Color image setting system, color image setting method, and color image setting program

Abstract

This invention provides a color image setting system, a color image setting method, and a color image setting program that allow for color image setting of a target area. [Solution] The color image setting system is a system for setting the color image C of a target area. The color image setting system comprises an evaluation unit and a setting unit. The evaluation unit calculates an evaluation value D for each of the multiple color image types CA based on analysis information including the analysis results for each of the multiple color image types CA for the target area. The setting unit sets the color image type CA with the largest evaluation value D as the color image C of the target area.

Description

Technical Field

[0001] The present disclosure relates to a color image setting system, a color image setting method, and a color image setting program.

Background Art

[0002] It is known to set the color of the exterior or wall of a building to harmonize with the landscape of the town where the building is constructed. The landscape of the town is evaluated by human vision. Patent Document 1 discloses a technique for objectively evaluating the color of a landscape by quantifying it.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, even if the color of an object is quantified, it is difficult to specify what kind of color image the object corresponds to.

Means for Solving the Problems

[0005] (1) A color image setting system for solving the above problems is a color image setting system for setting a color image of a target area, including an evaluation unit that calculates an evaluation value for each of a plurality of color image types for the target area based on analysis information including analysis results for each of the plurality of color image types for the target area, and a setting unit that sets the color image type with the largest evaluation value as the color image of the target area. The color image type indicates the type of the color image.

[0006] This configuration calculates evaluation values ​​for each of multiple color image types. Therefore, multiple color image types can be compared. The color image type with the highest evaluation value is then set as the color image for the target area. This allows a color image to be set for the target area.

[0007] (2) In the color image setting system described in (1) above, the analysis information includes a plurality of color image types, a plurality of evaluation items, an item evaluation value table including the item evaluation values ​​of the evaluation items for each of the plurality of color image types, and matching information indicating whether or not the target area corresponds to the evaluation items, wherein the item evaluation value of the evaluation item for the color image type in the item evaluation value table is a value added to the color image type when the target area corresponds to the evaluation item.

[0008] In this configuration, the analysis information consists of an item evaluation value table and relevant information. The item evaluation value table contains the item evaluation values ​​for each evaluation item of multiple color image types. Therefore, the evaluation values ​​for each of the multiple color image types can be easily calculated using the relevant information.

[0009] (3) In the color image setting system described in (2) above, one or more of the multiple evaluation items are configured to be selectable in a binary format, where one of two mutually conflicting evaluation items is either applicable or not.

[0010] This configuration allows users to select one or more of the multiple evaluation items in a binary choice format. Therefore, it is easy and clear to determine whether or not an item applies. Consequently, the analysis information is less likely to contain misinformation. Here, misinformation refers to incorrect information resulting from wrong judgments due to the difficulty in making a decision.

[0011] (4) In the color image setting system described in (2) or (3) above, the system further comprises an acquisition unit and a display unit, wherein the display unit displays a plurality of evaluation items and an input field for receiving input on whether or not the target area corresponds to the evaluation item, and the acquisition unit acquires the corresponding information from the analysis information based on the input in the input field for the evaluation item.

[0012] With this configuration, the relevant information can be acquired via the display unit and the acquisition unit. Compared to acquiring the relevant information by obtaining the analysis information as a file, the operation is simpler, making it easier to collect the relevant information.

[0013] (5) In the color image setting system described in any one of (2) to (4) above, the evaluation unit calculates the evaluation value for each of the multiple color image types, and the evaluation value for each color image type is the sum of the evaluation values ​​for the evaluation items to which the target area of ​​the color image type corresponds. With this configuration, the evaluation value for each color image type can be easily calculated.

[0014] (6) In the color image setting system described in (5) above, the setting unit sets the color image type having an evaluation value that is greater than or equal to the first setting value compared to other color image types as the color image for the target area.

[0015] This configuration improves the validity of determining whether the color image set for the target area is appropriate for that area, compared to simply setting the color image type with the highest evaluation value as the color image for the target area.

[0016] (7) In the color image setting system described in (6) above, if there is no color image type among the other color image types that has an evaluation value greater than or equal to the first setting value, the evaluation unit acquires first additional evaluation information including a first additional evaluation value assigned to one of the plurality of color image types, and updates the evaluation value of the specific color image type by adding the first additional evaluation value to the original evaluation value of the specific color image type.

[0017] In this configuration, if there are no other color image types with an evaluation value greater than or equal to the first setting value, the evaluation values ​​of each of the multiple color image types are updated by the first additional evaluation information. Therefore, a color image can be set for the target area based on the newly updated evaluation values ​​of each of the multiple color image types.

[0018] (8) In the color image setting system described in (7) above, the first additional evaluation value is an added value set for a color image type identified based on color image map information, the color image map information is information including the color coordinates of the exterior structures of the target area in the color image map, and the color image map is a map showing the relationship between color coordinates and color image types. With this configuration, the first additional evaluation value can be derived based on the color image map information.

[0019] (9) In the color image setting system described in (8) above, if there is no color image type among the other color image types that has an evaluation value greater than or equal to the first setting value, the evaluation unit acquires second additional evaluation information including a second additional evaluation value assigned to a specific color image type among the plurality of color image types, and updates the evaluation value of the specific color image type by adding the second additional evaluation value to the original evaluation value of the specific color image type.

[0020] In this configuration, if there are no other color image types with an evaluation value greater than or equal to the first setting value, the evaluation values ​​of each of the multiple color image types are updated by the second additional evaluation information. Therefore, a color image can be set for the target area based on the newly updated evaluation values ​​of each of the multiple color image types.

[0021] (10) In the color image setting system described in (9) above, the second additional evaluation value is an added value set for the color image type with the largest area ratio in the captured image of the target region. With this configuration, the second additional evaluation value can be derived based on analysis of the captured image.

[0022] (11) In the color image setting system described in any one of (1) to (10) above, the target area is an area within the city that includes the site of the target building, and if the city includes a traditional streetscape, it is an area that includes the traditional streetscape, and if the city does not include the traditional streetscape, it is an area that includes a streetscape within the intermediate area that includes the site.

[0023] When a town includes traditional streetscapes, the town's color image is greatly influenced by those traditional streetscapes. Thus, the town's color image changes depending on whether or not it includes traditional streetscapes. According to the above structure, the target area differs depending on whether or not the town includes traditional streetscapes. Specifically, when the town includes traditional streetscapes, the target area is the area that includes the traditional streetscapes. When the town does not include traditional streetscapes, the target area is the area that includes the streetscapes within the intermediate area that includes the site. This allows the target area to be appropriately defined as the area for setting the town's color image, including the site of the target building. Therefore, the color image of the target building can be appropriately set to harmonize with the town's color image.

[0024] (12) The color image setting method for solving the above problems is a color image setting method for setting the color image of a target area, in which a computer calculates evaluation values for each of a plurality of color image types for the target area based on analysis information including analysis results for each of the plurality of color image types, and a setting step in which the computer sets the color image type with the largest evaluation value as the color image of the target area, wherein the color image type indicates the type of the color image.

[0025] According to this configuration, evaluation values for each of the plurality of color image types are calculated. Therefore, the plurality of color image types can be compared. And the color image type with the largest evaluation value is set as the color image of the target area. Thereby, the color image for the target area can be set.

[0026] (13) The color image setting program for solving the above problems is a color image setting program for causing a computer to set the color image of a target area, in which the computer calculates evaluation values for each of a plurality of color image types for the target area based on analysis information including analysis results for each of the plurality of color image types, and a setting step in which the computer sets the color image type with the largest evaluation value as the color image of the target area, wherein the color image type indicates the type of the color image.

[0027] According to this configuration, evaluation values for each of the plurality of color image types are calculated. Therefore, the plurality of color image types can be compared. And the color image type with the largest evaluation value is set as the color image of the target area. Thereby, the color image for the target area can be set.

Effect of the Invention

[0028] According to the color image setting system, color image setting method, and color image setting program of this disclosure, a color image can be set for a target area. [Brief explanation of the drawing]

[0029] [Figure 1] This is a schematic diagram of several areas of the city. [Figure 2] This is a flowchart showing the procedure for setting the target area. [Figure 3] This is a schematic diagram showing the relationship between the city, the target area, and the target building. [Figure 4] This is a block diagram of the color image setting system. [Figure 5] This is a diagram of a table containing some of the analytical information. [Figure 6] This is a diagram showing the item evaluation value table. [Figure 7] This is a diagram of a table showing the item evaluation value table, the corresponding information from the analysis, and the evaluation values ​​for the color image types based on the check analysis. [Figure 8] This is a table diagram that includes evaluation values ​​for color image types based on check analysis and a first additional evaluation value based on color image map analysis. [Figure 9] This is a table diagram that includes evaluation values ​​for color image types based on check analysis, a first additional evaluation value based on color image map analysis, and a second additional evaluation value based on image analysis. [Figure 10] This is a color image map. [Figure 11] This diagram shows the color coordinates of the main exterior wall, accent exterior wall, and other exterior elements for each building in the target area of ​​the first example. [Figure 12] This diagram shows the color coordinates of the main exterior wall, accent exterior wall, and other exterior features for each building in the target area of ​​the second example. [Figure 13] This is a diagram showing a photographic image of the streetscape in the target area. [Figure 14]This is an explanatory diagram illustrating image analysis. [Figure 15] This is a flowchart showing the steps for setting the color image. [Modes for carrying out the invention]

[0030] <First Embodiment> The color image setting system 1 of this embodiment will be described with reference to Figures 1 to 15. The color image setting system 1 is used when setting the color image C.

[0031] An example of using the color image setting system 1 is given. When constructing a building in a section of City R1, it is sometimes necessary to ensure that the building harmonizes with City R1. In order to set the color image C of the target building (hereinafter referred to as the target building), it is necessary to set the color image C of City R1. This is when the color image setting system 1 is used.

[0032] When setting a color image C in city R1, the target area T that the color image setting system 1 will analyze is identified. The color image setting system 1 then sets the color image C for the target area T.

[0033] In the example shown in Figure 1, town R1 includes various streetscapes. Specifically, town R1 may include streetscapes with rows of houses, streetscapes including rice paddies, traditional streetscapes T1 with rows of traditional houses, streetscapes with rows of commercial buildings, etc. Therefore, when setting a color image C for town R1, one target area T is identified from within town R1.

[0034] The target area T is the area within city R1 that includes the site T3 of the target building. City R1 is the area where the residents of the target building may interact. In one example, city R1 is defined as the area within the first radius RA1 centered on the site T3 of the target building. An example of the first radius RA1 is 1 km.

[0035] Refer to Figures 2 and 3 to explain the target area T that is subject to evaluation. The target area T that is subject to evaluation is set according to the streetscape of town R1. If town R1 includes a traditional streetscape T1, the target area T is the area that includes the traditional streetscape T1. If town R1 does not include a traditional streetscape T1, the target area T is the area that includes streetscape T2, which is located within the intermediate area R2 that includes site T3.

[0036] The flow shown in Figure 2 allows you to define the target area T for city R1, which includes the target building. In step S101, it is determined whether or not there is a traditional townscape T1 within the range of the target town R1 (target town). In step S101, if there is a traditional streetscape T1 within the range of the target city R1 (target city), in step S102, the area including the traditional streetscape T1 is set as the target area T. In step S101, if there is no traditional streetscape T1 within the range of the target city R1 (target city), in step S103, the streetscape T2 within the intermediate area R2 is set as the target area T.

[0037] The intermediate region R2 is the area near the target building. In one example, the intermediate region R2 is defined as the area within the second radius RA2 centered on the site T3 of the target building. An example of the second radius RA2 is 500m (see Figure 3).

[0038] If town R1 includes traditional streetscape T1, the color image C of town R1 is strongly influenced by traditional streetscape T1. Therefore, when constructing buildings that harmonize with town R1, the color image C of traditional streetscape T1 is important. If town R1 does not include traditional streetscape T1, when constructing buildings that harmonize with town R1, the surrounding streetscape becomes an important factor for harmony. For these reasons, the target area T is set according to the streetscape within town R1.

[0039] [Color Image C] Color Image C is a concept used when classifying images of a city R1 or buildings, etc., by color. There are various methods for classifying Color Image C. In this embodiment, Color Image C has the following four Color Image Types CA. Color Image Types CA indicate the types of Color Image C.

[0040] Color Image C has the following color image types CA: Warm Soft WS, Warm Hard WH, Cool Soft CS, and Cool Hard CH. Warm Soft WS is abbreviated as WS in drawings. Warm Hard WH is abbreviated as WH in drawings. Cool Soft CS is abbreviated as CS in drawings. Cool Hard CH is abbreviated as CH in drawings.

[0041] Warm Soft WS is a color scheme based on medium-luminosity chromatic colors, with low contrast between each color. Warm Hard WH is a color scheme primarily consisting of either low-luminosity chromatic colors or high-luminosity chromatic colors, with high contrast between each color. Cool Soft CS is a color scheme based on medium-luminosity achromatic colors, with low contrast between each color. Cool Hard CH is a color scheme primarily consisting of either low-luminosity chromatic colors or high-luminosity achromatic colors, with high contrast between each color.

[0042] As shown in Figure 4, the color image setting system 1 comprises an evaluation unit 2 and a setting unit 3. The color image setting system 1 further comprises an acquisition unit 4 and a display unit 5.

[0043] The color image setting system 1 is comprised of a computer. The evaluation unit 2 and the setting unit 3 are comprised of the computer's processor and programs stored in the computer's memory.

[0044] The acquisition unit 4 is an interface for acquiring information. In one example, the acquisition unit 4 takes the information displayed on the display unit 5 via keyboard input and inputs it into the evaluation unit 2.

[0045] The evaluation unit 2 calculates an evaluation value D for each of the multiple color image types CA based on the analysis information A. Analysis information A contains the analysis results for each of the multiple color image types CA applied to the target area T. Analysis information A also contains information for determining which of the multiple color image types CA the target area T corresponds to.

[0046] Analysis Information A includes evaluation item B1. Evaluation item B1 is information used to determine which of the multiple color image types CA the target area T corresponds to. Evaluation item B1 is formed in the form of a question. Analysis Information A includes information on whether or not it corresponds to evaluation item B1 (corresponding information A2, described below). Corresponding information A2 allows for the determination of which of the multiple color image types CA the target area T corresponds to. Corresponding information A2, which indicates whether or not it corresponds to evaluation item B1, is collected from an analyst who analyzes the target area T by visual inspection. An example of an analyst is a designer. An example of Analysis Information A is described below.

[0047] [Analysis Information A] Analysis information A includes multiple color image types CA, multiple evaluation items B1, item evaluation value table A1, and relevant information A2.

[0048] In this embodiment, a portion of the analysis information A is configured as a checklist. Specifically, the checklist includes multiple color image types CA, multiple evaluation items B1, and the corresponding information A2. The checklist is configured so that each of the multiple evaluation items B1 can be checked for each color image type CA, and so that the corresponding evaluation item B1 can be checked. Since the analysis information A includes a checklist, in this embodiment, the evaluation value D of the analysis information A is also called the "evaluation value D based on check analysis" (see Figure 7).

[0049] Evaluation item B1 includes questions to identify which color image type CA the target area T belongs to. Evaluation item B1 is configured to allow the target area T to be evaluated by visual inspection. In this embodiment, evaluation item B1 consists of seven items, from item 1 to item 7.

[0050] The first item is a question to determine whether it is warm or cool. Here, "warm" is a concept that includes warm-soft WS and warm-hard WH. "Cool" is a concept that includes cool-soft CS and cool-hard CH.

[0051] The second item consists of questions to determine whether it is soft or hard. Here, "soft" is a concept that includes warm soft (WS) and cool soft (CS). "Hard" is a concept that includes warm hard (WH) and cool hard (CH).

[0052] The third item is a question to determine whether the person is warm or cool. The third item is the same as the first item in that it asks whether the person is warm or cool, but the content of the question is different from the first item.

[0053] Item 4 is a question to determine whether it is a warm soft WS or not. Item 5 is a question to determine whether it is a warm hard WH or not. Item 6 is a question to determine whether it is a cool soft CS or not. Item 7 is a question to determine whether it is a cool hard CH or not.

[0054] One or more of the multiple evaluation items B1 are configured to be selectable in a binary format, where the user must choose between two opposing evaluation items B2. In this embodiment, the first, second, and third items are configured to be selectable in a binary format.

[0055] [Item Evaluation Value Table A1] As shown in Figure 6, Item Evaluation Value Table A1 contains the Item Evaluation Value DX for each of the multiple color image types CA and their respective evaluation items B1. The Item Evaluation Value DX for evaluation item B1 of color image type CA in Item Evaluation Value Table A1 is the value added to color image type CA when the target area T corresponds to evaluation item B1.

[0056] Among the multiple evaluation items B1, evaluation item B1 that is closely related to the characteristics of the color image type CA has a higher item evaluation value DX compared to the other evaluation items B1. In this embodiment, the item evaluation values ​​DX for items 1 and 2 are set to be greater than the item evaluation values ​​DX for items 3 through 7.

[0057] In this embodiment, for the sake of simplicity of calculation, the item evaluation value DX is a natural number. The minimum value of the item evaluation value DX is 1 point. The maximum value of the item evaluation value DX is 2 points.

[0058] The relevant information A2 is information regarding whether or not the target area T corresponds to evaluation item B1. As described above, relevant information A2 is collected from the person who visually inspects the target area T. Relevant information A2 is obtained by inputting it into the display unit 5 that displays evaluation item B1.

[0059] Let's explain an example of whether or not an item falls under evaluation item B1. Here, we will explain the first item of evaluation item B1. The first item is a binary question: (1A) Does it fall under the category of "colored colors such as beige and brown are prominent" or (1B) Does it fall under the category of "achromatic colors such as gray and black are prominent"? If the target area T falls under (1A), the corresponding information A2 for the first item will be set to "(1A)". The corresponding information A2 will be set similarly for the other evaluation items B1.

[0060] [Evaluation Section 2] The evaluation unit 2 calculates an evaluation value D for each of the multiple color image types CA. The evaluation value D for each color image type CA is the sum of the item evaluation values ​​DX of evaluation item B1 to which the target area T corresponds for each color image type CA.

[0061] Referring to Figure 7, we will explain the evaluation value D for WarmSoft WS in the analysis information A shown in Figure 5.

[0062] In the example of analysis information A shown in Figure 5, the relevant items are (1A) for item 1, (2A) for item 2, (3A) for item 3, and item 4. Warmsoft WS has an item evaluation value DX of 2 points for item 1 (1A). Warmsoft WS has an item evaluation value DX of 2 points for item 2 (2A). Warmsoft WS has an item evaluation value DX of 1 point for item 3 (3A). Warmsoft WS has an item evaluation value DX of 1 point for item 4. Therefore, the sum of these item evaluation values ​​DX results in an evaluation value D of Warmsoft WS of 6 points. The evaluation value D for other color image types CA is calculated in the same way.

[0063] The evaluation unit 2 terminates the evaluation if there is a color image type CA that has an evaluation value D greater than or equal to the first set value for any of the other color image types CA.

[0064] If the difference in evaluation value D between multiple color image types CA is small, it is unclear which color image type CA the target area T corresponds to. Therefore, the first setting value is set to a value greater than 1 point, which is the minimum value of the item evaluation value DX. For example, the first setting value is 2 points.

[0065] In the example shown in Figure 8, there are no other color image type CAs that have an evaluation value D greater than or equal to the first set value. If there are no other color image type CAs that have an evaluation value D greater than or equal to the first set value, the evaluation unit 2 acquires the first additional evaluation information (see below).

[0066] The first additional evaluation information includes information that contains a first additional evaluation value D1 assigned to a specific color image type CA among multiple color image types. The first additional evaluation value D1 is an added value set for a color image type CA identified based on color image map information (see below).

[0067] The evaluation unit 2 then updates the evaluation value D of a specific color image type CA by adding the first additional evaluation value D1 to the original evaluation value DR of the specific color image type CA. Hereinafter, the update performed when the first additional evaluation value D1 is added will be referred to as the "first update".

[0068] In the example shown in Figure 9, after the first update, there are no other color image type CAs that have an evaluation value D greater than or equal to the first set value. If, even after the first update, there are no other color image type CAs that have an evaluation value D greater than or equal to the first set value, the evaluation unit 2 acquires second additional evaluation information.

[0069] The second additional evaluation information includes the second additional evaluation value D2 assigned to a specific color image type CA among multiple color image type CAs. Note that the second additional evaluation information is different from the first additional evaluation information.

[0070] The second additional evaluation value D2 is an added value set for the color image type CA with the largest area ratio (see below) in the captured image P of the target region T.

[0071] The evaluation unit 2 then updates the evaluation value D of a specific color image type CA by adding the second additional evaluation value D2 to the original evaluation value DR of the specific color image type CA. Hereinafter, the update performed when the second additional evaluation value D2 is added will be referred to as the "second update".

[0072] [First additional evaluation value D1] The first additional evaluation value D1 will be explained with reference to Figures 10 and 11. The first additional evaluation value D1 is an evaluation value D that is assigned only to color image species CA identified based on the analysis using the color image map MP (hereinafter also referred to as "color image map analysis") for the streetscape TX of the target area T. One first additional evaluation value D1 is set for the streetscape TX of the target area T. The color image map MP is a map that shows the range of color image species CA in a color coordinate system.

[0073] The evaluation unit 2 identifies a specific range E that includes the color coordinates of the main exterior wall of the target area T of the color image map information. Next, the evaluation unit 2 calculates the area where the specific range E that includes the color coordinates of the main exterior wall of the target area T of the color image map information overlaps with the range of color image type CA in the color image map MP. Then, the evaluation unit 2 identifies the color image type CA with the largest area as the color image type CA of the target area T.

[0074] Here, the color image map information includes the color coordinates of the exterior elements in the target area T within the color image map MP.

[0075] Exterior features include the main exterior wall, accent exterior wall, and other exterior features. Other exterior features include gates and fences. The main exterior wall is the exterior wall facing the road and has the largest area among the exterior walls facing the road. The accent exterior wall is an exterior wall facing the road, has a different color from the main exterior wall, and has a smaller area than the main exterior wall.

[0076] Referring to Figure 10, an example of a color image map MP is described. A color image map MP is a map that shows the relationship between color coordinates and color image species CA.

[0077] In the color image map MP of Figure 10, the Warm Soft WS range includes the medium brightness range of chromatic colors. The Warm Hard WH range includes the high brightness range and the low brightness range of chromatic colors. The Cool Soft CS range includes the medium brightness range of achromatic colors. The Cool Hard CH range includes the high brightness range and the low brightness range of achromatic colors.

[0078] This section explains the color image map analysis. For each house in the streetscape TX of the target area T, the main exterior wall color, accent exterior wall color, and other exterior colors are collected. Colors are collected for at least three houses. Of the collected colors, those that do not fall within the color coordinate range of the color image map MP are excluded from evaluation because they have little impact on the color image C of the streetscape TX. In this embodiment, colors with a saturation greater than 2.0 are excluded from evaluation.

[0079] As shown in Figure 11, the collected colors are shown in the same color coordinate system as the color image map MP. Specifically, the collected colors are shown in the color coordinate system in a way that allows for the identification of the type of location from which the colors were collected. The types of locations from which the colors were collected are the main exterior wall, the accent exterior wall, and other exterior structures.

[0080] The evaluation unit 2 compares a specific range E (see below) with the color image map MP. Specifically, the evaluation unit 2 calculates the area where the specific range E and the range of color image type CA in the color image map MP overlap. The specific range E may include all of the color coordinates of the main outer wall of the target area T. The specific range E may also include only the color coordinates of the main outer wall of the target area T whose distance from each other is less than or equal to a predetermined distance F. In this embodiment, the specific range E is the range of color coordinates of the main outer wall of the target area T whose distance from each other is less than or equal to a predetermined distance F (see Figure 11).

[0081] In one example, a specific range E is defined to include groups of color coordinates that are connected to each other by a distance of F or less between them. Alternatively, the specific range E may include three or more color coordinates. In this embodiment, the specific range E is defined for the main exterior wall as the smallest circle or ellipse, and includes three or more color coordinates that are connected to each other by a distance of F or less between them. In another example, the specific range E may be defined based on the main exterior wall and the accent exterior wall. In yet another example, the specific range E may be defined based on the main exterior wall, the accent exterior wall, and other exterior features. The specific range E may be defined as a single range, or it may be defined as two or more ranges.

[0082] After setting the specific range E, the evaluation unit 2 performs the following process. The evaluation unit 2 identifies the color image type CA that has the largest overlapping area with the specific range E as the color image type CA of the target area T. Then, the evaluation unit 2 assigns a first additional evaluation value D1 to the specific color image type CA thus identified.

[0083] Refer to Figure 11 for a detailed explanation of how to identify the color image type CA. Figure 11 shows the color coordinates of the main exterior wall, the accent exterior wall, and other exterior elements for five houses. In the example shown in Figure 11, the black squares indicate the color coordinates of the main exterior wall. The gray squares (hatched in Figure 11; the same applies below) indicate the color coordinates of the accent exterior wall. The white squares indicate the color coordinates of other exterior elements. There are five black squares, five gray squares, and two white squares.

[0084] A specific range E is defined by four color coordinates from the five color coordinates of the black-painted square mark on the main exterior wall, which are connected by connecting lines within a predetermined distance F. This specific range E is then compared to the color image map MP. This comparison identifies the color image type CA that has the largest overlap area with the specific range E. In the example in Figure 11, the specific range E overlaps most with warm soft WS. Therefore, based on the color image map analysis, the color image C of the target area T is identified as warm soft WS. The evaluation unit 2 then assigns a first additional evaluation value D1 to the specific color image type CA identified in this way.

[0085] Figure 12 shows the color coordinates of the main exterior wall, accent exterior wall, and other exterior elements for the other five houses. In the example shown in Figure 12, as in Figure 11, the black squares indicate the color coordinates of the main exterior wall. The gray squares (hatched in Figure 12; the same applies below) indicate the color coordinates of the accent exterior wall. The white squares indicate the color coordinates of the other exterior elements.

[0086] In the example shown in Figure 12, the color coordinates of the main exterior wall do not form a cohesive group. Specifically, for the main exterior wall, there are no three or more color coordinates connected by a distance of F or less between them. Therefore, in the example shown in Figure 12, a color image C cannot be identified for the target area T.

[0087] [Second additional evaluation value D2] The second additional evaluation value D2 will be explained with reference to Figures 13 and 14. Figure 13 shows an example of a captured image P. Figure 14 shows the area of ​​each color image type CA in the captured image P.

[0088] The second additional evaluation value D2 is an evaluation value D assigned only to color image type CA identified based on analysis of the captured image P (hereinafter also referred to as "image analysis") for the streetscape TX in the target area T. One second additional evaluation value D2 is set for the streetscape TX in the target area T. The captured image P is an image of the streetscape TX in the target area T taken using a predetermined shooting method. The captured image P shows the streetscape TX.

[0089] The analysis using the captured image P is explained below. In the captured image P, the main exterior walls, accent exterior walls, and other exterior features of each house in the streetscape TX of the target area T are color-coded based on the following procedure. The color of each of the main exterior walls, accent exterior walls, and other exterior features is identified as belonging to one of several color image types CA. Then, each of the main exterior walls, accent exterior walls, and other exterior features is color-coded according to the identified color image type CA. The color coding may be performed by the evaluation unit 2 or by another color analysis device.

[0090] The evaluation unit 2 calculates the area of ​​each color image type CA (hereinafter referred to as "color image area") based on the color-coded captured image P. The evaluation unit 2 then calculates the area ratio of the color image types CA. The evaluation unit 2 identifies the color image type CA with the largest area ratio of color image areas as the color image type CA of the target region T.

[0091] The evaluation unit 2 may identify the color image type CA of the target region T based on the area ratio of each color image type CA in multiple captured images P taken of the target region T from different directions. For each of the multiple captured images P, the evaluation unit 2 calculates the color image area for each color image type CA based on the color-coded captured images P. Then, the evaluation unit 2 sums up the color image areas for each color image type CA. The evaluation unit 2 calculates the area ratio of the summed color image areas for each color image type CA. Then, the evaluation unit 2 identifies the color image type CA with the largest area ratio as the color image type CA of the target region T.

[0092] In Figure 14, Warm Soft WS is shown in light gray, and Cool Soft CS is shown in dark gray. The ratio of the areas of Warm Soft WS, Warm Hard WH, Cool Soft CS, and Cool Hard CH is 1:0:25:0. Therefore, the color image C of the target region T is identified as Cool Soft CS. The evaluation unit 2 then assigns a second additional evaluation value D2 to the specific color image type CA identified in this way.

[0093] [Acquisition part 4] The acquisition unit 4 acquires the relevant information A2 from the analysis information A based on the input in the input field for evaluation item B1 displayed in the display unit 5.

[0094] [Display section 5] The display unit 5 is composed of a liquid crystal display or an organic EL display. The display unit 5 displays information output from the evaluation unit 2. The display unit 5 displays multiple evaluation items B1 and input fields. For example, the table shown in Figure 5 is displayed.

[0095] The input field accepts input indicating whether the target area T corresponds to evaluation item B1. When the table shown in Figure 5 is displayed, the corresponding check box becomes the input field. The corresponding check box is entered in the input field by operating an input device such as a keyboard.

[0096] [Settings Section 3] The setting unit 3 sets the color image type CA with the largest evaluation value D as the color image C for the target area T.

[0097] The setting unit 3 sets a color image type CA that has an evaluation value D that is greater than or equal to the first setting value compared to other color image types CA as the color image C for the target area T.

[0098] [Color Image Settings Procedure] Referring to Figure 15, the procedure for setting color image C will be described. In the following description, the computer can perform essentially the same operations as the color image setting system 1. The computer may also be the color image setting system 1.

[0099] The color image setting procedure described here explains how to build a building that harmonizes with City R1. City R1's color image C is set to determine the colors of the building's exterior and walls.

[0100] In the first step S1, it is checked whether a design code is set for town R1 (the target town). A design code may be set for town R1 according to regulations such as townscape agreements and landscape ordinances. In this case, the color image C can be identified from the design code. However, there are cases where the color image C cannot be identified.

[0101] In the second step S2, it is determined whether a single color image C can be identified from the design code. If a single color image C can be identified from the design code, the building design can be carried out by referring to that color image C.

[0102] If there is only one color image C derived from the design code, in step S11, the computer sets that color image C as the color image C for town R1 (the target town). Then the computer terminates this flow.

[0103] If the color image C of town R1 cannot be uniquely identified, that is, if the image of town R1 may correspond to multiple color images C, the process proceeds to the next step, step S3.

[0104] In the third step S3, the computer sets multiple color images C set in city R1 (target city) which has a design code as the color image C to be evaluated. For example, if warm soft WS and warm hard WH are set as color image C in city R1, warm soft WS and warm hard WH will be set as the evaluation targets.

[0105] In step 4, S4, the target region T is defined. The target region T is defined based on the flow shown in Figure 2. The definition of the target region T may be performed by a human. The definition of the target region T may be performed by a computer based on an image containing the target region T.

[0106] In the fifth step, S5, the computer calculates an evaluation value D for each color image type CA based on the analysis information A.

[0107] In step 6, S6, it is determined whether there is one color image type CA whose evaluation value D is greater than or equal to the first setting value for any of the other color image types CA. If there is one such color image type CA, in step 11, S11, the computer sets the corresponding color image type CA as color image C. If a single color image type CA cannot be identified, or if there is no color image type CA that satisfies the condition that the evaluation value D is greater than or equal to the first setting value for any of the other color image types CA, the process proceeds to the next step, S7.

[0108] In step 7, S7, the evaluation unit 2 performs a color image map analysis. The evaluation unit 2 identifies the color image type CA of the target region T through the color image map analysis. The evaluation unit 2 then assigns a first additional evaluation value D1 to the specific color image type CA identified in this way. Furthermore, the evaluation unit 2 performs a first update. That is, the evaluation unit 2 updates the evaluation value D of the specific color image type CA by adding the first additional evaluation value D1 to the original evaluation value DR of the specific color image type CA (first update).

[0109] In step 8, S8, it is determined whether there is one color image type CA whose evaluation value D is greater than or equal to the first setting value for any of the other color image types CA. If there is one such color image type CA, in step 11, S11, the computer sets the corresponding color image type CA as color image C. If a single color image type CA cannot be identified, or if there is no color image type CA that satisfies the condition that the evaluation value D is greater than or equal to the first setting value for any of the other color image types CA, the process proceeds to the next step.

[0110] In step 9, S9, the evaluation unit 2 performs image analysis. Based on the image analysis described above, the evaluation unit 2 identifies the color image type CA of the target region T. The evaluation unit 2 then assigns a second additional evaluation value D2 to the specific color image type CA identified in this way. Furthermore, the evaluation unit 2 performs a second update. That is, the evaluation unit 2 updates the evaluation value D of the specific color image type CA by adding the second additional evaluation value D2 to the original evaluation value DR of the specific color image type CA (second update).

[0111] In step 10, S10, the color image type CA, which has the highest evaluation value D, is set as color image C.

[0112] [Operation of this embodiment] When constructing a new building or renovating an existing one, there are times when it is desirable to match the building's exterior to the color image C of town R1. However, town R1 is large and diverse, so the color image C of town R1 varies from person to person. Thus, there is no fixed standard for defining the color image C of town R1. For this reason, it is difficult to set an objectively evaluateable color image C of town R1. Furthermore, when constructing multiple new buildings to harmonize with town R1, there is a risk that buildings with different color image Cs will be constructed. In such cases, contrary to the purpose, the uniformity of the color image C of town R1 will be compromised.

[0113] In the technology disclosed herein, the color image setting system 1 comprises an evaluation unit 2 and a setting unit 3. The evaluation unit 2 calculates an evaluation value D for each of the multiple color image types CA based on analysis information A, which includes the analysis results for each of the multiple color image types CA for the target area T. The setting unit 3 sets the color image type CA with the largest evaluation value D as the color image C for the target area T. In this way, the technology analyzes each of the multiple color image types CA rather than narrowing down the color image C for the target area T to a single color image C based on human perception. Therefore, multiple color image types CA are evaluated relatively. As a result, an appropriate color image C can be set for the target area T.

[0114] [Effects of this embodiment] (1) The color image setting system 1 comprises an evaluation unit 2 and a setting unit 3. The evaluation unit 2 calculates an evaluation value D for each of the multiple color image types CA based on analysis information A, which includes the analysis results for each of the multiple color image types CA for the target area T. The setting unit 3 sets the color image type CA with the largest evaluation value D as the color image C for the target area T.

[0115] This configuration allows for the calculation of an evaluation value D for each of multiple color image types CA. Therefore, multiple color image types CA can be compared. The color image type CA with the highest evaluation value D is then set as the color image C for the target region T. This allows for the setting of a color image C for the target region T.

[0116] (2) Analysis information A includes multiple color image types CA, multiple evaluation items B1, item evaluation value table A1, and relevant information A2 indicating whether the target area T corresponds to evaluation item B1. Item evaluation value table A1 includes the item evaluation value DX for each of the multiple color image types CA and evaluation item B1. The item evaluation value DX for evaluation item B1 of the color image type CA in item evaluation value table A1 is the value added to the color image type CA when the target area T corresponds to evaluation item B1.

[0117] In this configuration, analysis information A includes item evaluation value table A1 and relevant information A2. Item evaluation value table A1 contains the item evaluation value DX for evaluation item B1 for each of the multiple color image types CA. Therefore, the evaluation value D for each of the multiple color image types CA can be easily calculated using relevant information A2.

[0118] (3) One or more of the multiple evaluation items B1 are configured to be selectable in a binary format, where the user must choose whether or not they fall under one of two opposing evaluation items B2. With this configuration, one or more of the multiple evaluation items B1 are configured to be selectable in a binary format. Therefore, it is easy to determine whether or not an evaluation item B1 applies in a simple and clear manner. Consequently, the analysis information A is less likely to contain misinformation. Here, misinformation is misinformation resulting from incorrect judgments due to the difficulty in making a determination.

[0119] (4) The color image setting system 1 comprises an acquisition unit 4 and a display unit 5. The display unit 5 displays a plurality of evaluation items B1 and an input field that accepts input on whether or not the target area T corresponds to an evaluation item B1. The acquisition unit 4 acquires the relevant information A2 from the analysis information A based on the input in the input field for evaluation item B1. With this configuration, the relevant information A2 can be acquired via the display unit 5 and the acquisition unit 4. Compared to acquiring the relevant information A2 by acquiring the analysis information A as a file, the operation is simpler, making it easier to collect the relevant information A2.

[0120] (5) The evaluation unit 2 calculates an evaluation value D for each of the multiple color image types CA. The evaluation value D for each color image type CA is the sum of the item evaluation values ​​DX of evaluation item B1 to which the target area T corresponds for each color image type CA. With this configuration, the evaluation value D for each color image type CA can be easily calculated.

[0121] (6) The setting unit 3 sets a color image type CA that has an evaluation value D that is greater than or equal to the first setting value compared to other color image types CA as the color image C for the target area T. With this configuration, the validity of whether the color image C set for the target area T is an appropriate color image C for the target area T can be improved compared to simply setting the color image type CA with the largest evaluation value D as the color image C for the target area T.

[0122] (7) If there is no other color image type CA that has an evaluation value D greater than or equal to the first set value, the evaluation unit 2 obtains first additional evaluation information, including a first additional evaluation value D1, which is assigned to one of the multiple color image type CAs. The evaluation unit 2 then updates the evaluation value D of the specific color image type CA by adding the first additional evaluation value D1 to the original evaluation value DR of the specific color image type CA.

[0123] In this configuration, if there are no other color image types CA with an evaluation value D greater than or equal to the first set value, the evaluation value D of each of the multiple color image types CA is updated by the first additional evaluation information. Therefore, a color image C can be set for the target area T based on the newly updated evaluation values ​​D of each of the multiple color image types CA.

[0124] (8) The first additional evaluation value D1 is an added value set for the color image type CA identified based on the color image map information. The color image map information includes the color coordinates of the exterior structures of the target area T in the color image map MP. The color image map MP is a map that shows the relationship between color coordinates and color image type CA. With this configuration, the first additional evaluation value D1 can be derived based on the color image map information.

[0125] (9) If there are no other color image type CAs that have an evaluation value D greater than or equal to the first set value, the evaluation unit 2 acquires second additional evaluation information including a second additional evaluation value D2. The evaluation unit 2 then updates the evaluation value D of a specific color image type CA by adding the second additional evaluation value D2 to the original evaluation value DR of that specific color image type CA.

[0126] In this configuration, if there are no other color image types CA with an evaluation value D greater than or equal to the first set value, the evaluation value D of each of the multiple color image types CA is updated by the second additional evaluation information. Therefore, a color image C can be set for the target area T based on the newly updated evaluation values ​​D of each of the multiple color image types CA.

[0127] (10) The second additional evaluation value D2 is an added value set for the color image type CA with the largest area ratio in the captured image P of the target region T. With this configuration, the second additional evaluation value D2 can be derived based on the analysis (image analysis) of the captured image P.

[0128] (11) In the color image setting system 1, the target area T is the area within town R1 that includes the site T3 of the target building. If town R1 includes a traditional streetscape T1, the target area T is the area that includes the traditional streetscape T1. If town R1 does not include a traditional streetscape T1, the target area T is the area that includes the streetscape T2 within the intermediate area R2 that includes the site T3.

[0129] If town R1 includes a traditional streetscape T1, the color image C of town R1 is greatly influenced by the traditional streetscape T1. Thus, the color image C of town R1 changes depending on whether or not it includes the traditional streetscape T1. According to the above configuration, the target area T differs depending on whether or not town R1 includes the traditional streetscape T1. Specifically, if town R1 includes the traditional streetscape T1, the target area T is the area that includes the traditional streetscape T1. If town R1 does not include the traditional streetscape T1, the target area T is the area that includes the streetscape T2 within the intermediate area R2 that includes the site T3. This allows the target area T to be appropriately set as the area for setting the color image C of town R1 that includes the site T3 of the target building. Therefore, the color image C of the target building can be appropriately set to harmonize with the color image C of town R1.

[0130] <Second Embodiment> A method for setting a color image according to the second embodiment will now be described. In this embodiment, components common to the first embodiment are denoted by the same reference numerals as in the first embodiment, and the description of redundant components is omitted.

[0131] The color image setting method is substantially the same as that of the color image setting system 1 according to the first embodiment. The color image setting method is a method for setting the color image C of the target area T. The color image setting method is performed by one or more computers. The computers may be personal computers, general-purpose computers, or servers connected to an internet network.

[0132] The color image setting method includes an evaluation step and a setting step. The evaluation step and the setting step may be performed by one computer or by separate computers.

[0133] In the evaluation process, the computer calculates an evaluation value D for each of the multiple color image types CA based on analysis information A, which includes the analysis results for each of the multiple color image types CA for the target area T.

[0134] In the setup process, the computer sets the color image type CA, which has the largest evaluation value D, as the color image C for the target area T.

[0135] This color image setting method calculates an evaluation value D for each of multiple color image types CA. Therefore, multiple color image types CA can be compared. The color image type CA with the highest evaluation value D is then set as the color image C for the target region T. This allows the color image C to be set for the target region T.

[0136] <Third Embodiment> The color image setting program will be described. In this embodiment, components common to the first embodiment are denoted by the same reference numerals as in the first embodiment, and the description of redundant components is omitted.

[0137] The color image setting program is a program that can perform the processing carried out by the color image setting system 1 according to the first embodiment. That is, the color image setting program is configured to cause the computer to set the color image C of the target area T.

[0138] The color image setting program causes one or more computers to perform predetermined processes by operating them. These computers may be personal computers, general-purpose computers, or servers connected to an internet network.

[0139] The color image setting program includes an evaluation step and a setting step. In the evaluation step, the color image setting program causes the computer to calculate an evaluation value D for each of the multiple color image types CA for the target area T, based on analysis information A which includes the analysis results for each of the multiple color image types CA. In the setting step, the color image setting program causes the computer to set the color image type CA with the largest evaluation value D as the color image C for the target area T.

[0140] This color image setting program calculates an evaluation value D for each of several color image types CA. Therefore, multiple color image types CA can be compared. The color image type CA with the highest evaluation value D is then set as the color image C for the target region T. This allows the color image C to be set for the target region T.

[0141] <Variation> The above embodiments are examples of possible forms of the color image setting system 1, color image setting method, and color image setting program, and are not intended to limit their forms. The color image setting system 1, color image setting method, and color image setting program may take forms different from those exemplified in the above embodiments. Examples include forms in which some of the configurations of the embodiments are replaced, modified, or omitted, or forms in which new configurations are added to the embodiments. Modifications of the embodiments are shown below.

[0142] In this embodiment, the color image C of the target region T is selected from four types of color image CA. Therefore, in this embodiment, there are four possible color image Cs for the color image C of the target region T. The technology of this disclosure is not limited to four types of color image CAs for the color image C of the target region T. There may be two types, three types, or five or more types of color image CAs for the color image C of the target region T.

[0143] In the first embodiment, after check analysis, a first additional evaluation value D1 is identified based on color image map analysis, and then a second additional evaluation value D2 is identified based on analysis of the captured image P (image analysis), but the order is not limited to this.

[0144] In one example, after the check analysis, a second additional evaluation value D2 may be identified based on the analysis of the captured image P, and then a first additional evaluation value D1 may be identified based on the color image map MP. In this case, if, after the check analysis, there are no other color image types CA with an evaluation value D greater than or equal to the first set value, the second additional evaluation value D2 is added to the evaluation value D obtained from the check analysis. Furthermore, if, after adding the second additional evaluation value D2, there are no other color image types CA with an evaluation value D greater than or equal to the first set value, the first additional evaluation value D1 is added to the evaluation value D after adding the second additional evaluation value D2.

[0145] In another example, after the check analysis, a first additional evaluation value D1 is identified based on the color image map analysis, and a second additional evaluation value D2 is identified based on the analysis of the captured image P (image analysis). In this case, if, after the check analysis, there are no other color image types CA that have an evaluation value D greater than or equal to the first set value, the evaluation value D from the check analysis is summed up with the first additional evaluation value D1 and the second additional evaluation value D2.

[0146] In the first embodiment, the item evaluation value DX in item evaluation value table A1 is a natural number, but the item evaluation value DX may also be a real number. The value of the item evaluation value DX in item evaluation value table A1 can be set arbitrarily.

[0147] In the technology disclosed herein, the target area T on which the color image C is set is not limited to being within a city R1. A streetscape in a rural area can be used as the target area T, and the color image C of that target area T can be set. A streetscape near a port can also be used as the target area T, and the color image C of that target area T can be set. A streetscape in a resort area can also be used as the target area T, and the color image C of that target area T can be set.

[0148] This specification discloses the following technologies: [Note 1] Note 1 is a color image setting system. The color image setting system is a system for setting the color image of a target area. The color image setting system comprises an evaluation unit and a setting unit. The evaluation unit calculates an evaluation value for each of the multiple color image types based on analysis information including the analysis results for each of the multiple color image types for the target area. The setting unit sets the color image type with the largest evaluation value as the color image for the target area. The color image type indicates the type of color image.

[0149] [Note 2] In the color image setting system described in Appendix 1, the analysis information includes a plurality of color image types, a plurality of evaluation items, an item evaluation value table containing the item evaluation values ​​for each of the plurality of color image types, and information indicating whether or not the target area corresponds to the evaluation items. The item evaluation value of the evaluation item for the color image type in the item evaluation value table is a value added to the color image type when the target area corresponds to the evaluation item.

[0150] [Note 3] In the color image setting system described in Appendix 2, one or more of the multiple evaluation items are configured to be selectable in a binary format, where the user must choose between two mutually opposing evaluation criteria.

[0151] [Note 4] The color image setting system described in Appendix 2 further includes an acquisition unit and a display unit. The display unit displays a plurality of evaluation items and an input field that accepts input as to whether or not the target area corresponds to the evaluation item. The acquisition unit acquires the corresponding information from the analysis information based on the input in the input field for the evaluation item.

[0152] [Note 5] In the color image setting system described in Appendix 2, the evaluation unit calculates the evaluation value for each of the multiple color image types. The evaluation value for each color image type is the sum of the evaluation values ​​for the evaluation items to which the target area corresponds for each color image type.

[0153] [Note 6] In the color image setting system described in Appendix 5, the setting unit sets the color image type having an evaluation value that is greater than or equal to the first setting value compared to other color image types as the color image for the target area.

[0154] [Note 7] The color image setting system described in Appendix 6. The evaluation unit obtains first additional evaluation information, including a first additional evaluation value assigned to a specific one of the multiple color image types, if there is no other color image type that has an evaluation value greater than or equal to the first setting value. The evaluation unit updates the evaluation value of the specific color image type by adding the first additional evaluation value to the original evaluation value of the specific color image type.

[0155] [Note 8] In the color image setting system described in Appendix 7, the first additional evaluation value is an added value set for a color image type identified based on color image map information. The color image map information includes information including the color coordinates of the exterior structures of the target area in the color image map. The color image map is a map showing the relationship between color coordinates and color image types.

[0156] [Note 9] In the color image setting system described in Appendix 8, if there is no color image type among the other color image types that has an evaluation value greater than or equal to the first setting value, the evaluation unit acquires second additional evaluation information, which includes a second additional evaluation value assigned to a specific color image type among the multiple color image types. The evaluation unit updates the evaluation value of the specific color image type by adding the second additional evaluation value to the original evaluation value of the specific color image type.

[0157] [Note 10] In the color image setting system described in Appendix 9, the second additional evaluation value is an added value set for the color image type with the largest area ratio in the captured image of the target area.

[0158] [Note 11] In the color image setting system described in Appendix 1, the target area is the area within the city that includes the site of the target building. If the city includes a traditional streetscape, the target area is the area that includes the traditional streetscape. If the city does not include a traditional streetscape, the target area is the area that includes the streetscape within the intermediate area that includes the site.

[0159] [Note 12] Appendix 12 describes a color image setting method. The color image setting method is a method for setting the color image of a target area. The color image setting method includes an evaluation step and a setting step. In the evaluation step, the computer calculates an evaluation value for each of the multiple color image types based on analysis information including the analysis results for each of the multiple color image types for the target area. In the setting step, the computer sets the color image type with the largest evaluation value as the color image for the target area. The color image type indicates the type of color image.

[0160] [Note 13] Appendix 13 is a color image setting program. The color image setting program is a program that causes a computer to set the color image of a target area. The color image setting program includes an evaluation step and a setting step. In the evaluation step, the color image setting program causes the computer to calculate an evaluation value for each of the multiple color image types based on analysis information including the analysis results for each of the multiple color image types for the target area. In the setting step, the color image setting program causes the computer to set the color image type with the largest evaluation value as the color image of the target area. The color image type indicates the type of color image. [Explanation of Symbols]

[0161] A...Analysis information, A1...Item evaluation value table, A2...Relevant information, B1...Evaluation item, B2...Evaluation content, C...Color image, D...Evaluation value, D1...First additional evaluation value, D2...Second additional evaluation value, DX...Item evaluation value, MP...Color image map, P...Captured image, R1...City, R2...Intermediate area, T...Target area, T3...Site, 1...Color image setting system, 2...Evaluation unit, 3...Setting unit, 4...Acquisition unit, 5...Display unit.

Claims

1. A color image setting system for setting a color image of a target area, An evaluation unit calculates an evaluation value for each of the multiple color image types based on analysis information including the analysis results for each of the multiple color image types for the target area. The system includes a setting unit that sets the color image type with the largest evaluation value as the color image for the target area, The aforementioned color image type indicates the type of color image, The aforementioned analysis information is, Multiple color image types, Multiple evaluation criteria, A table of item evaluation values ​​containing the item evaluation values ​​for each of the aforementioned evaluation items for each of the multiple color image types, The subject area includes information indicating whether or not it corresponds to the evaluation item, The item evaluation value of the evaluation item for the color image type in the item evaluation value table is the value added to the color image type when the target area corresponds to the evaluation item. Color image setting system.

2. One or more of the aforementioned evaluation items are configured to be selectable in a binary format, where the user must choose between two conflicting evaluation criteria. The color image setting system according to claim 1.

3. Furthermore, it includes an acquisition unit and a display unit, The display unit displays a plurality of evaluation items and an input field for receiving input on whether or not the target area corresponds to the evaluation item. The acquisition unit acquires the relevant information from the analysis information based on the input in the input field of the evaluation item. The color image setting system according to claim 1.

4. The evaluation unit, The evaluation value is calculated for each of the multiple color image types, The evaluation value of the color image type is the sum of the evaluation values ​​of the evaluation items to which the target area of ​​the color image type corresponds. The color image setting system according to claim 1.

5. The setting unit sets the color image type having an evaluation value that is greater than or equal to the first setting value compared to other color image types as the color image for the target area. The color image setting system according to claim 4.

6. The evaluation unit, If there is no other color image type that has an evaluation value greater than or equal to the first set value, First additional evaluation information is obtained, which includes a first additional evaluation value assigned to a specific one of the multiple color image types. The evaluation value of the specific color image type is updated by adding the first additional evaluation value to the original evaluation value of the specific color image type. The color image setting system according to claim 5.

7. The first additional evaluation value is, This is an additive value set for the color image type identified based on the color image map information. The aforementioned color image map information includes information that includes the color coordinates of the exterior structures of the target area in the color image map. The aforementioned color image map is a map that shows the relationship between color coordinates and color image types. The color image setting system according to claim 6.

8. The evaluation unit, If there is no other color image type that has an evaluation value greater than or equal to the first set value, Second additional evaluation information is obtained, which includes a second additional evaluation value assigned to a specific color image type among the multiple color image types. The evaluation value of the specific color image type is updated by adding the second additional evaluation value to the original evaluation value of the specific color image type. The color image setting system according to claim 7.

9. The aforementioned second additional evaluation value is, Regarding the area ratio of each of the color image types in the captured image of the target region, the added value is set to the image type with the largest area ratio. The color image setting system according to claim 8.

10. The aforementioned target area is, The area within the city that includes the site of the building in question, If the aforementioned town includes a traditional streetscape, the area includes the aforementioned traditional streetscape. If the aforementioned town does not include the aforementioned traditional streetscape, then the area that includes the streetscape is the intermediate area that includes the aforementioned site. The color image setting system according to claim 1.

11. A method for setting a color image for a target area, An evaluation step in which a computer calculates an evaluation value for each of the multiple color image types based on analysis information including the analysis results for each of the multiple color image types for the target area, The computer includes a setting step of setting the color image type with the largest evaluation value as the color image of the target area, The aforementioned color image type indicates the type of color image, The aforementioned analysis information is, Multiple color image types, Multiple evaluation criteria, A table of item evaluation values ​​containing the item evaluation values ​​for each of the aforementioned evaluation items for each of the multiple color image types, The subject area includes information indicating whether or not it corresponds to the evaluation item, The item evaluation value of the evaluation item for the color image type in the item evaluation value table is the value added to the color image type when the target area corresponds to the evaluation item. How to set the color image.

12. A color image setting program that causes a computer to set the color image of a target area, An evaluation step to calculate an evaluation value for each of the multiple color image types based on analysis information including the analysis results for each of the multiple color image types for the target area, The computer is instructed to perform a setting step that causes the color image type with the largest evaluation value to be set as the color image for the target area. The aforementioned color image type indicates the type of color image, The aforementioned analysis information is, Multiple color image types, Multiple evaluation criteria, A table of item evaluation values ​​containing the item evaluation values ​​for each of the aforementioned evaluation items for each of the multiple color image types, The subject area includes information indicating whether or not it corresponds to the evaluation item, The item evaluation value of the evaluation item for the color image type in the item evaluation value table is the value added to the color image type when the target area corresponds to the evaluation item. Color image setting program.

Images