Information processing device and program

Abstract

To correct one image including two or more objects to obtain uniformity in image quality between a plurality of images.SOLUTION: An information processing apparatus comprises a processor, and the processor acquires a plurality of images each including any of a plurality of objects, and based on a result of analysis of the plurality of objects in the plurality of images, determines one of two or more objects of the plurality of objects suitable for correction of one image including the two or more objects.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an information processing device and a program. [Background technology]

[0002] Patent document 1 describes a data correction device in which an image recognition unit recognizes images in a page represented by page description data, a natural image discrimination unit determines whether each recognized image is a natural image or not, an image analysis unit calculates setup conditions for image correction processing on the natural images, a second correction condition calculation unit calculates correction conditions for making image quality approximately constant for similar natural images that are similar to each other, and an image correction unit applies image correction processing to the similar natural images based on the setup conditions and correction conditions.

[0003] Patent document 2 describes an image processing device that, upon receiving image data, analyzes the image data to identify the subject being photographed and classify it into multiple categories, and when correcting the image data, determines the correction content based on this category and the category of previously printed image data, and performs the correction process. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2008-35010 A [Patent Document 2] JP 2008-54164 A Summary of the Invention [Problem to be solved by the invention]

[0005] When it is desired to correct one image so as to obtain a sense of uniformity in image quality among a plurality of images, there are cases where the one image contains two or more objects. In such a case, if a configuration is adopted in which the one image is corrected to match both of the two or more objects, it is not possible to correct the one image so as to obtain a sense of uniformity in image quality among the plurality of images.

[0006] It is an object of the present invention to be able to correct an image containing two or more objects so as to obtain a sense of uniformity in image quality among the multiple images. [Means for solving the problem]

[0007] The invention described in claim 1 includes a processor, and the processor is configured to generate a plurality of images each including any one of a plurality of objects. From a printed manuscript including the Get The above An image containing two or more objects among the plurality of objects When the number of images including a specific object among the two or more objects in the plurality of images is equal to or greater than a threshold, the specific object is Correct according to thing The information processing device is characterized by determining Claim 2 The invention described in is characterized in that the one image is included in the plurality of images acquired from the document. Claim 1 The present invention relates to an information processing device. Claim 3 The invention described in is, When the number of images including a first object and the number of images including a second object among the two or more objects in the plurality of images are equal, The above Manuscript The first object in a part of The number of images containing The second object in question If it is greater than the number of images containing The first image is then To Correct according to thing determining Claim 1 The present invention relates to an information processing device. Claim 4 The invention described in is an information processing device as described in claim 1, characterized in that the processor determines, if the two or more objects include an object specified by a user, to correct the one image to match the specified object. Claim 5The invention described in the above includes a processor, the processor being configured to: of a printed matter that contains more images including the first object than images including the second object, When the first image is acquired in a state where it is included in a first document, the first image is corrected to match the first object, and the first image is of a print that includes more images including the second object than images including the first object When the image is acquired in a state where it is included in the second manuscript, The The information processing device is characterized by performing correction to match the second object. Claim 6 The invention described in the item (1) is a method for acquiring a plurality of images each including one of a plurality of objects, From a printed manuscript including the The ability to obtain The above An image containing two or more objects among the plurality of objects When the number of images including a specific object among the two or more objects in the plurality of images is equal to or greater than a threshold, the specific object is Correct according to thing The present invention is a program for realizing the function of determining the above. Effect of the Invention

[0008] According to the invention of claim 1, It is possible to determine which object an image should be corrected for by taking into consideration the number of images that include each object among the multiple images in the document. . Claim 2 According to the invention, an image containing two or more objects within a document can be corrected so as to obtain a sense of uniformity in image quality within the document. Claim 3 According to the invention, in a plurality of images The number of images that contain each object Even if there are two objects that meet or exceed the standard, it is possible to determine which object an image should be adjusted to. Claim 4 According to the invention, the user can specify which object an image is to be adjusted to for correction. Claim 5 According to the invention, depending on whether an image including a first object and a second object is included in a first document or a second document, it is possible to switch between correcting the image to match the first object or the second object. Claim 6 According to the invention, It is possible to determine which object an image should be corrected for by taking into consideration the number of images that include each object among the multiple images in the document. . [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 illustrates an example of a hardware configuration of an image processing device according to an embodiment of the present invention. [Diagram 2] 1 is a block diagram showing an example of a functional configuration of an image processing device according to an embodiment of the present invention; [Figure 3-1] 4 is a flowchart showing a first example of the operation of the image processing device in the embodiment of the present invention. [Figure 3-2] 4 is a flowchart showing a first example of the operation of the image processing device in the embodiment of the present invention. [Figure 4] 11 is a flowchart showing an example of the flow of a priority correction content determination process in the embodiment of the present invention. [Diagram 5] 13A and 13B are diagrams showing an example of a correction setting screen that is displayed before the document obtaining unit obtains a document. [Figure 6] 13 is a diagram showing an example of scene information after a scene determination unit counts up the number of images for each scene for a plurality of images. FIG. [Figure 7] 11 is a diagram showing an example of correction content information to which a correction content determination unit refers when determining correction content. FIG. [Figure 8-1] 10 is a flowchart showing a second example of the operation of the image processing device in the embodiment of the present invention. [Figure 8-2] 10 is a flowchart showing a second example of the operation of the image processing device in the embodiment of the present invention. [Figure 9] 13 is a diagram showing an example of a correction setting screen displayed when an original obtaining unit obtains an original mode. FIG. [Figure 10] 11 is a diagram showing an example of top-priority scene information that is referred to when a correction content determination unit determines a top-priority scene. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0011] [Outline of this embodiment] This embodiment provides an information processing device that acquires multiple images, each of which includes one of multiple objects, and based on analysis results regarding the multiple objects in the multiple images, determines which of the two or more objects an image that includes two or more of the multiple objects should be corrected to.

[0012] Here, the information processing device may acquire multiple images from any unit of data, such as a printed manuscript or a page containing multiple images, but in the following, it will be described as acquiring multiple images from a printed manuscript containing multiple images.

[0013] In this case, an image to be corrected according to which of two or more objects is to be determined may or may not be included in the multiple images acquired from the document. The former is a case where an image within the document is corrected to obtain a sense of unity within the document, and the latter is a case where an image outside the document is corrected to obtain a sense of unity within the document. The information processing device may perform either of these corrections, but the following description will be given assuming that the information processing device performs the former correction.

[0014] Furthermore, the analysis result may be any information related to a plurality of objects in a plurality of images, but hereinafter it will be described as information indicating the importance of each of the plurality of objects in the plurality of images.

[0015] In this case, the analysis result may represent the importance of each object by any information about the images that include each object in the multiple images. The image information may include, for example, the number of images that include each object in the multiple images, the area of ​​each object in the multiple images, and the position of each object in each of the multiple images. In the following, the number of images that include each object in the multiple images will be used as an example.

[0016] In addition, when the analysis result indicates that the importance of a specific object among two or more objects is equal to or higher than a standard, the information processing device may determine to correct one image to match the specific object. Here, the importance of a specific object among two or more objects being equal to or higher than a standard may mean, for example, that the importance of the specific object among two or more objects is the highest, or that the importance of the specific object is equal to or higher than a predetermined threshold, and the former will be described below as an example.

[0017] Then, when the specific object is a first object and a second object, the information processing device may determine whether to correct one image to match the first object or the second object based on the analysis results of the first object and the second object in the part of the multiple images. Here, the "part" refers to a part of the multiple images, regardless of whether the proportion of the multiple images is large or small, but the following description will be given taking as an example a case where the multiple images are all images included in the document and the part is all images included in the pages of the document.

[0018] The information processing device performs the above operation as a first operation. In this case, the information processing device can be considered as correcting an image including a first object and a second object in a state where the image is included in a first document, to match the first object, and correcting an image in a state where the image is included in a second document, to match the second object.

[0019] In addition, if the two or more objects include an object designated by a user, the information processing device may determine to correct the one image to match the designated object. In this case, if the two or more objects do not include an object designated by a user, the information processing device may determine, based on the analysis result, to which of the two or more objects the one image is to be corrected.

[0020] The information processing device performs an operation in which this operation is added to the first operation as a second operation.

[0021] In the following, an image processing device will be described as an example of an information processing device. Here, the image processing device may be a PC (Personal Computer) or the like in which image processing software is installed, and may be connected to a printing device that prints images after image processing.

[0022] [Hardware configuration of image processing device] FIG. 1 is a diagram showing an example of a hardware configuration of an image processing device 10 according to the present embodiment. As shown in the figure, the image processing device 10 includes a processor 11, a main memory 12, and an HDD (Hard Disk Drive) 13. Here, the processor 11 executes various software such as an OS (Operating System) and applications to realize various functions described later. The main memory 12 is a storage area for storing various software and data used for executing the software, and the HDD 13 is a storage area for storing input data for the various software and output data from the various software. Furthermore, the image processing device 10 includes a communication interface (hereinafter, referred to as "I / F") 14 for communicating with the outside, a display device 15 such as a display, and an input device 16 such as a keyboard and a mouse.

[0023] [Functional configuration of image processing device] 2 is a block diagram showing an example of a functional configuration of the image processing device 10 according to the present embodiment. As shown in the figure, the image processing device 10 includes a document acquisition unit 21, an image acquisition unit 22, a scene determination unit 23, a scene information storage unit 24, a correction content determination unit 28, and a correction processing unit 29.

[0024] When performing the first operation, the manuscript acquisition unit 21 acquires a manuscript of a printed matter including a plurality of images. Here, the printed matter refers to a recording medium such as paper that is printed by a printing device and used for a specific purpose. Examples of the printed matter include photo books and food products. The manuscript refers to data that is output to a printing device to create the printed matter. Examples of the manuscript include data of photo books and food products created by software.

[0025] When performing the second operation, in addition to the above, the document acquisition unit 21 also acquires a document mode indicating a top priority scene that is a scene that the user wants to give top priority to in the document. As will be described later, in the first operation, correction is made to match a scene contained in many images, but in the second operation, even if there are few images containing a certain scene, the user may want to make correction to that scene as top priority, so the top priority scene can be specified externally regardless of the number of images.

[0026] The image acquisition unit 22 acquires a plurality of images from the document acquired by the document acquisition unit 21. Here, the plurality of images are preferably all images contained in the document, but in cases where there are too many images if all images are acquired, a portion of the images contained in the document may be acquired. Each of the plurality of images includes one of a plurality of scenes prepared in advance. Here, a scene refers to an object included in the image. For example, if the image is a photograph, a scene refers to a subject included in the image, that is, a photographed object. Examples of scenes include landscapes, people, animals, and food. For example, scenes that can be identified by an image discrimination technique using AI may be prepared in advance as the scene. In this embodiment, the processing of the image acquisition unit 22 is performed as an example of acquiring a plurality of images each including one of a plurality of objects.

[0027] The scene determination unit 23 creates scene information related to scenes in the manuscript by determining the scenes contained in each of the multiple images acquired by the image acquisition unit 22. The scene determination unit 23 may determine the scenes using, for example, an image discrimination technique using AI. The scene determination unit 23 counts the number of images containing each scene, and creates information on the number of images containing each scene as scene information. Each time the scene determination unit 23 determines the scene contained in an image acquired by the image acquisition unit 22, it passes the image to the correction content determination unit 28.

[0028] The scene information storage unit 24 stores the scene information created by the scene determination unit 23. In this embodiment, the scene information is used as an example of an analysis result related to a plurality of objects in a plurality of images. In this embodiment, the scene information is also used as an example of an analysis result indicating the importance of each of the plurality of objects in a plurality of images. Furthermore, in this embodiment, the scene information is also used as an example of an analysis result indicating the importance of each object by the number of images including each object among the plurality of images.

[0029] When performing the first operation, the correction content determination unit 28 determines to which of the two or more scenes an image including two or more scenes passed from the scene determination unit 23 should be corrected to, based on the scene information stored in the scene information storage unit 24. In the present embodiment, this process is performed by the correction content determination unit 28 as an example of determining to which of the two or more objects an image including two or more objects among a plurality of objects should be corrected to, based on the analysis result.

[0030] For example, the correction content determination unit 28 determines that an image including two or more scenes passed from the scene determination unit 23 should be corrected to match the scene included in the most images in the document. In this embodiment, a case where a certain scene among two or more scenes is included in the most images in the document is used as an example of a case where the analysis result indicates that the importance of a specific object among two or more objects is equal to or higher than a reference. Also, in this embodiment, this process of the correction content determination unit 28 is performed as an example of determining to correct an image to match a specific object in that case.

[0031] Furthermore, if there are multiple scenes included in the most images in the document, the correction content determination unit 28 determines to correct the image including two or more scenes delivered from the scene determination unit 23 to match the scene included in the most images in the page. In this embodiment, as an example of a case where a specific object is a first object and a second object, a case where there are multiple scenes included in the most images in the document is used. Also, in this embodiment, as an example of an analysis result regarding the first object and the second object in a part of the multiple images, information on the scene included in the most images in the page is used. Furthermore, in this embodiment, this process of the correction content determination unit 28 is performed as an example of determining whether an image is corrected to match the first object or the second object based on the analysis result in that case.

[0032] Furthermore, if the most numerous image on a page contains multiple scenes, the correction content determination unit 28 determines to correct the image containing two or more scenes passed from the scene determination unit 23 according to a scene determined by a predetermined priority order. Here, the predetermined priority order is exemplified as follows: people, landscapes, animals, food, flowers, and industrial products. This is the order that is considered to have the weakest degree of influence, taking into account the degree of influence of the correction.

[0033] Then, the correction content determination unit 28 determines the correction content to be applied when making correction in accordance with the scene, based on a predetermined correspondence between the scene and the correction content.

[0034] In addition to the above, when performing the second operation, the correction content determination unit 28 also determines which of the two or more scenes to correct the image including two or more scenes sent from the scene determination unit 23 according to the document mode acquired by the document acquisition unit 21. For example, the correction content determination unit 28 identifies the highest priority scene based on the document mode. Then, if the highest priority scene is included in the two or more scenes, the correction content determination unit 28 determines to correct the image including two or more scenes sent from the scene determination unit 23 according to the highest priority scene. In this embodiment, the highest priority scene is used as an example of an object specified by the user. Also, in this embodiment, if two or more objects include an object specified by the user, this process of the correction content determination unit 28 is performed as an example of determining to correct one image according to the specified object.

[0035] Furthermore, the correction content determination unit 28 performs the same correction as the first operation on an image including two or more scenes passed from the scene determination unit 23, if the two or more scenes do not include the highest priority scene. In this embodiment, this process is performed by the correction content determination unit 28 as an example of determining, based on the analysis result, to which of two or more objects an image should be corrected if two or more objects do not include an object specified by the user.

[0036] When the image and the correction content are passed from the correction content determination unit 28, the correction processing unit 29 performs a correction process on the passed image with the passed correction content. In this embodiment, the process of the correction processing unit 29 is performed as an example of correcting an image including a first object and a second object to match the first object when the image is acquired in a state where the image is included in a first document, and correcting an image to match the second object when the image is acquired in a state where the image is included in a second document.

[0037] It should be noted that the image processing device 10 does not necessarily have to include all of the document acquisition unit 21, the image acquisition unit 22, the scene determination unit 23, the scene information storage unit 24, the correction content determination unit 28, and the correction processing unit 29. For example, the image processing device 10 does not have to include the document acquisition unit 21. In that case, in the image processing device 10, the image acquisition unit 22 may acquire a plurality of images before being included in the document. Alternatively, the image processing device 10 does not have to include the correction processing unit 29. In that case, the image processing device 10 may communicate the correction content determined by the correction content determination unit 28 to another device, and the other device may perform correction on the image to be corrected using the communicated correction content.

[0038] [First operation of image processing device] 3-1 and 3-2 are flowcharts showing a first operation example of the image processing device 10 in the present embodiment. In the following, for simplicity of explanation, it is assumed that one image includes at most two scenes.

[0039] As shown in FIG. 3-1, in the image processing device 10, first, the document obtaining unit 21 obtains a document (step 201).

[0040] Next, the image acquisition unit 22 acquires a plurality of images from the document acquired in step 201 (step 202).

[0041] Next, the scene determination unit 23 focuses on one image among the multiple images acquired in step 202 (step 203). Then, the scene determination unit 23 determines the scene of the image focused on in step 203 (step 204). As a result, the scene determination unit 23 counts up the number of images for each scene in the scene information stored in the scene information storage unit 24 (step 205). Thereafter, the scene determination unit 23 determines whether or not there is an unprocessed image among the multiple images acquired in step 202 (step 206). Then, if the scene determination unit 23 determines that there is an unprocessed image, it returns the process to step 203, and if it determines that there is no unprocessed image, it proceeds to the process of FIG. 3-2.

[0042] Next, as shown in Fig. 3-2, the correction content determination unit 28 focuses on one image among the multiple images used in the scene determination in step 204 (step 211). Then, the correction content determination unit 28 determines whether the image focused on in step 211 includes two scenes (step 212). If it is determined in step 212 that the image does not include two scenes, the correction content determination unit 28 determines correction content suited to the one scene included in the image (step 213).

[0043] If it is determined in step 212 that the image contains two scenes, the correction content determination unit 28 performs a priority correction content determination process to determine the correction content of the scene that has priority among the two scenes (step 217). The priority correction content determination process will be described in detail later.

[0044] Next, the correction processing unit 29 corrects the image focused on in step 211 with the correction content determined in step 213 or step 217 (step 218). After that, the correction processing unit 29 determines whether or not there is an unprocessed image among the multiple images used for scene determination in step 204 (step 219). If the correction processing unit 29 determines that there is an unprocessed image, it returns the process to step 211, and if it determines that there is no unprocessed image, it ends the process.

[0045] FIG. 4 is a flowchart showing an example of the flow of the priority correction content determination process in step 217 in FIG. 3-2.

[0046] The correction content determination unit 28 first determines whether the images of scene A or the images of scene B are more prevalent in the document by referring to the scene information stored in the scene information storage unit 24 (step 221). If it is determined in step 221 that the images of scene A are more prevalent in the document, the correction content determination unit 28 determines the correction content suited to scene A (step 222). If it is determined in step 221 that the images of scene B are more prevalent in the document, the correction content determination unit 28 determines the correction content suited to scene B (step 223).

[0047] On the other hand, if it is determined in step 221 that the number of images of scene A and the number of images of scene B are the same in the document, the correction content determination unit 28 determines whether the images of scene A or the images of scene B are more numerous in the page (step 224). If it is determined in step 224 that the images of scene A are more numerous in the page, the correction content determination unit 28 determines the correction content suited to scene A (step 225). If it is determined in step 224 that the images of scene B are more numerous in the page, the correction content determination unit 28 determines the correction content suited to scene B (step 226). On the other hand, if it is determined in step 224 that the number of images of scene A and the number of images of scene B are the same in the page, the correction content determination unit 28 determines the correction content suited to the scene determined by a predetermined priority order (step 227).

[0048] [Specific example of the first operation of the image processing device] 5(a) and (b) are diagrams showing an example of a correction setting screen 300 displayed on the display device 15 before the document acquisition unit 21 acquires the document in step 201 of FIG. 3-1. As shown in the figure, the correction setting screen 300 includes a pull-down list 310. In the pull-down list 310, whether to correct the image by automatic correction or manual correction is selected.

[0049] 5(a) shows the state of the correction setting screen 300 when manual correction is selected from the pull-down list 310. In this case, check boxes 331, 332 and slider bars 333, 334 are displayed as active, and other items are displayed as inactive. The check boxes 331, 332 indicate that skin correction and noise correction will be performed, respectively. The slider bars 333, 334 indicate the degree of brightness and vividness, respectively.

[0050] 5(b) shows the state of the correction setting screen 300 when automatic correction is selected in the pull-down list 310. In this case, the check box 321 is displayed as active, and the other items are displayed as inactive. The check box 321 instructs the user to optimize the correction depending on the document use. When such an instruction is given in the check box 321, the operation of this embodiment is performed.

[0051] Fig. 6 is a diagram showing an example of scene information 600 after the scene determination unit 23 counts up the number of images for each scene for multiple images in step 205 of Fig. 3-1. As shown in the figure, the scene information 600 associates a scene name with the number of images.

[0052] The scene name is the name of the scene. The number of images is the number of images that include the corresponding scene. This diagram shows that the images acquired in step 202 of FIG. 3-1 included 20 images that include landscapes, 30 images that include people, 5 images that include animals, 4 images that include food, 3 images that include flowers, and 0 images that include industrial products. If an image includes multiple scenes, the number of images may be counted for each of the multiple scenes. For example, if an image includes both a person and food, the image may be counted as one image that includes a person and one image that includes food.

[0053] FIG. 7 is a diagram showing an example of correction content information 700 to be referred to when the correction content determination unit 28 determines the correction content in step 213 in FIG. 3-2 or steps 222, 223, 225, 226, and 227 in FIG.

[0054] As shown in the figure, the correction content information 700 associates a scene name, brightness correction information, contrast correction information, noise correction information, sharpness correction information, saturation correction information, and skin color correction information. The scene name is the name of the scene. The brightness correction information, contrast correction information, noise correction information, saturation correction information, and skin color correction information are information that defines whether or not the corresponding correction is to be performed when an image includes the corresponding scene. Moreover, the sharpness correction information is information that defines the degree of sharpness correction to be performed when an image includes the corresponding scene.

[0055] For example, consider the case of correcting an image containing a person and food. If this image is to be corrected to match the person, brightness correction, contrast correction, noise correction, and skin color correction will be performed. On the other hand, if this image is to be corrected to match the food, brightness correction, contrast correction, and saturation correction will be performed, and sharpness correction will be performed to a lesser extent. Note that the combination of corrections for the scene shown in FIG. 7 is merely an example.

[0056] [Second operation of image processing device] 8-1 and 8-2 are flowcharts showing a second operation example of the image processing device 10 in the present embodiment. In the following, for simplicity of explanation, it is assumed that one image includes at most two scenes.

[0057] 8-1, in the image processing device 10, the document acquisition unit 21 first accepts a document mode (step 251). This document mode is stored in a memory (not shown) that can be referenced by the correction content determination unit 28. Then, the document acquisition unit 21 acquires a document (step 261).

[0058] Next, the image acquisition unit 22 acquires a plurality of images from the document acquired in step 261 (step 262).

[0059] Next, the scene determination unit 23 focuses on one image among the multiple images acquired in step 262 (step 263). Then, the scene determination unit 23 determines the scene of the image focused on in step 263 (step 264). As a result, the scene determination unit 23 counts up the number of images for each scene in the scene information stored in the scene information storage unit 24 (step 265). Thereafter, the scene determination unit 23 determines whether or not there is an unprocessed image among the multiple images acquired in step 262 (step 266). Then, if the scene determination unit 23 determines that there is an unprocessed image, it returns the process to step 263, and if it determines that there is no unprocessed image, it proceeds to the process of FIG. 8-2.

[0060] Next, as shown in Fig. 8-2, the correction content determination unit 28 focuses on one image among the multiple images used in the scene determination in step 264 (step 271). Then, the correction content determination unit 28 determines whether the image focused on in step 271 includes two scenes (step 272). If it is determined in step 272 that the image does not include two scenes, the correction content determination unit 28 determines correction content suited to the one scene included in the image (step 273).

[0061] If it is determined in step 272 that the image contains two scenes, the correction content determination unit 28 determines the highest priority scene based on the document mode received in step 251 and stored in a memory (not shown) (step 274). Then, the correction content determination unit 28 determines whether the highest priority scene is among the two scenes identified in step 272 (step 275). If it is determined in step 275 that the highest priority scene is among the two scenes, the correction content determination unit 28 determines the correction content according to the highest priority scene (step 276).

[0062] If it is determined in step 275 that there is no top-priority scene among the two scenes, the correction content determination unit 28 performs a priority correction content determination process to determine the correction content of the priority scene among the two scenes (step 277). Details of this priority correction content determination process have been described with reference to FIG. 4, so a description thereof will be omitted here.

[0063] Next, the correction processing unit 29 corrects the image focused on in step 271 with the correction content determined in step 273, step 276, or step 277 (step 278). After that, the correction processing unit 29 determines whether or not there is an unprocessed image among the multiple images used for scene determination in step 264 (step 279). If the correction processing unit 29 determines that there is an unprocessed image, it returns the process to step 271, and if it determines that there is no unprocessed image, it ends the process.

[0064] [Specific example of the second operation of the image processing device] 9 is a diagram showing an example of a correction setting screen 350 displayed on the display device 15 when the document acquisition unit 21 acquires the document mode in step 251 of FIG. 8-1. As shown in the figure, the correction setting screen 350 includes a pull-down list 360. In the pull-down list 360, whether to correct the image by automatic correction or manual correction is selected.

[0065] FIG. 9 shows the state of the correction setting screen 350 when automatic correction is selected in the pull-down list 360. In this case, the check boxes 371 and 372 and the pull-down list 373 are displayed as active, and the other items are displayed as inactive. The check box 371 instructs to optimize the correction according to the document use. The check box 372 instructs to specify the document mode. The pull-down list 373 allows one of the document modes to be selected. Here, the people priority mode is selected. When such an instruction is given in the check boxes 371 and 372, the operation of this embodiment is performed. Here, since the people priority mode is selected in the pull-down list 373, in step 276 of FIG. 8-2, the correction content determination unit 28 determines the correction content for the image including two scenes, if the two scenes include people, to be adapted to the people.

[0066] The scene information after the scene determination unit 23 counts up the number of images for each scene for a plurality of images in step 265 in FIG. 8-1 is the same as that described with reference to FIG.

[0067] FIG. 10 is a diagram showing an example of top-priority scene information 750 that the correction content determination unit 28 refers to when determining the top-priority scene in step 274 in FIG. 8-2.

[0068] As shown in the figure, the top priority scene information associates a manuscript mode with a top priority scene name. The manuscript mode is a mode indicating a top priority scene that is a scene that the user wants to give top priority to in the manuscript. The top priority scene name is the name of the top priority scene indicated in the corresponding manuscript mode.

[0069] The correction content information that the correction content determination unit 28 refers to when determining the correction content in steps 273 and 276 in FIG. 8-2, or steps 222, 223, 225, 226, and 227 in FIG. 4, is the same as that described with reference to FIG. 7.

[0070] [Processor] In this embodiment, the term "processor" refers to a processor in a broad sense, and includes general-purpose processors (e.g., CPU: Central Processing Unit, etc.) and dedicated processors (e.g., GPU: Graphics Processing Unit, ASIC: Application Specific Integrated Circuit, FPGA: Field Programmable Gate Array, programmable logic device, etc.).

[0071] In addition, the operations of the processor in this embodiment may be performed not only by one processor, but also by multiple processors located at physically separate locations working together. The order of the operations of the processor is not limited to the order described in this embodiment, and may be changed.

[0072] [program] The processes performed by the image processing device 10 in this embodiment are prepared as a program such as application software, for example.

[0073] In other words, the program realizing this embodiment can be understood as a program that causes a computer to realize the functions of acquiring multiple images, each of which includes one of multiple objects, and determining, based on the analysis results of the multiple objects in the multiple images, which of the two or more objects an image that includes two or more of the multiple objects should be corrected to.

[0074] Incidentally, the program for realizing the present embodiment can be provided not only by communication means but also by being stored in a recording medium such as a CD-ROM. [Explanation of symbols]

[0075] 10: image processing device, 21: document acquisition section, 22: image acquisition section, 23: scene determination section, 24: scene information storage section, 28: correction content determination section, 29: correction processing section

Claims

1. A processor is provided. The processor, acquiring a plurality of images from a printed manuscript including the plurality of images, each of the images including any one of a plurality of objects; When the number of images including a specific object among the two or more objects in the plurality of images is equal to or greater than a reference value, the image including two or more objects in the plurality of images is determined to be corrected to match the specific object.

23. An information processing apparatus comprising:

2. The information processing apparatus according to claim 1 , wherein the one image is included in the plurality of images acquired from the document.

3. The information processing device according to claim 1, characterized in that when the number of images including a first object among the two or more objects in the plurality of images is the same as the number of images including a second object, and the number of images including the first object in a portion of the document is greater than the number of images including the second object, the processor determines to correct the one image to match the first object.

4. The information processing device according to claim 1 , wherein the processor determines, if the two or more objects include an object specified by a user, to correct the one image to match the specified object.

5. A processor is provided. The processor, When an image including a first object and a second object is acquired in a state where the image is included in a first document of a printed matter that includes more images including the first object than images including the second object, the image is corrected to match the first object; When the one image is acquired in a state where it is included in a second document of a printed matter that includes more images including the second object than images including the first object, the one image is corrected to match the second object.

23. An information processing apparatus comprising:

6. On the computer, A function of acquiring a plurality of images from a printed manuscript including a plurality of images each including any one of a plurality of objects; a function of determining to correct an image including two or more objects among the plurality of objects to match a specific object among the two or more objects when the number of images including the specific object among the two or more objects in the plurality of images is equal to or greater than a reference value; A program to achieve this.

Images