIG. 33, in the arrangement of the dividing points D associated with the deformation type for sharpening the face, two horizontal dividing lines Lh orthogonal to the reference line RL and 4 parallel to the reference line RL are used. A vertical division line Lv is set. The two horizontal dividing lines Lh are called Lh1 and Lh2 in order from the bottom of the deformation area TA. The four vertical dividing lines Lv are referred to as Lv1, Lv2, Lv3, and Lv4 in order from the left of the deformation area TA.

  The horizontal dividing line Lh1 is arranged below the chin image in the deformation area TA, and the horizontal dividing line Lh2 is arranged near the eye image. The vertical dividing lines Lv1 and Lv4 are arranged outside the cheek line image, and the vertical dividing lines Lv2 and Lv3 are arranged outside the eye corner image. The horizontal dividing line Lh and the vertical dividing line Lv are arranged in the deformation area TA set in advance so that the positional relationship between the horizontal dividing line Lh and the vertical dividing line Lv and the image becomes the above-described positional relationship as a result. It is executed according to the correspondence with the size.

  According to the arrangement of the horizontal dividing line Lh and the vertical dividing line Lv described above, the intersection of the horizontal dividing line Lh and the vertical dividing line Lv, and the intersection of the horizontal dividing line Lh and the vertical dividing line Lv and the outer frame of the deformation area TA In addition, the dividing point D is arranged. As shown in FIG. 33, division points D located on the horizontal division line Lhi (i = 1 or 2) are referred to as D0i, D1i, D2i, D3i, D4i, and D5i in order from the left. For example, the dividing points D located on the horizontal dividing line Lh1 are called D01, D11, D21, D31, D41, D51. Similarly, the dividing points D located on the vertical dividing line Lvj (j = 1, 2, 3, 4) are called Dj0, Dj1, Dj2, Dj3 in order from the bottom. For example, the division points D located on the vertical division line Lv1 are called D10, D11, D12, and D13.

  As shown in FIG. 33, the arrangement of the dividing points D in this embodiment is symmetrical with respect to the reference line RL.

  The deformation area dividing unit 250 divides the deformation area TA into a plurality of small areas by a straight line connecting the arranged dividing points D (that is, the horizontal dividing line Lh and the vertical dividing line Lv). In the example of FIG. 33, the deformation area TA is divided into 15 rectangular small areas.

  Since the arrangement of the dividing points D is determined by the numbers and positions of the horizontal dividing lines Lh and the vertical dividing lines Lv, the dividing point arrangement pattern table 410 defines the numbers and positions of the horizontal dividing lines Lh and the vertical dividing lines Lv. It can be paraphrased as being.

E. Small area transformation:
For each small area obtained by dividing the deformation area TA by arranging the division point D in the deformation area TA, the division area deformation unit 260 (FIG. 1) moves the position of the division point D arranged in the deformation area TA. It is deformed by doing.

  The movement mode (movement direction and movement distance) of the position of each division point D for the deformation process is determined by the division type and the degree of deformation set in step S120 (FIG. 4) by the division point movement table 420 (FIG. 1). Are determined in advance in association with the combination. The divided region deformation unit 260 refers to the divided point movement table 420 and moves the position of the divided point D with the moving direction and moving distance associated with the combination of the deformation type and the degree of deformation set in step S120. To do.

  As described above, when the deformation “type A” (see FIG. 5) for sharpening the face is set as the deformation type and the degree of “medium” is set as the deformation degree, these deformations are performed. The position of the dividing point D is moved with the movement direction and the movement distance associated with the combination of the type and the degree of deformation.

  FIG. 34 is an explanatory diagram showing an example of the contents of the dividing point movement table 420. FIG. 35 is an explanatory diagram showing an example of the movement of the position of the dividing point D according to the dividing point movement table 420. In FIG. 34, among the movement modes of the position of the dividing point D defined by the dividing point movement table 420, the deformation type for sharpening the face and the combination of the degree of deformation of the degree “medium” are associated. The movement mode is shown. As shown in FIG. 34, in the dividing point movement table 420, for each dividing point D, there is a moving amount along a direction (H direction) orthogonal to the reference line RL and a direction parallel to the reference line RL (V direction). It is shown. Note that the unit of movement amount shown in the dividing point movement table 420 is the pixel pitch PP of the target image TI. For the H direction, the amount of movement to the right side is represented as a positive value, the amount of movement to the left side is represented as a negative value, and for the V direction, the amount of movement upward is positive. It is expressed as a value, and the downward movement amount is expressed as a negative value. For example, the dividing point D11 is moved to the right along the H direction by a distance that is seven times the pixel pitch PP, and is moved upward along the V direction by a distance that is 14 times the pixel pitch PP. For example, the division point D22 is not moved because the movement amount is zero in both the H direction and the V direction.

  Note that the position of the dividing point D (for example, the dividing point D10 shown in FIG. 35) located on the outer frame of the deformation area TA is not moved so that the boundary between the images inside and outside the deformation area TA does not become unnatural. Therefore, in the dividing point movement table 420 shown in FIG. 34, the movement mode for the dividing point D located on the outer frame of the deformation area TA is not defined.

  In FIG. 35, the division point D before the movement is indicated by a white circle, and the division point D after the movement or the division point D without the movement of the position is indicated by a black circle. The divided point D after the movement is called a divided point D ′. For example, the position of the dividing point D11 is moved in the upper right direction in FIG. 35 and becomes the dividing point D′ 11.

  It should be noted that all of the combinations of the two division points D (for example, combinations of the division points D11 and D41) that have a symmetric positional relationship with respect to the reference line RL are all relative to the reference line RL after the division point D is moved. The movement mode is determined so as to maintain a symmetrical positional relationship.

  For each small area constituting the deformation area TA, the divided area deforming unit 260 is an image of a small area newly defined by moving the position of the dividing point D. The image is deformed so that For example, in FIG. 35, an image of a small region (small region indicated by hatching) having vertices at division points D11, D21, D22, and D12 is divided into division points D′ 11, D′ 21, D22, and D′ 12. Is transformed into an image of a small area with the vertex at.

  Note that when a small area is excluded from the deformation target as described above, the movement distance of the dividing point corresponding to the vertex of the small area is set to zero. As a result, the small area excluded from the deformation target is not deformed. For example, in the case where small areas having the vertices at the dividing points D11, D21, D22, and D12 that are hatched in FIG. 35 are excluded from the deformation target, the dividing points D11, D21, The movement amounts of D22 and D12 in the H direction and the V direction are set to zero.

  FIG. 36 is an explanatory diagram showing the concept of the image deformation processing method performed by the divided region deformation unit 260. In FIG. 36, the division point D is indicated by a black circle. In FIG. 36, for simplification of description, for the four small regions, the state before the position movement of the dividing point D is shown on the left side, and the state after the position moving of the dividing point D is shown on the right side. In the example of FIG. 36, the center dividing point Da is moved to the position of the dividing point Da ′, and the positions of the other dividing points D are not moved. Thereby, for example, an image of a rectangular small area (hereinafter also referred to as “pre-deformation noticeable small area BSA”) having the vertices at the division points Da, Db, Dc, Dd before the movement of the division point D is obtained from the division point Da ′. , Db, Dc, and Dd are transformed into an image of a rectangular small area (hereinafter also referred to as “the noticed small area ASA after deformation”).

  The image deformation process is performed in units of triangular areas by dividing a rectangular small area into four triangular areas using the center of gravity CG of the small area. In the example of FIG. 36, the pre-deformation attention small area BSA is divided into four triangular areas having the centroid CG of the pre-deformation attention small area BSA as one vertex. Similarly, the post-deformation attention small area ASA is divided into four triangular areas having the centroid CG ′ of the post-deformation attention small area ASA as one vertex. Then, image deformation processing is performed for each corresponding triangular area in each state before and after the movement of the dividing point Da. For example, an image of a triangular area having vertices at the division points Da and Dd and the center of gravity CG in the attention small area BSA before deformation has a vertex at the division points Da ′ and Dd and the center of gravity CG ′ in the attention small area ASA after deformation. It is transformed into an image of a triangular area.

  FIG. 37 is an explanatory diagram showing the concept of an image deformation processing method in a triangular area. In the example of FIG. 37, the image of the triangular area stu having points s, t, and u as vertices is transformed into the image of a triangular area s′t′u ′ having vertices as points s ′, t ′, u ′. . For the deformation of the image, the position of a certain pixel in the image of the triangular area s't'u 'after the deformation corresponds to the position in the image of the triangular area stu before the deformation, and the calculated position The pixel value in the image before deformation in (i.e., the original image) is used as the pixel value of the image after deformation.

  For example, in FIG. 37, the position of the pixel of interest p ′ in the image of the triangular area s′t′u ′ after deformation corresponds to the position p in the image of the triangular area stu before deformation. The position p is calculated as follows. First, coefficients m1 and m2 for expressing the position of the pixel of interest p ′ as a sum of a vector s′t ′ and a vector s′u ′ as shown in the following equation (1) are calculated.

  Next, by using the calculated coefficients m1 and m2, the position p is obtained by calculating the sum of the vector st and the vector su in the triangular area stu before deformation by the following equation (2).

  When the position p in the triangular area stu before deformation coincides with the pixel center position of the image before deformation, the pixel value of the pixel is set as the pixel value of the image after deformation. On the other hand, when the position p in the triangular area stu before deformation is shifted from the pixel center position of the image before deformation, an interpolation operation such as bicubic using the pixel values of the pixels around the position p. Thus, the pixel value at the position p is calculated, and the calculated pixel value is set as the pixel value of the image after deformation.

  Image deformation from the image of the triangular area stu to the image of the triangular area s't'u 'by calculating the pixel value for each pixel in the image of the triangular area s't'u' after the deformation as described above Processing can be performed. The divided area deformation unit 260 performs a deformation process by defining a triangular area as described above for each small area constituting the deformation area TA shown in FIG. 35, and performs an image deformation process in the deformation area TA.

  Here, a case where the deformation “type A” (see FIG. 5) for sharpening the face is set as the deformation type and the degree of “medium” is set as the deformation degree is taken as an example. An aspect is demonstrated in detail. FIG. 38 is an explanatory diagram showing a form of face shape correction in this case. In FIG. 38, the image of the deformation | transformation aspect of each small area | region which comprises deformation | transformation area | region TA is shown with the arrow.

  In the face shape correction shown in the example of FIG. 38, the position of the dividing point D (D11, D21, D31, D41) arranged on the horizontal dividing line Lh1 is upward in the direction (V direction) parallel to the reference line RL. On the other hand, the position of the dividing point D (D12, D22, D32, D42) arranged on the horizontal dividing line Lh2 is not moved (see FIG. 34). Therefore, the image located between the horizontal dividing line Lh1 and the horizontal dividing line Lh2 is reduced in the V direction. As described above, since the horizontal dividing line Lh1 is disposed below the jaw image and the horizontal dividing line Lh2 is disposed near the lower part of the eye image, in this face shape correction, in the face image, the jaw The image of the part from the eye to the bottom of the eye is reduced in the V direction. As a result, the jaw line in the image moves upward.

  On the other hand, regarding the direction (H direction) orthogonal to the reference line RL, the position of the dividing point D (D11, D12) arranged on the vertical dividing line Lv1 is moved rightward and arranged on the vertical dividing line Lv4. The position of the dividing point D (D41, D42) is moved to the left (see FIG. 34). Further, of the two division points D arranged on the vertical division line Lv2, the position of the division point D (D21) arranged on the horizontal division line Lh1 is moved rightward and arranged on the vertical division line Lv3. Of the two divided points D, the position of the divided point D (D31) arranged on the horizontal dividing line Lh1 is moved to the left (see FIG. 34). Therefore, the image located on the left side of the vertical dividing line Lv1 is enlarged on the right side in the H direction, and the image located on the right side of the vertical dividing line Lv4 is enlarged on the left side. An image located between the vertical dividing line Lv1 and the vertical dividing line Lv2 is reduced or moved to the right in the H direction, and an image located between the vertical dividing line Lv3 and the vertical dividing line Lv4 is moved in the H direction. Is reduced or moved to the left. Further, the image located between the vertical division line Lv2 and the vertical division line Lv3 is reduced in the H direction with the position of the horizontal division line Lh1 as the center.

  As described above, the vertical division lines Lv1 and Lv4 are arranged outside the cheek line image, and the vertical division lines Lv2 and Lv3 are arranged outside the corner image. Therefore, in the face shape correction in the example of FIG. 38, the image of the portion outside the both corners of the face image is reduced in the H direction as a whole. In particular, the reduction rate is high near the jaw. As a result, the shape of the face in the image becomes thinner in the width direction as a whole.

  When the deformation modes in the H direction and the V direction described above are combined, the face shape in the target image TI is sharpened by the face shape correction shown in the example of FIG. Note that a sharp face shape can be expressed as a so-called “small face”.

  Note that the small areas (hatched areas) whose vertices are the dividing points D22, D32, D33, and D23 shown in FIG. 38 are determined according to the arrangement method of the horizontal dividing lines Lh2 and the vertical dividing lines Lv2 and Lv3. This area includes the image. As shown in FIG. 34, since the division points D22 and D32 are not moved in the H direction or the V direction, the small area including the images of both eyes is not deformed. In this way, in the example of FIG. 38, the small region including the images of both eyes is not deformed, and the image after the face shape correction is made more natural and preferable.

F. Variations:
The present invention is not limited to the above-described examples and embodiments, and can be implemented in various modes without departing from the gist thereof. For example, the following modifications are possible.

F1. Modification 1:
In each of the above embodiments, in order to prevent the image after the deformation process from becoming an unnatural image, it is assumed that the deformation of the overlapping small area that overlaps the overlapping area where the plurality of deformation areas overlap is not performed. It suffices if the deformation amount of the overlapping small area can be reduced. Even in this case, the image shift at the outer periphery of the overlapping region can be reduced, so that the image after the deformation process can be prevented from being an unnatural image.

F2. Modification 2:
In each of the above embodiments, whether or not to deform each small region obtained by dividing the deformation region is determined, but it is also possible to reduce the amount of deformation of a part of the deformation region including the overlapping region. For example, it is good also as what suppresses the movement of the dividing point which enters into an overlapping area among the dividing points used for a division | segmentation of a deformation | transformation area | region. Even in this case, since the deformation amount of the overlapping region is reduced, the image shift at the outer periphery of the overlapping region can be reduced, and the image after the deformation process can be prevented from being an unnatural image.

F3. Modification 3:
In each of the embodiments described above, the present invention is applied to the deformation process for correcting the shape of the face in the target image. However, the present invention can be applied to a case where the deformation area to be deformed can overlap in addition to the face deformation process. Generally applicable.

F4. Modification 4:
In each of the above embodiments, the deformation area is set as a rectangular area, but the shape of the deformation area may be another shape (for example, an ellipse or a rhombus).

F5. Modification 5:
In each of the above-described embodiments, the face shape correction printing process (FIG. 3) by the printer 100 as the image processing apparatus has been described. May be executed by the personal computer, and only the printing process (step S300) may be executed by the printer. The printer 100 is not limited to an ink jet printer, and may be another type of printer, such as a laser printer or a sublimation printer.

F6. Modification 6:
In each of the above embodiments, a part of the configuration realized by hardware may be replaced with software, and conversely, a part of the configuration realized by software may be replaced by hardware. .

100 ... Printer 110 ... CPU
DESCRIPTION OF SYMBOLS 120 ... Internal memory 140 ... Operation part 150 ... Display part 160 ... Printer engine 170 ... Card interface 172 ... Card slot 200 ... Face shape correction part 210 ... Deformation mode setting part 212 ... Specification acquisition part 220 ... Face area detection part 230 ... Face Area adjustment unit 240 ... deformation area setting part 250 ... deformation area division part 260 ... divided area deformation part 270 ... overlapping small area detection part 280 ... area overlap detection part 290 ... division form change part 310 ... display processing part 320 ... print processing part 410: Division point arrangement pattern table 420 ... Division point movement table

Claims (6)

An image processing apparatus,
A deformation area setting unit that analyzes a target image and sets a plurality of deformation areas on the target image;
A deformation processing unit that performs deformation of an image in the deformation area;
With
The deformation processing unit reduces a deformation amount of a partial region of each of the plurality of deformation regions including an overlapping portion of the plurality of deformation regions when the plurality of deformation regions overlap;
Image processing device. The image processing apparatus according to claim 1,
The deformation processing unit performs deformation of the image in the deformation area by deforming a small area obtained by dividing the deformation area into a plurality of areas,
The partial area is the whole or a part of the plurality of small areas overlapping the overlapping part,
Image processing device. The image processing apparatus according to claim 2,
The image processing apparatus, wherein the partial area includes a partial area obtained by further dividing a small area overlapping the overlapping part. The image processing apparatus according to any one of claims 1 to 3,
The deformation processing unit is an image processing device that sets a deformation amount of the partial region to zero. The image processing apparatus according to any one of claims 1 to 4,
The target image is an image including a human face,
The deformation area setting unit sets an area including images of a plurality of organs of the person's face as the deformation area.
Image processing device. An image processing method comprising:
(A) analyzing a target image and setting a plurality of deformation regions on the target image;
(B) a step of deforming the image in the deformation region;
With
The step (b) includes a step of reducing a deformation amount of a partial region of each of the plurality of deformation regions including an overlapping portion of the plurality of deformation regions when the plurality of deformation regions overlap. ,
Image processing method.

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