Image processing device, method and program

Abstract

Achieves highly efficient and high-quality color simulation. [Solution] The image processing device includes a segmentation processing unit, a trimming processing unit, an adjustment processing unit, a multiplication processing unit, and a composition processing unit. The segmentation processing unit detects a target region in the input image by segmenting the input image. The trimming processing unit extracts the target region from the input image as a mask region by trimming the target region. The adjustment processing unit converts the mask region into a low-saturation region with reduced saturation by adjusting the saturation of the mask region. The multiplication processing unit converts the low-saturation region into a colored region colored with the specified color by multiplying the low-saturation region by a specified color. The composition processing unit generates an output image in which the target region in the input image has been replaced with the colored region by compositing the colored regions of the input image.

Description

[Technical Field]

[0001] The present invention relates to an image processing device, method, and program. [Background technology]

[0002] Conventionally, there is a technique for creating a finished drawing of a house's exterior wall paint using dedicated color simulation software. For example, in conventional techniques, a user (e.g., a painting contractor or a client) manually masks a photograph of the house. The user then creates the finished drawing by filling (or overpainting) the masked area with a single color.

[0003] However, manual masking by users requires a lot of time and effort (e.g., 1 to 2 hours per photo). Filling the masked area with a single color eliminates the texture of the original photo (e.g., shadows, unevenness, gloss), so the finished image deviates from the actual finish. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Mizuzo Co., Ltd., Color Simulation App "NURiiE", [online], [Retrieved July 24, 2025], Internet<URL:https: / / mizukura.jp / color-simulation / > Summary of the Invention [Problem to be solved by the invention]

[0005] An object of the present invention is to realize a highly efficient and high-quality color simulation. [Means for solving the problem]

[0006] An image processing device according to an embodiment includes a segmentation processing unit, a trimming processing unit, an adjustment processing unit, a multiplication processing unit, and a composition processing unit. The segmentation processing unit detects a target region in an input image by segmentation processing on the input image. The trimming processing unit extracts the target region from the input image as a mask region by trimming the target region. The adjustment processing unit converts the mask region into a low-saturation region with reduced saturation by adjustment processing on the saturation of the mask region. The multiplication processing unit converts the low-saturation region into a colored region colored with the specified color by multiplying the low-saturation region by a specified color. The composition processing unit generates an output image in which the target region in the input image is replaced with the colored region by composition processing of the colored regions on the input image. [Effects of the Invention]

[0007] According to the present invention, highly efficient and high-quality color simulation can be realized. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram showing an example of the functional configuration of an image processing system. [Figure 2] FIG. 2 is a sequence diagram showing an example of the operation of the image processing system. [Figure 3] FIG. 3 is a flowchart showing an example of the operation of the image processing device. [Figure 4] FIG. 4 is a diagram showing an example of an input image. [Figure 5] FIG. 5 is a diagram showing an example of a color selection image. [Figure 6] FIG. 6 is a diagram showing an example of an output image. [Figure 7] FIG. 7 is a block diagram showing an example of the functional configuration of another image processing system. [Figure 8] FIG. 8 is a sequence diagram showing an example of the operation of another image processing system. [Figure 9]FIG. 9 is a flowchart showing an example of the operation of another image processing device. [Figure 10] FIG. 10 is a diagram showing an example of specifying an area in an input image. [Figure 11] FIG. 11 is a diagram showing an example of another color selection image. [Figure 12] FIG. 12 is a diagram showing an example of another output image. [Figure 13] FIG. 13 is a block diagram illustrating an example of the hardware configuration of an image processing device. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments will be described with reference to the drawings. Parts with the same reference numerals are considered to be the same, and redundant description will be omitted where appropriate.

[0010] (Embodiment) 1 is a block diagram showing an example of the functional configuration of an image processing system 100. The image processing system 100 is a system that processes images. The image processing system 100 includes an image processing device 1 and a user terminal 2. The image processing device 1 and the user terminal 2 are connected to each other via a wired (or wireless) connection so that they can communicate with each other.

[0011] The image processing device 1 is a device (e.g., a computer, a server) that processes images. For example, the image processing device 1 receives an input image 50 and a specified color 70 (also called a "main color") from a user terminal 2. The image processing device 1 generates an output image 90 by performing image processing using the input image 50 and the specified color 70. The image processing device 1 transmits the output image 90 to the user terminal 2. The image processing device 1 includes various processing units for image processing (e.g., a segmentation processing unit 11, a trimming processing unit 12, an adjustment processing unit 13, a multiplication processing unit 14, and a synthesis processing unit 15).

[0012] The segmentation processing unit 11 is a means for executing segmentation processing on an image. For example, the segmentation processing unit 11 performs segmentation processing on an input image 50 to detect an image region (hereinafter referred to as a "target region TR") to be processed in the input image 50.

[0013] The trimming processing unit 12 is a means for performing a trimming process on an image. For example, the trimming processing unit 12 performs a trimming process on the target region TR of the input image 50, thereby extracting the target region TR from the input image 50 as a masked image region (hereinafter referred to as a "mask region MR").

[0014] The adjustment processing unit 13 is a means for performing adjustment processing on an image. For example, the adjustment processing unit 13 performs adjustment processing on the saturation of the mask region MR to convert the mask region MR into an image region with reduced saturation (hereinafter referred to as a "low saturation region LR").

[0015] The multiplication unit 14 is a means for performing a multiplication process on an image. For example, the multiplication unit 14 multiplies the low saturation region LR by a specified color 70 to convert the low saturation region LR into an image region colored with the specified color 70 (hereinafter referred to as a "colored region CR").

[0016] The synthesis processing unit 15 is a means for executing synthesis processing on an image. For example, the synthesis processing unit 15 synthesizes a colored region CR onto an input image 50 to generate an output image 90 in which the target region TR in the input image 50 is replaced with the colored region CR.

[0017] The user terminal 2 is a terminal (e.g., a computer or a smartphone) operated by a user. For example, the user terminal 2 acquires an input image 50 by photographing an object. The user terminal 2 selects a designated color 70 in accordance with an operation by the user. The user terminal 2 transmits the input image 50 and the designated color 70 to the image processing device 1. The user terminal 2 receives and displays an output image 90 from the image processing device 1. The user terminal 2 includes various processing units (e.g., an image capturing unit 21, an operation unit 22, a display unit 23) for input processing (or output processing).

[0018] The photographing unit 21 is a means for photographing an image (e.g., a camera). For example, the photographing unit 21 photographs an input image 50 in accordance with an operation by a user. The photographing unit 21 may store the photographed input image 50 in a memory (not shown).

[0019] The operation unit 22 is a means for receiving an operation by a user (e.g., a mouse, a keyboard, a touch panel). For example, the operation unit 22 receives an operation (e.g., a tap, a click) on a display image displayed on the display unit 23. The operation unit 22 selects a GUI (Graphical User Interface) component in the display image in accordance with the received operation.

[0020] The display unit 23 is a means for displaying an image (for example, a display). For example, the display unit 23 displays the input image 50, the output image 90, GUI components, and the like.

[0021] The image processing device 1 may include at least one of the processing units (photographing unit 21, operation unit 22, display unit 23) included in the user terminal 2. For example, the image processing device 1 may include the operation unit 22 and the display unit 23, while the user terminal 2 may include the photographing unit 21. When an input image 50 is input, the image processing device 1 may accept input of a specified color 70 from the user and display an output image 90 on the display unit 23.

[0022] The image processing device 1 may acquire the input image 50 through a storage medium (or a network). For example, the storage medium may be a CD (Compact Disc), a DVD (Digital Versatile Disc), a USB (Universal Serial Bus) memory, etc. For example, the network may be a LAN (Local Area Network), a WAN (Wide Area Network), an intranet, the Internet, etc.

[0023] 2 is a sequence diagram showing an example of the operation of the image processing system 100. The image processing system 100 executes the information processing method according to steps S1 to S7.

[0024] (Step S1) First, the user terminal 2 captures an image as the input image 50 via the photographing unit 21. For example, the photographing unit 21 captures a photo of a house as the input image 50 (see FIG. 4).

[0025] (Step S2) Next, the user terminal 2 uploads the input image 50 via the operation unit 22. For example, the operation unit 22 uploads the input image 50 by dragging and dropping the input image 50 onto a web page (not shown) displayed on the display unit 23. This upload causes the input image 50 to be transmitted to the image processing device 1. Step S2 may be executed after step S3.

[0026] (Step S3) Next, the user terminal 2 selects the designated color 70 via the operation unit 22. For example, the operation unit 22 selects the designated color 70 in the color selection image (see FIG. 5) displayed on the display unit 23. With this selection, the designated color 70 is transmitted to the image processing device 1. Step S3 may be executed before step S2.

[0027] (Step S4) Subsequently, the image processing device 1 performs image processing using the input image 50 and the specified color 70 through each processing unit. For example, the image processing device 1 performs image processing through the segmentation processing unit 11, the trimming processing unit 12, the adjustment processing unit 13, the multiplication processing unit 14, and the synthesis processing unit 15 (see FIG. 3). By performing the image processing, an output image 90 is generated (see FIG. 6). After step S4, the process proceeds to step S6.

[0028] (Step S5) Meanwhile, the user terminal 2 displays a wait image (not shown) on the display unit 23. For example, the display unit 23 displays the wait image while step S4 is being executed. The wait image may combine a circular (or linear) progress indicator with the text "Processing." Step S5 ends simultaneously with the end of step S4.

[0029] (Step S6) Subsequently, the image processing device 1 transmits the output image 90 to the user terminal 2 via the synthesis processing unit 15. The user terminal 2 may receive the output image 90 transmitted from the image processing device 1 and store it in a memory (not shown).

[0030] (Step S7) Finally, the user terminal 2 displays the output image 90 on the display unit 23 (see FIG. 6). The display unit 23 may display the output image 90 in any image file format. The image file format may be a raster format (e.g., JPEG (Joint Photographic Experts Group), GIF (Graphics Interchange Format), or PNG (Portable Network Graphics)). The user can check the finished color simulation by checking the output image 90 displayed on the display unit 23.

[0031] 3 is a flowchart showing an example of the operation of the image processing device 1. In step S4 (see FIG. 2), the image processing device 1 executes the image processing method relating to steps S41 to S45.

[0032] (Step S41) First, the image processing device 1 detects a target region TR in the input image 50 through the segmentation processing unit 11. For example, the segmentation processing unit 11 detects the target region TR by performing segmentation processing on the input image 50. The segmentation processing unit 11 may detect the target region TR using generative AI (Artificial Intelligence). The segmentation processing unit 11 may detect the target region TR using a machine learning model (e.g., a Convolutional Neural Network (CNN), an autoencoder, or a U-net) trained to perform semantic segmentation. Machine learning model-based segmentation processing can reduce the effort and time required for a user to manually detect (i.e., mask) the target region TR.

[0033] If the input image 50 represents a house, the segmentation processing unit 11 may segment each part of the house. Each part may include the following: roof, gable, fascia, eaves, ridge, corner ridge, exterior wall, recessed corner, protruding corner, fascia board, eaves, shutter, door pocket, arrowhead, entrance, fence, gate, gate door, approach, entrance porch, curb, rain gutter, eaves gutter, downspout, water collector, crawling gutter, elbow, call gutter, grip hardware, veranda, balcony, coping, and parapet. The segmentation processing unit 11 may detect a part of each part specified by the user as the target region TR. For example, if the user specifies "exterior wall," the segmentation processing unit 11 may detect the "exterior wall" through segmentation processing.

[0034] (Step S42) Next, the image processing device 1 extracts the target region TR as a mask region MR through the trimming processing unit 12. For example, the trimming processing unit 12 excludes image regions other than the target region TR from the input image 50. This exclusion allows the target region TR to be extracted from the input image 50 as the mask region MR.

[0035] (Step S43) Next, the image processing device 1 converts the mask region MR into a low saturation region LR through the adjustment processing unit 13. For example, the adjustment processing unit 13 executes a saturation adjustment process that reduces the saturation of the mask region MR. The saturation adjustment process can subtract (i.e., reduce saturation) the color of the mask region MR while maintaining the texture of the mask region MR.

[0036] (Step S44) Next, the image processing device 1 converts the low saturation region LR into a colored region CR through the multiplication unit 14. For example, the multiplication unit 14 converts the low saturation region LR into a colored region CR by multiplying the low saturation region LR by a specified color 70. The multiplication unit 14 may perform the multiplication process using a generation AI. Through the multiplication process, the low saturation mask region MR (i.e., the low saturation region LR) can be colored with the specified color 70 while maintaining the texture of the mask region MR.

[0037] (Step S45) Finally, the image processing device 1 generates an output image 90 through the synthesis processing unit 15. For example, the synthesis processing unit 15 executes synthesis processing to synthesize a colored region CR with the input image 50. Through the synthesis processing, it is possible to generate an output image 90 in which the target region TR in the input image 50 has been replaced with the colored region CR.

[0038] FIG. 4 is a diagram showing an example of an input image 50. The input image 50 is a photograph showing the exterior of a house 51 from an oblique front direction. The house 51 has a front exterior wall 52 and a side exterior wall 53. The front exterior wall 52 and the side exterior wall 53 are painted beige. The painted portions (beige) of the front exterior wall 52 and the side exterior wall 53 are represented by hatching diagonally downward to the right. The shaded portions of the front exterior wall 52 and the side exterior wall 53 are represented by a dot pattern. The front exterior wall 52 has two front windows 521. The side exterior wall 53 has four side windows 531.

[0039] 5 is a diagram showing an example of a color selection image 60. The color selection image 60 is an image that allows the user to select a specified color 70. The color selection image 60 is also called a "color palette image." The color selection image 60 has three search condition boxes (61, 62, 63) and a search result area 64.

[0040] The three search condition boxes (61, 62, 63) are boxes (i.e., GUI components) for inputting search conditions. Search condition box 61 accepts search conditions related to "manufacturer." Search condition box 62 accepts search conditions related to "category." Search condition box 63 accepts search conditions related to "color name / color code search."

[0041] For example, the user inputs search conditions into three search condition boxes (61, 62, 63) via the operation unit 22 of the user terminal 2. The user inputs the manufacturer "NP Industrial Association" into the search condition box 61. The user inputs the category "all colors" into the search condition box 62.

[0042] The image processing device 1 searches a database (not shown) using the search conditions entered in three search condition boxes (61, 62, 63). The database may store multiple colors associated with each search condition. The image processing device 1 displays the search results obtained by searching the database in the search result area 64.

[0043] The search result area 64 is an area for displaying the search results of the database. The search result area 64 has a message 641 and multiple icons 642. The message 641 indicates that out of all the colors stored in the database (i.e., out of all Y colors), a number of colors (i.e., X colors) that match the search criteria have been found. The placeholders "X" and "Y" are filled with integers equal to or greater than 0 (especially X≦Y).

[0044] The multiple icons 642 are icons that indicate color samples and color names and color codes. The multiple icons 642 are arranged in a grid (or matrix) in the vertical and horizontal directions. For example, the top left icon 642 indicates the color sample "gray" and the color name and color code "95-50B." By checking the color samples, the user can intuitively understand the color. The user can associate the color name and color code with the color of the color sample and understand it.

[0045] For example, the user selects a desired icon 642 from among the plurality of icons 642 through the operation unit 22 of the user terminal 2. The selected icon 642 is surrounded by a frame 643. For example, the selected icon 642 indicates a color sample "yellow" and a color name / color code "27-90P." By selecting the desired icon 642, the specified color 70 associated with the selected icon 642 is selected.

[0046] FIG. 6 is a diagram showing an example of an output image 90. The output image 90 is similar to the input image 50 (see FIG. 4). In the output image 90, the front exterior wall 52 and the side exterior wall 53 (i.e., the target area TR) of the house 51 are colored with the specified color 70 (see FIG. 5). The target area TR corresponds to the surface (i.e., the exterior wall surface) excluding the two front windows 521 and the four side windows 531. In the front exterior wall 52, the surface excluding the two front windows 521 is colored "yellow." In the side exterior wall 53, the surface excluding the four side windows 531 is colored "yellow." The yellow color is represented by hatching diagonally downward to the left. Shading is represented by a dot pattern.

[0047] The output image 90 maintains shading similar to that of the input image 50. Furthermore, the output image 90 maintains the pattern of the exterior wall surface (e.g., the boundary lines between blocks) similar to that of the input image 50. As a result, the output image 90 maintains the texture of the input image 50 while coloring the target region TR with the specified color 70.

[0048] According to the embodiment described above, the image processing device 1 includes a segmentation processing unit 11, a trimming processing unit 12, an adjustment processing unit 13, a multiplication processing unit 14, and a composition processing unit 15. The segmentation processing unit 11 detects a target region TR in the input image 50 by segmenting the input image 50. The trimming processing unit 12 extracts the target region TR from the input image 50 as a mask region MR by trimming the target region TR from the input image 50. The adjustment processing unit 13 adjusts the saturation of the mask region MR to convert the mask region MR into a low-saturation region LR with reduced saturation. The multiplication processing unit 14 multiplies the low-saturation region LR by a specified color 70 to convert the low-saturation region LR into a colored region CR colored with the specified color 70. The composition processing unit 15 generates an output image 90 in which the target region TR in the input image 50 has been replaced with the colored region CR by compositing the input image 50 with the colored region CR.

[0049] That is, the image processing device 1 automates manual masking (i.e., segmentation processing) performed by the user, thereby reducing the user's time and effort. The image processing device 1 reduces the saturation of the mask region MR before performing color conversion, so that the mask region MR can be colored with the specified color 70 while maintaining the texture of the original photograph (i.e., the input image 50). Therefore, the image processing device 1 can achieve highly efficient and high-quality color simulation.

[0050] Furthermore, the image processing device 1 can reduce the processing time required for color simulation (for example, 10 to 30 seconds per photograph). As a result, the image processing device 1 can significantly reduce processing time compared to the conventional technology (described above), for example, by up to 99%. At the same time, the image processing device 1 can express realistic textures in the simulation image (i.e., the output image 90).

[0051] (Variation) 7 is a block diagram showing an example of the functional configuration of another image processing system 100R. The image processing system 100R is similar to the image processing system 100 (see FIG. 1). The image processing system 100R includes another image processing device 1R and a user terminal 2.

[0052] The other image processing device 1R is a device (e.g., a computer, a server) that processes images. For example, the other image processing device 1R receives an input image 50, a specified color 70, an area 70R, and another specified color 70S (also called a "sub-color") from a user terminal 2. The other image processing device 1R generates another output image 90R by performing image processing using the input image 50, the specified color 70, the area 70R, and the another specified color 70S. The other image processing device 1R transmits the other output image 90R to the user terminal 2. The other image processing device 1R includes various processing units for image processing (e.g., a segmentation processing unit 11, an area identification unit 11R, a trimming processing unit 12, an adjustment processing unit 13, a multiplication processing unit 14, and a synthesis processing unit 15).

[0053] The region specifying unit 11R is a means for specifying a region. For example, the region specifying unit 11R specifies an image region (hereinafter referred to as a "specified region DR") specified by the user from within the target region TR.

[0054] 8 is a sequence diagram showing an example of the operation of another image processing system 100R. The other image processing system 100R executes the information processing method according to steps S1 to S7. Following step S3 (see FIG. 2), the other image processing system 100R executes steps S3R and S3S. Steps S3, S3R, and S3S may be executed in any order.

[0055] (Step S3R) Subsequently, the user terminal 2 designates the area 70R via the operation unit 22. For example, the operation unit 22 designates the area 70R in the input image 50 displayed on the display unit 23 (see FIG. 10). By this designation, the area 70R is transmitted to the image processing device 1.

[0056] (Step S3S) Subsequently, the user terminal 2 selects another designated color 70S via the operation unit 22. For example, the operation unit 22 selects another designated color 70S in another color selection image (see FIG. 11) displayed on the display unit 23. With this selection, the other designated color 70S is transmitted to the image processing device 1. Step S3S is similar to step S3 (see FIG. 2).

[0057] (Step S4R) Subsequently, the other image processing device 1R performs image processing using the input image 50, the specified color 70, the area 70R, and the other specified color 70S through each processing unit. For example, the other image processing device 1R performs image processing through the segmentation processing unit 11, the region identification unit 11R, the trimming processing unit 12, the adjustment processing unit 13, the multiplication processing unit 14, and the synthesis processing unit 15 (see FIG. 9). By performing the image processing, another output image 90R is generated (see FIG. 12).

[0058] 9 is a flowchart showing an example of the operation of the other image processing device 1R. In step S4R (see FIG. 8), the other image processing device 1R executes the image processing method relating to steps S41 to S45R.

[0059] (Step S41) First, the other image processing device 1R detects a target region TR in the input image 50 through the segmentation processing unit 11 (see FIG. 3).

[0060] (Step S41R) Next, the other image processing device 1R identifies a designated region DR from the target region TR through the region identification unit 11R. For example, the region identification unit 11R identifies an image region from the target region TR that is included in the area 70R designated by the user as the designated region DR. That is, the region identification unit 11R identifies an overlapping region between the target region TR and the area 70R as the designated region DR (see FIG. 10).

[0061] Following step S41R, a series of processes from step S42 to step S44 is executed (see FIG. 3). Meanwhile, following step S41R, another series of processes from step S42R to step S44R is executed. The steps in this series of processes and this series of processes may be executed in any order. After this series of processes and this series of processes are executed, step S45R is executed.

[0062] (Step S42R) Subsequently, the other image processing device 1R extracts the designated region DR as another mask region MRT through the trimming processing unit 12. For example, the trimming processing unit 12 excludes image regions other than the designated region DR from the input image 50. This exclusion allows the designated region DR to be extracted as another mask region MRT from the input image 50. Step S42R is similar to step S42 (see FIG. 3).

[0063] (Step S43R) Subsequently, the other image processing device 1R converts the other mask region MRT into another low saturation region LRT through the adjustment processing unit 13. For example, the adjustment processing unit 13 executes saturation adjustment processing to reduce the saturation of the other mask region MRT. The saturation adjustment processing can subtract (i.e., reduce saturation) the color of the other mask region MRT while maintaining the texture of the other mask region MRT. Step S43R is similar to step S43 (see FIG. 3).

[0064] (Step S44R) Subsequently, the other image processing device 1R converts the other low saturation region LRT into another colored region CRT through the multiplication processing unit 14. For example, the multiplication processing unit 14 converts the other low saturation region LRT into another colored region CRT by multiplying the other low saturation region LRT by another specified color 70S. Through the multiplication processing, the other low saturation region MRT (i.e., the other low saturation region LRT) can be colored with the other specified color 70S while maintaining the texture of the other mask region MRT. Step S44R is similar to step S44 (see FIG. 3).

[0065] (Step S45R) Finally, the other image processing device 1R generates another output image 90R through the synthesis processing unit 15. For example, the synthesis processing unit 15 executes synthesis processing to synthesize the colored area CR and another colored area CRT with the input image 50. Through the synthesis processing, it is possible to generate another output image 90R in which the target area TR in the input image 50 is replaced with the colored area CR and the specified area DR is replaced with the other colored area CRT.

[0066] FIG. 10 is a diagram showing an example of designating an area 70R in an input image 50. The operation unit 22 of the user terminal 2 moves a cursor C in the input image 50. By clicking any location in the input image 50, the cursor C sets a point P corresponding to the clicked location. For example, by clicking six locations in order, the cursor C sets six points (P1, P2, P3, P4, P5, P6) corresponding to the six locations, respectively. Two adjacent points P are connected by one line segment. As a result, an area 70R surrounded by the six points (P1 to P6) and the six line segments is designated.

[0067] Area 70R encompasses approximately the upper half of house 51. Area 70R encompasses approximately the upper half of each of front exterior wall 52 and side exterior wall 53. The overlapping area between front exterior wall 52 and area 70R is identified as designated area DR. The overlapping area between side exterior wall 53 and area 70R is identified as designated area DR.

[0068] FIG. 11 is a diagram showing an example of another color selection image 60R. The another color selection image 60R is similar to the color selection image 60 (see FIG. 5). The operation unit 22 of the user terminal 2 selects a desired icon 642 from among multiple icons 642. The selected icon 642 is surrounded by another frame 643R. The selected icon 642 indicates the color sample "red" and the color name / color code "08-50V." By selecting the desired icon 642, another specified color 70S associated with the selected icon 642 is selected.

[0069] FIG. 12 is a diagram showing an example of another output image 90R. In the other output image 90R, the front exterior wall 52 and the side exterior wall 53 of the house 51 (i.e., the target area TR) are colored with a specified color 70 (see FIG. 5). Furthermore, approximately the upper half of each of the front exterior wall 52 and the side exterior wall 53 is colored with another specified color 70S (see FIG. 11). As a result, approximately the lower half of each of the front exterior wall 52 and the side exterior wall 53 is colored with "yellow," and approximately the upper half is colored with "red." Yellow is represented by hatching diagonally downward to the left. Red is represented by cross-hatching diagonally downward to the left and diagonally downward to the right. Shading is represented by a dot pattern.

[0070] According to the above-described modified example, the image processing device 1R further includes a region identification unit 11R. The region identification unit 11R identifies a designated region DR designated by the user from the target region TR. The trimming processing unit 12 extracts the designated region DR from the input image 50 as a separate mask region MRT by trimming the designated region DR from the input image 50. The adjustment processing unit 13 adjusts the saturation of the separate mask region MRT to convert the separate mask region MRT into a separate low-saturation region LRT with a reduced saturation. The multiplication processing unit 14 multiplies the separate low-saturation region LRT by a separate designated color 70S to convert the separate low-saturation region LRT into a separate colored region CRT colored with the separate designated color 70S. The composition processing unit 15 composites the colored region CR and the separate colored region CRT from the input image 50 to generate a separate output image 90R in which the target region TR is replaced with the colored region CR and the designated region DR is replaced with the separate colored region CRT in the input image 50.

[0071] Another image processing device 1R can provide the same effect as the image processing device 1. The other image processing device 1R can generate another output image 90R in which a house or the like is colored with any two colors (two-tone color). The user can check the color simulation results for the combination of the two colors.

[0072] 13 is a block diagram showing an example of the hardware configuration of the image processing device 1. For example, the image processing device 1 is a general computer (or a computing device). The image processing device 1 includes components (CPU 111, RAM 112, ROM 113, storage 114, and communication device 115). The components are connected to each other via an internal bus so that they can communicate with each other.

[0073] The CPU 111 is a processor that executes processing according to a program. The CPU 111 uses a predetermined area of ​​the RAM 112 as a work area. The CPU 111 realizes each processing unit (e.g., the segmentation processing unit 11, the trimming processing unit 12, the adjustment processing unit 13, the multiplication processing unit 14, and the synthesis processing unit 15) by reading and executing each program stored in the ROM 113 (or the storage 114). The CPU 111 may realize another processing unit (e.g., the area identification unit 11R). Each processing unit may be realized by a dedicated hardware circuit (e.g., an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA (Field Programmable Gate Array)). Each processing unit may be implemented on-premise (or in the cloud). The CPU 111 is an example of a processing unit.

[0074] The RAM 112 is a volatile memory that rewritably stores various data. The ROM 113 is a nonvolatile memory that non-rewritably stores various data. The storage 114 is various storage media. The storage 114 may be a drive device that writes (or reads) various data to and from the storage media. The RAM 112, the ROM 113, or the storage 114 is an example of a storage unit.

[0075] The communication device 115 is a device that communicates various types of data. The communication device 115 may be connected to an external device via a network. The communication device 115 may be an antenna. The communication device 115 is an example of a communication unit.

[0076] Each embodiment of the present invention is presented as an example and does not limit the scope of the present invention. Each embodiment can be implemented in various forms without departing from the spirit of the present invention. Each embodiment can be combined with other embodiments. In such cases, the combined effects can be obtained. Each embodiment includes multiple components, and various combinations of multiple components can result in various inventions. Each embodiment or combination of each component is included within the scope of the present invention. [Explanation of symbols]

[0077] 1...image processing device, 1R...another image processing device, 2...user terminal, 11...segmentation processing unit, 11R...area identification unit, 12...trimming processing unit, 13...adjustment processing unit, 14...multiplication processing unit, 15...composite processing unit, 21...photographing unit, 22...operation unit, 23...display unit, 50...input image, 51...house, 52...front exterior wall, 53...side exterior wall, 60...color selected image, 60R...another color selected image, 61, 62, 63...search condition box, 64...search result area, 70...specified color, 70R...area, 70S...another specified color, 90...output image image, 90R...another output image, 100...image processing system, 100R...another image processing system, 111...CPU, 112...RAM, 113...ROM, 114...storage, 115...communication equipment, 521...front window, 531...side window, 641...message, 642...icon, 643...border line, 643R...another border line, C...cursor, CR...colored area, CRT...another colored area, DR...designated area, LR...low saturation area, LRT...another low saturation area, MR...mask area, MRT...another mask area, P...point, TR...target area

Claims

1. a segmentation processing unit that performs a segmentation process on an input image to detect a target region in the input image; a trimming processing unit that extracts the target region from the input image as a mask region by trimming the target region of the input image; an adjustment processing unit that converts the mask area into a low-saturation area by performing an adjustment process on the saturation of the mask area; a multiplication processing unit that converts the low saturation region into a colored region colored with the designated color by multiplying the low saturation region by the designated color; a synthesis processing unit that generates an output image in which the target region in the input image is replaced with the colored region by synthesizing the input image with the colored region; An image processing device comprising:

2. an area specifying unit that specifies a designated area specified by a user within the target area; Further comprising: the trimming processing unit extracts the designated area from the input image as a separate mask area by trimming the designated area of ​​the input image; the adjustment processing unit converts the other mask region into another low-saturation region in which the other saturation is reduced by performing an adjustment process on the other saturation of the other mask region; the multiplication processing unit converts the other low saturation region into another colored region colored with the other specified color by multiplying the other low saturation region by the other specified color; the synthesis processing unit synthesizes the colored region and the different colored region on the input image to generate a different output image in which the target region in the input image is replaced with the colored region and the specified region is replaced with the different colored region. The image processing device according to claim 1 .

3. The computer detecting a region of interest in an input image by a segmentation process on the input image; extracting the target region from the input image as a mask region by performing a trimming process on the target region of the input image; converting the mask area into a low-saturation area in which the saturation is reduced by performing an adjustment process on the saturation of the mask area; converting the low saturation region into a colored region colored with the designated color by multiplying the low saturation region by the designated color; generating an output image in which the target region in the input image is replaced with the colored region by performing a synthesis process on the input image using the colored region; Image processing methods.

4. On the computer, a segmentation processing function for detecting a target region in an input image by performing a segmentation process on the input image; a trimming processing function for extracting the target region from the input image as a mask region by trimming the target region of the input image; an adjustment processing function for converting the mask area into a low-saturation area by performing an adjustment process on the saturation of the mask area; a multiplication processing function for converting the low saturation region into a colored region colored with the designated color by multiplying the low saturation region by the designated color; a synthesis processing function for generating an output image in which the target area in the input image is replaced with the colored area by synthesizing the input image with the colored area; An image processing program that achieves this.

Images