CN115984721A - Method for realizing country landscape management based on oblique photography and image recognition technology - Google Patents
Method for realizing country landscape management based on oblique photography and image recognition technology Download PDFInfo
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Abstract
The invention relates to a method for realizing the country feature management based on oblique photography and an image recognition technology, which utilizes the oblique photography and the image recognition technology to extract and manage the features of country buildings. Specifically, the three-dimensional real-scene model and the orthophoto map are formed through an oblique photography technology, the building is extracted through a technical method of image recognition, classification and supervision, a building range line is optimized through combination of linear regression calculation, a building model and a data file are built, and based on the building model and the data file, the geomorphic parameters are summarized, the geomorphic harmony of a newly-built building is judged, and the geomorphic harmony of village construction change is judged and screened. The method can quickly acquire and identify the rural geomorphic conditions, realize the multi-dimensional management and geomorphic control standard formulation of rural construction, build a rural geomorphic management system, conveniently and efficiently complete the dynamic update of the rural geomorphic conditions, and realize the dynamic supervision of the rural geomorphology.
Description
Technical Field
The invention relates to the technical field of country feature management, in particular to a method for realizing country feature management based on oblique photography and an image recognition technology.
Background
Most rural areas in China have long history and cultural characteristics, and after the quick industrial and urbanized gifts, the appearance of the rural areas in China is greatly changed. Although most county and city organizations compile village planning, rural house building standard atlas and other guidance village construction and guide and control building features, linking in village construction management is still insufficient, and effective implementation is difficult to achieve. Therefore, it is important to explore effective management methods of the country landscape.
At present, village geomorphology management work is scattered in village layout and wide in range, a large amount of manpower and material resources are consumed for investigation, management work is complicated to develop, regular monitoring and management work is difficult, illegal construction, false report indexes and random construction often occur, and therefore management problems of data shortage, weak management force, high supervision difficulty and the like exist in village construction management work.
At present, remote sensing technology is generally utilized to carry out planning construction management on villages, high-resolution remote sensing images are shot to carry out division and planning management on types of land for villages, but the method has the following two problems that firstly, the data precision of the high-resolution remote sensing images is insufficient, the management of small-size construction of village-level buildings, structures and the like is difficult to realize, secondly, the high-resolution remote sensing images are two-dimensional images, data loss exists in the aspect of building geomorphology of dimensions such as building facade style, height, materials and the like, and the management of the building geomorphology is inconvenient, so that the village construction management based on the remote sensing images still has certain limitation.
Disclosure of Invention
In view of the above, in order to overcome the problems of data vacancy, large management amount, high supervision difficulty and the like in the country landscape management, the invention provides a method for realizing the country landscape management based on oblique photography and an image recognition technology, so as to realize efficient and scientific management of the country landscape.
In order to achieve the purpose, the invention adopts the technical scheme that:
a method for realizing country feature management based on oblique photography and image recognition technology comprises the following steps:
step S1: shooting a village by adopting unmanned aerial vehicle oblique photography, and setting a ground RTK calibration point and a check point; performing data calculation processing on the village based on unmanned aerial vehicle shooting data and RTK data to obtain a three-dimensional live-action model and a digital orthophoto map of the village;
step S2: converting and correcting a space coordinate system of the three-dimensional live-action model and the orthophoto map in a GIS space geographic information system to ensure that the two coordinate systems are overlapped;
and step S3: the method comprises the steps of carrying out supervision classification on a digital orthophoto map in image analysis software, carrying out automatic preliminary cutting on the digital orthophoto map, carrying out sample selection on construction elements such as buildings and structures in the digital orthophoto map, carrying out 'reclassification' on the orthophoto map through comprehensive identification and training of sample characteristic parameters such as color, spectral band ratio, elevation, height difference, shape and length-width ratio of a sample, and deriving a grid map with classification attributes;
the derived grid map with classification attributes comprises different attributes of buildings, vegetation, the ground and water; sampling points are extracted from the ground attribute grid map, and a curved surface is generated based on automatic fitting of the sampling points, namely a digital elevation model DEM;
and step S4: extracting and optimizing each building boundary line based on the grid graph of the building attributes, extracting and numbering each building according to the optimized building boundary line on the three-dimensional live-action model and the orthophoto map which are aligned in position in the GIS, and initially creating a building file;
step S5: extracting building material spatial data based on the separated real-scene models of the buildings and the optimized building boundary lines, and constructing a village building material spatial database;
specifically, each separated building three-dimensional live-action model is converted into a three-dimensional space point cloud model, and the building height (H) is analyzed by using point cloud analysis software x ) Roof slope (i) x ) Facade material color (R) x ,G x ,B x ) Carrying out analysis; building boundary to building length (L) based on optimization x ) Width (W) x ) Distance (D) x ) And the like for analysis;
the building height (H) x ) Roof slope (i) x ) Facade material color (R) x ,G x ,B x ) And building length (L) x ) Width (W) x ) Distance (D) x ) And the like to form building material space data;
step S6: performing overall statistics and analysis on village geomorphic parameter elements based on a village building material spatial database, and calculating parameter mean values of the length-width ratio, height, spacing, color and roof gradient of a building, namely building geomorphic reference parameters of the village, so as to facilitate compiling a rural house construction atlas in county and city areas and the like; meanwhile, the building geomorphology submitted to the new application can be automatically and preliminarily judged and approved;
the method for automatically and primarily judging and approving the new building style comprises the following steps: the image recognition technology is utilized to intelligently divide and recognize images such as a building plane graph, a vertical face effect graph and the like submitted for application, extract length, width, height, material color, roof form and the like, and calculate evaluation values based on building feature parameters;
step S7: the method comprises the steps that an unmanned aerial vehicle is used for shooting regularly to generate a three-dimensional real-scene model and an orthophoto map of the village, a latest village building model and map spots are established through the S1-S5 method, and the latest village building model and the map spots are compared with an original village database to find changes; then, calculating an evaluation value of the changed building based on the building geomorphic parameters (step S6), and evaluating the harmony of the changed image spots according to the evaluation value; and positioning and amplifying the buildings with low coordination degree, and sending the buildings to the personnel of the supervision department to realize the three-dimensional supervision and management of the landscapes of the buildings in the villages.
In the step S4, the method for extracting and optimizing the building boundary line includes:
obtaining the graphic spots of the grid graph of the building attribute, placing the boundary line of the graphic spots into an XY two-dimensional coordinate system, cutting the graphic spots into 4 directional sides through the center, extracting sample points of each side according to 50% of density, respectively reading the X value and the Y value, calculating the X sum (Sigma X), the Y value sum (Sigma Y), the X value sum (Sigma X), and the Y value sum (Sigma Y), and substituting the following two formulas to calculate the gradient b and the related factor a of a regression line:
and obtaining a regression line, sequentially performing linear regression calculation on four sides, and combining the regression line and the four sides into a closed building boundary line to form an optimal building boundary line.
In the step 5, the step of processing the image,
the method for analyzing the building height parameters comprises the following steps: calculating the point cloud distance between the extracted building point cloud model and the village digital elevation model DEM, wherein the peak value of the distance calculation result is the building roof height value (H) because the point clouds on the vertical surfaces are different in height and the point clouds on the roof layer are basically at the same height x )；
The method for analyzing the slope of the building roof comprises the following steps: the extracted building point cloud model is subjected to space angle calculation between points, and the point cloud on the vertical surface is basically in the vertical direction ([ gamma ] 0=90 degrees), so that the building is divided into a plurality of partsThe point cloud on the surface presents an angle (gamma 0=0 ℃) parallel to the ground or a certain angle (gamma 0 < 60 ℃), so that the peak value of the angle except the 90-degree peak value is the roof slope (i) x )；
The method for analyzing the material color of the building facade comprises the following steps: rotating the extracted building point cloud model in XYZ axis in point cloud analysis software to make the building facade parallel to the space axis surface, deriving the orthographic projection image of the building facade, intelligently cutting the facade by using image recognition software, and extracting the color value RGB (R) of the facade color block x ,G x ,B x ) And the area ratio S of color blocks cx (
S is the area of the building or region image, S x The areas of different color blocks in the region are shown, x represents the numbers of different color blocks), and the dominant hue is formed by sorting the color block areas according to the proportion cx Higher value) and influence the hue (S) cx Lower values);
building length (L) based on optimized building boundary line x ) Width (W) x ) Directly reading to obtain building distance (D) by calculating relative distance between building boundaries x )。
The calculation method of the geomorphic evaluation value is as follows:
building geomorphic evaluation value Y x ＝HX*40％+iX*20％+CX*15％+LWX*10％+DX*5％
Wherein:
the height evaluation value is:
the rooftop form rating is: if 10 ° < i x iX =1 if < 60 °, if i x < 10 °, then iX =0
The color evaluation value is:
wherein n is the area S of the color block cx The color block of the top 3 of the sequence is taken to be listed into a calculated value (namely n =1,2, 3), x refers to the building or the area to be evaluated, and R refers to the area to be evaluated xn Means the color R value of the color block ordered as the nth bit, and similarly the G value and the B value, and->
The color mean value of the n-th bit in the geomorphic parameter is sorted, and the G value and the B value are similar;
the evaluation value of the plane morphology is as follows:
the building spacing evaluation value is as follows:
after the scheme is adopted, the method for constructing the system is convenient for managing the country construction landscape, and has the advantages of high efficiency, scientificity, low cost and the like; the method can quickly collect and identify the village construction condition, realize the multi-dimensional management and the geomorphic control standard formulation of the village construction, build a village construction management system, overcome the management on the aspect of geomorphic dimension which is lost by the traditional construction remote sensing monitoring system, conveniently and efficiently complete the dynamic update of the village geomorphic condition, and realize the dynamic supervision of the village geomorphology.
The invention optimizes the extraction of the building range line based on oblique photography and image segmentation technology, and forms a regression boundary line by crossing in a linear regression calculation mode, thereby avoiding the problem of uneven building outline range caused by data acquisition errors of a point cloud model, simplifying and forming a graph which is more in line with surveying and mapping standards and has vector attributes, and enabling the extraction of the building image, the model and the form data to be more accurate.
Drawings
FIG. 1 is a flow chart of a method for realizing country construction management based on oblique photography and image recognition technology provided by the invention;
FIG. 2 is a building grid graph and building boundary line extracted based on supervised classification;
FIG. 3 is a building boundary line formed by regression calculations based on building boundary point clouds;
FIG. 4 is a value of a village landscape color parameter extracted based on image segmentation;
fig. 5 is a building facade orthographic projection image extracted based on XYZ axis correction.
Detailed Description
As shown in FIG. 1, the invention discloses a method for realizing rural landscape management based on oblique photography and image recognition technology, which comprises the following steps:
step S1: carrying out on-site survey on the overall situation of a target village, planning a flight line and flight parameters of the unmanned aerial vehicle according to the range of the village area, carrying out oblique shooting, and setting a ground RTK calibration point and a check point; and carrying out three-dimensional live-action modeling processing on the village based on the unmanned aerial vehicle shooting data and the RTK data to obtain a village three-dimensional live-action model and a digital orthophoto map.
Step S2: and (3) converting and correcting the three-dimensional live-action model and the orthophoto map in a GIS spatial geographic information system to enable the coordinate systems to be coincident.
And step S3: the method comprises the steps of performing supervision classification on a digital orthophoto map in image analysis software (such as eCongnition), performing automatic preliminary cutting on the digital orthophoto map, performing sample selection on construction elements such as buildings and structures in the digital orthophoto map, performing 'reclassification' on the orthophoto map through comprehensive identification and training of sample characteristic parameters such as color, spectral band ratio, elevation, height difference, shape, length-width ratio and the like of a sample, and deriving a grid map with classification attributes, wherein the grid map is specifically shown in FIG. 2.
The derived grid map with classification attributes comprises different attributes of buildings, vegetation, the ground, water bodies and the like. Sampling points are extracted from the ground attribute grid map, and a curved surface is generated based on automatic fitting of the sampling points, namely the digital elevation model DEM. The grid maps with the same attribute are combined to form the current land maps such as cultivated land, forest land, grassland, construction land, traffic land, water area and the like.
And step S4: and extracting and optimizing each building boundary line based on the grid graph of the building attributes, cutting the three-dimensional live-action model and the orthographic image which are aligned in position in the GIS according to the optimized building boundary line, extracting and numbering each building, and initially creating a building file.
In this embodiment, the method for extracting and optimizing the building boundary line includes: obtaining the graphic spots of the grid graph of the building attribute, placing the boundary line of the graphic spots into an XY two-dimensional coordinate system, cutting the graphic spots into 4 directional sides through the center, extracting sample points of each side according to 50% of density, respectively reading the X value and the Y value, calculating the X sum (Sigma X), the Y value sum (Sigma Y), the X value sum (Sigma X), and the Y value sum (Sigma Y), and substituting the following two formulas to calculate the gradient b and the related factor a of a regression line:
regression lines of the directional sides are obtained, linear regression calculation is performed on four sides in sequence, and the four sides are combined to form a closed building boundary line, so that an optimal building boundary line is formed, as shown in fig. 3.
Due to modeling limitation of the oblique photography modeling technology and error in judgment of image segmentation technical parameters, the grid map of the building attributes extracted based on the image supervision and classification method in the step S3 has certain unevenness, which is inconsistent with the building boundary line standard (smooth curve or flat straight line) of the terrain map in reality and in the mapping industry. Therefore, the invention uses a regression calculation mode to take regression lines of all edges and combine the regression lines to form the building boundary line.
Step S5: and extracting the building material space data based on the separated real-scene models of the buildings and the optimized building boundary lines, and constructing a village building material space database.
Specifically, each separated building three-dimensional live-action model is converted into a three-dimensional space point cloud model, and the building height (H) is analyzed by using point cloud analysis software x ) Roof slope (i) x ) Facade material color (R) x ,G x ,B x ) Etc. for analysis.Building boundary to building length (L) based on optimization x ) Width (W) x ) Distance (D) x ) And so on. The building height (H) x ) Roof slope (i) x ) Facade material color (R) x ,G x ,B x ) And building length (L) x ) Width (W) x ) Distance (D) x ) Etc. constitute building material space data.
The method for analyzing the building height parameters comprises the following steps: performing point cloud distance calculation on the extracted building point cloud model and the village digital elevation model DEM, wherein the peak value of the distance calculation result is a building roof height value (H) because the point clouds on the vertical surface are different in height and the point clouds on the roof layer are basically at the same height x )。
The method for analyzing the building roof gradient comprises the following steps: the extracted building point cloud model is subjected to space angle calculation between points, the point cloud on the vertical surface is basically in the vertical direction ([ gamma ] 0=90 degrees), and the point cloud on the roof is parallel to the ground angle ([ gamma ] 0=0 degrees) or has a certain angle ([ gamma ] 0 < 60 degrees), so the angle peak value except the 90-degree peak value is removed as the roof gradient (i < gamma > 0 < 60 degrees) x )。
As shown in fig. 5, the method for analyzing the material color of the building facade comprises the following steps: rotating the extracted building point cloud model in XYZ axis in point cloud analysis software to make the building facade parallel to the space axis surface, deriving the orthographic projection image of the building facade, intelligently cutting the facade by using image recognition software (such as eCongnition), and extracting the color value RGB (R) of the facade color block x ,G x ,B x ) And the area ratio S of color blocks cx (
S is the area of the building or region image, S x The areas of different color blocks in the region are shown, x represents the numbers of different color blocks), and the dominant hue is formed by sorting the color block areas according to the proportion cx Higher value) and influence on hue (S) cx The value is lower). (as shown in fig. 4).
The method for analyzing the length, width and spacing of the building comprises the following steps: building length (L) based on optimized building boundary line x ) Width (W) x ) Directly reading to obtain the building distance (D) by calculating the relative distance between the building boundaries x )。
Step S6: performing overall statistics and analysis on village geomorphic parameter elements based on a village building material spatial database, and calculating parameter mean values such as the length-width ratio, the height, the interval, the color, the roof gradient and the like of a building, namely building geomorphic reference parameters of the village, so that a farmhouse construction drawing set can be conveniently compiled in county areas, urban areas and the like; meanwhile, the building style submitted by the new application can be automatically and preliminarily judged and approved. The method for automatically and primarily judging and approving the new building style comprises the following steps: the image recognition technology is utilized to intelligently segment and recognize images such as a building plane graph, a vertical face effect graph and the like submitted for application, the length, the width, the height, the material color, the roof form and the like are extracted, evaluation value calculation is carried out based on building geomorphic parameters, and a geomorphic evaluation value calculation method comprises the following steps:
building geomorphic estimation value Y x ＝HX*40％+iX*20％+CX*15％+LWX*10％+DX*5％
Wherein:
the height evaluation value is:
the rooftop form rating is: if 10 ° < i x iX =1 if < 60 °, if i x < 10 °, then iX =0
The color evaluation value is:
wherein n is the area S of the color block cx The color block of the top 3 of the sequence is taken to be listed into a calculated value (namely n =1,2, 3), x refers to the building or the area to be evaluated, and R refers to the area to be evaluated xn Means the color R value of the color block ordered as the nth bit, the G value and the B value in the same way, and the combination thereof>
The color mean value of the n-th bit in the geomorphic parameter is sorted, and the G value and the B value are similar; />
The evaluation value of the plane morphology is as follows:
the building spacing evaluation value is as follows:
the supervision department personnel can decide whether to approve the construction of the new building according to the landscape evaluation value of the building and return the revised design draft to the scheme which is not passed.
Step S7: the method comprises the steps that an unmanned aerial vehicle is used for shooting regularly to generate a three-dimensional live-action model and an orthophoto map of the village, a latest village building model and map spots are built through the S1-S5 method, and the latest village building model and the map spots are compared with an original village database to find changes; then, the evaluation value calculation is performed for the building that has changed based on the building feature parameters (synchronization step S6), and the harmony of the change patches is evaluated based on the evaluation value, and for example, when the evaluation value is below a certain threshold, the harmony is considered to be low. And positioning and amplifying the buildings with low coordination degree, and sending the buildings to the personnel of the supervision department to realize the three-dimensional supervision and management of the landscapes of the buildings in the villages.
The method summarizes the geomorphic parameters of the buildings in the villages, performs geomorphic coordination evaluation on the change points through the parameters, screens out changes caused by the life of residents or the growth change of vegetation or elevation and other reasons, prejudges geomorphic coordination in advance, and reduces the field verification work of geomorphic control management. After the change is compared, the invention scores the changed buildings from the geomorphic parameters and extracts the changed pictures, so that the workload of the workers in the field supervision is reduced.
In conclusion, the method for constructing a more system is convenient for managing the country construction landscape and has the advantages of high efficiency, scientificity, low cost and the like; the method can quickly collect and identify the village construction condition, realize the multi-dimensional management and the geomorphic control standard formulation of the village construction, build a village construction management system, overcome the management on the aspect of geomorphic dimension which is lost by the traditional construction remote sensing monitoring system, conveniently and efficiently complete the dynamic update of the village geomorphic condition, and realize the dynamic supervision of the village geomorphology.
The invention optimizes the extraction of the building range line based on oblique photography and image segmentation technology, and forms a regression boundary line by crossing in a linear regression calculation mode, thereby avoiding the problem of uneven building outline range caused by data acquisition errors of a point cloud model, simplifying and forming a graph which is more in line with surveying and mapping standards and has vector attributes, and enabling the extraction of the building image, the model and the form data to be more accurate.
The above description is only an example of the present invention, and does not limit the technical scope of the present invention, so that any minor modifications, equivalent changes and modifications made to the above embodiment according to the technical essence of the present invention are within the technical scope of the present invention.
Claims (4)
1. A method for realizing country feature management based on oblique photography and image recognition technology is characterized in that: the method comprises the following steps:
step S1: shooting a village by adopting unmanned aerial vehicle oblique photography, and setting a ground RTK calibration point and a check point; performing data calculation processing on the village based on unmanned aerial vehicle shooting data and RTK data to obtain a three-dimensional real-scene model and a digital orthophoto map of the village;
step S2: converting and correcting a space coordinate system of the three-dimensional live-action model and the orthophoto map in a GIS space geographic information system to ensure that the two coordinate systems are overlapped;
and step S3: the method comprises the steps of carrying out supervision classification on a digital orthophoto map in image analysis software, carrying out automatic preliminary cutting on the digital orthophoto map, carrying out sample selection on construction elements such as buildings and structures in the digital orthophoto map, carrying out 'reclassification' on the orthophoto map through comprehensive identification and training of sample characteristic parameters such as color, spectral band ratio, elevation, height difference, shape and length-width ratio of a sample, and deriving a grid map with classification attributes;
the derived grid map with classification attributes comprises different attributes of buildings, vegetation, the ground and water; sampling points are extracted from the ground attribute grid map, and a curved surface is generated by automatic fitting based on the sampling points, namely the digital elevation model DEM;
and step S4: extracting and optimizing each building boundary line based on the grid graph of the building attributes, extracting and numbering each building according to the optimized building boundary line on the three-dimensional live-action model and the orthophoto map which are aligned in position in the GIS, and initially creating a building file;
step S5: extracting building material space data based on the separated real-scene models of the buildings and the optimized building boundary lines, and constructing a village building material space database;
specifically, each separated building three-dimensional live-action model is converted into a three-dimensional space point cloud model, and the building height (H) is analyzed by using point cloud analysis software x ) Roof slope (i) x ) Facade material color (R) x ,G x ,B x ) Carrying out analysis; building boundary to building length (L) based on optimization x ) Width (W) x ) Distance (D) x ) And the like for analysis;
the building height (H) x ) Roof slope (i) x ) Color of elevation material (R) x ,G x ,B x ) And building length (L) x ) Width (W) x ) Distance (D) x ) And the like to form building material space data;
step S6: performing overall statistics and analysis on village geomorphic parameter elements based on a village building material spatial database, and calculating parameter mean values of the length-width ratio, height, spacing, color and roof gradient of a building, namely building geomorphic reference parameters of the village, so as to facilitate compiling a rural house construction atlas in county and city areas and the like; meanwhile, the building geomorphology submitted to the new application can be automatically and preliminarily judged and approved;
the method for automatically and preliminarily distinguishing and approving the submitted new building features comprises the following steps: the image recognition technology is utilized to intelligently segment and recognize images such as a building plane graph, a vertical face effect graph and the like submitted for application, the length, the width, the height, the material color, the roof form and the like are extracted, and evaluation value calculation is carried out based on building feature reference parameters;
step S7: the method comprises the steps that an unmanned aerial vehicle is used for shooting regularly to generate a three-dimensional real-scene model and an orthophoto map of the village, a latest village building model and map spots are established through the S1-S5 method, and the latest village building model and the map spots are compared with an original village database to find changes; then, calculating evaluation values of the changed buildings based on the building geomorphic reference parameters, and evaluating the harmony of the changed image spots according to the evaluation values; and positioning and amplifying the buildings with low coordination degree, and sending the buildings to the personnel of the supervision department to realize the three-dimensional supervision and management of the landscapes of the buildings in the villages.
2. The method for realizing rural landscape management based on oblique photography and image recognition technology according to claim 1, wherein the method comprises the following steps: in the step S4, the method for extracting and optimizing the building boundary line includes:
obtaining the graphic spots of the grid graph of the building attribute, placing the boundary line of the graphic spots into an XY two-dimensional coordinate system, cutting the graphic spots into 4 directional sides through the center, extracting sample points of each side according to 50% of density, respectively reading the X value and the Y value, calculating the X sum (Sigma X), the Y value sum (Sigma Y), the X value sum (Sigma X), and the Y value sum (Sigma Y), and substituting the following two formulas to calculate the gradient b and the related factor a of a regression line:
and obtaining regression lines of the direction sides, sequentially performing linear regression calculation on the four sides, and combining the regression lines into a closed building boundary line to form an optimal building boundary line.
3. The method for realizing rural landscape management based on oblique photography and image recognition technology according to claim 1, wherein the method comprises the following steps: in the step 5, the step of processing the image,
the method for analyzing the building height parameters comprises the following steps: performing extraction on the building point cloud model and the village digital elevation model DEMCalculating the distance between the point clouds, wherein the point clouds on the vertical surfaces are different in height, and the point clouds on the roof layer are basically at the same height, so that the peak value of the distance calculation result is the height value (H) of the building roof x )；
The method for analyzing the building roof gradient comprises the following steps: the extracted building point cloud model is subjected to space angle calculation between points, the point cloud on the vertical surface is basically in the vertical direction ([ gamma ] 0=90 degrees), and the point cloud on the roof is parallel to the ground angle ([ gamma ] 0=0 degrees) or has a certain angle ([ gamma ] 0 < 60 degrees), so the angle peak value except the 90-degree peak value is removed as the roof gradient (i < gamma > 0 < 60 degrees) x )；
The method for analyzing the material color of the building facade comprises the following steps: rotating the extracted building point cloud model in XYZ axis in point cloud analysis software to make the building facade parallel to the space axis surface, deriving the orthographic projection image of the building facade, intelligently cutting the facade by using image recognition software, and extracting the color value RGB (R) of the facade color block x ,G x ,B x ) And area ratio of color blocks
S is the area of the building or region image, S x The areas of different color blocks in the region are shown, x represents the numbers of different color blocks), and the dominant hue is formed by sorting the color block areas according to the proportion cx Higher value) and influence on hue (S) cx Lower values);
building length (L) based on optimized building boundary line x ) Width (W) x ) Directly reading to obtain the building distance (D) by calculating the relative distance between the building boundaries x )。
4. The method for realizing the country feature management based on oblique photography and image recognition technology according to claim 1, characterized in that: the calculation method of the geomorphic evaluation value is as follows:
building geomorphic estimation value Y x ＝HX*40％+iX*20％+CX*15％+LWX*10％+DX*5％
Wherein:
the height evaluation value is:
the rooftop form rating is: if 10 ° < i x iX =1 if < 60 °, if i x < 10 °, then iX =0
The color evaluation value is:
wherein n is the area S of the color blocks cx The color block of the top 3 of the sequence is taken to be listed into a calculated value (namely n =1,2, 3), x refers to the building or the area to be evaluated, and R refers to the area to be evaluated xn Means the color R value of the color block ordered as the nth bit, and similarly the G value and the B value, and->
Means the color mean value of the n-th order in the geomorphic parameter, the same way
Value and->
A value;
the evaluation value of the plane morphology is as follows:
/>
the building spacing evaluation value is as follows:
/>
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116822798A (en) * | 2023-07-06 | 2023-09-29 | 北京大学 | Regional locality measurement method for urban and rural feature modeling |
| CN116822798B (en) * | 2023-07-06 | 2024-03-29 | 北京大学 | Regional locality measurement method for urban and rural feature modeling |
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