A system and method for online verification and monitoring of cultivated land change patterns

Abstract

A system and method for online verification and monitoring of cultivated land change spots, which relates to the field of natural resource data management. A spot positioning unit locates the three-dimensional geographic coordinates of a suspected illegal change vector map spot of cultivated land protection; a camera matching unit matches a PTZ camera according to the three-dimensional geographic coordinates of the spots obtained by the spot positioning unit; and the P, T, and Z values ​​of the camera are determined according to the selected PTZ camera geographic location and the three-dimensional geographic coordinates of the spots; a position association unit converts the three-dimensional geographic coordinates of the spots into PTZ camera pixel coordinates, and marks the corresponding spot position on the PTZ camera image; and a spot verification unit includes a spot database, and stores the verified illegal spots in the spot database. The present invention combines a PTZ camera with a three-dimensional map to establish the consistency of the video and the three-dimensional map in time and space, and establishes a spot archive for a realistic scene of the online verification of suspected illegal spots, thereby effectively reducing the workload and improving efficiency.

Description

Technical Field

[0001] The present invention relates to the field of natural resource data management, and more specifically, to an online verification and monitoring method of cultivated land change images based on a PTZ camera. Background Art

[0002] In recent years, due to the rapid development of urbanization and industrialization, a large amount of arable land has been occupied and destroyed, resulting in a shortage of arable land resources and environmental pollution, which seriously affected food production and agricultural development. Since 2019, the National Natural Resources Supervision Agency has organized annual inspections on arable land protection, "managing land with maps", focusing on the intelligent identification and early discovery of patches, based on the core data source of serialized high-resolution satellite images, and the corresponding permanent basic farmland, temporary land, facility agricultural land, supplementary arable land projects, mining rights data and approval red line data for analysis, using AI intelligent recognition technology to extract patches of arable land use changes, forming suspected "occupying land", "destroying land" and changing the use of arable land and other illegal arable land change patches, which are sent to various provinces for suspected illegal patches to be verified, confirmed and handled, with "zero tolerance" for illegal occupation of arable land, resolutely curbing the "non-agriculturalization" of arable land, and strictly controlling the "non-grainization" of arable land, to escort food security.

[0003] After the land annual change survey and geographic national conditions map were compared and analyzed and deduplicated, the number of suspected problem spots extracted was huge, and striping and fragmentation were common. In addition, affected by the external weather environment, the accuracy of the spots was relatively low. In the provincial suspected illegal cultivated land change map verification work, it is difficult to accurately judge with the naked eye by superimposing the image of the change spots, and it is necessary to conduct field verification to confirm the suspected problems, which greatly increased the work of manual inspections; in view of the normalization of cultivated land protection supervision work, a large number of manual inspections have entered a periodic and continuous cycle, and there are also some verified spots that need to be verified multiple times. In addition, the timeliness of manual inspections consumes a lot of time, manpower, and material resources, and it is difficult to achieve timely prevention of cultivated land destruction; therefore, increasing the research on preliminary screening technical means for suspected problem spots, quickly identifying the actual situation of the change spots, accurately eliminating the spots that do not need to be paid attention to during the inspection, and improving the efficiency of problem spot verification and disposal has become a more difficult problem for industry personnel.

[0004] With the continuous development of camera monitoring methods, monitoring project research based on PTZ (Pan / Tilt / Zoom, horizontal rotation / tilt angle / lens focal length) cameras and various sensors has gradually emerged both at home and abroad.

[0005] Therefore, due to the limitations of existing technology, people cannot solve it. Summary of the invention

[0006] (I) Purpose of the invention: In order to solve the problems existing in the above-mentioned prior art, the purpose of the present invention is to provide an online verification and monitoring system and method for cultivated land change maps, which meets the real-time, high-definition, high-frequency, wide-coverage and normalized monitoring requirements of cultivated land protection investigation and monitoring, solves the problems of low accuracy, untimely verification and slow response speed of existing similar monitoring technologies, and reduces manpower and time costs.

[0007] (II) Technical solution: In order to solve the above technical problems, this technical solution provides an online verification and monitoring system for cultivated land change spots, including a spot positioning unit, a camera matching unit, a position association unit and a spot verification unit;

[0008] The map spot positioning unit locates the three-dimensional geographic coordinates of the vector map spots of suspected illegal changes in farmland protection;

[0009] The camera matching unit matches the adapted PTZ camera according to the three-dimensional geographic coordinates of the spots obtained by the spot positioning unit; and determines the P, T, and Z values ​​of the camera according to the selected PTZ camera geographic location and the three-dimensional geographic coordinates of the spots; when the suspected spots of cultivated land protection are clustered batch spots, the batch spots are integrated into a large spot A. 整合 , calculate the image spot A of the PTZ camera relative to the batch image spot integration 整合 P 整合 Value, T 整合 Value, Z 整合 Value; According to the spot A on the three-dimensional map 整合 The spatial distance direction between the center point position and the virtual camera position, and the azimuth angle are used as the P of the PTZ camera. 整合 value, the pitch angle as the T of the PTZ camera 整合 Value; use the MAX and MIN functions to get the Z value of each spot [Z min ,Z max ], sort the spots according to Z min and Z max Determine different segments and determine different Z values ​​for different segments as the Z of the segment 整合 value;

[0010] The position association unit converts the three-dimensional geographic coordinates of the image spot into the pixel coordinates of the PTZ camera, and marks the corresponding image spot position on the PTZ camera image;

[0011] The image spot checking unit includes an image spot database, and the checked illegal image spots are stored in the image spot database.

[0012] Preferably, the spot positioning unit first obtains the vector map spot of suspected illegal changes in farmland protection; then locates the three-dimensional geographical location of the vector map spot of suspected illegal changes in farmland protection to obtain the three-dimensional geographical coordinates of the spot.

[0013] Preferably, the map spot positioning unit determines the longitude and latitude position information of the acquired vector map spot of suspected illegal changes in farmland protection, and obtains the elevation data of the area corresponding to the vector map spot of suspected illegal changes in farmland protection, and uses GIS software to combine the longitude and latitude position information of the vector map spot of suspected illegal changes in farmland protection with the elevation data to construct a three-dimensional geographic coordinate system, assigns corresponding elevation values ​​to the vertices of the vector map spot of suspected illegal changes in farmland protection, and obtains the three-dimensional geographic coordinates of the map spot.

[0014] Preferably, the camera matching unit performs a spatial query within the first buffer area around the suspected illegal change spot, matches the PTZ cameras in the first buffer area, performs line of sight analysis and visual area analysis for the selected camera based on elevation data, uses ray in Cesium to pick up points on the map to determine whether there are obstacles between the camera and the spot, determines whether the spot position is visible, and selects the PTZ camera in the best position as the spot observation camera.

[0015] Preferably, the azimuth angle α and pitch angle β in the spatial coordinate system with the virtual camera position as the origin are calculated based on the spatial distance direction between the center point of the target spot on the three-dimensional map and the virtual camera position; the azimuth angle α is used as the P value of the virtual camera, and the pitch angle β is used as the T value of the virtual camera.

[0016] Preferably, according to the relative position of the virtual camera and the image spot, the zoom factor of the PTZ camera is adjusted to focus on observing the target image spot. According to different Z values, the screen coordinates of the four viewing points of the upper left, lower left, upper right and lower right are converted into world coordinates, and the relationship with the vector image spot is calculated. The maximum value of the Z value when the vector image spot is included is determined as the Z value.

[0017] Preferably, according to the actual area size, select the Z value that can view the largest number of batches of spots at one time; when the interval requirements are met, select a smaller Z value; select a smaller Z value; when the same spot can be viewed at different Z values, select a smaller Z value.

[0018] Preferably, for each visible clustered batch of spots, the maximum Z value of each spot is determined by the MAX function: Z max , use the MIN function to determine the minimum Z value of each containing the spot: Z min , including batch patches A 整合 Maximum Z value: Z 整合 .

[0019] Preferably, the maximum Z value and the minimum Z value of each spot are sorted, and when Z 整合 ≥ Maximum Z min , Z整合 All the spots under the value are visible, and the corresponding P is adjusted i T i That is, you can view the corresponding spots;

[0020] When Z imin ≤Z 整合 ≤Z i , at this time only part of the image is visible, then determine Z 整合 value, adjust the corresponding P and T values ​​to view the corresponding spots; for the spots that cannot be seen, you need to reselect the appropriate Z value: Z 1 Value, Z 1 >Z 整合 , when Z jmin ≤Z 1 ≤Z jmax , then some spots are visible again, adjust the corresponding P and T values ​​to view the corresponding spots; if some spots are still not visible, continue to determine Z 2 Value, Z 2 >Z 1 , when Z kmin ≤Z 2 ≤Z kmax At this time, some spots are visible. Adjust the corresponding P and T values ​​to view the corresponding spots, and so on, until all spots are visible.

[0021] A method for online verification and monitoring of cultivated land change spots, applicable to the above-mentioned online verification and monitoring system of cultivated land change spots, specifically comprises the following steps:

[0022] Step 1, the map spot positioning unit locates the three-dimensional geographic coordinates of the vector map spot of suspected illegal changes in farmland protection;

[0023] Step 2, the camera matching unit matches the adapted PTZ camera according to the three-dimensional geographic coordinates of the image spot obtained by the image spot positioning unit;

[0024] Step 3: The camera matching unit determines the P, T, and Z values ​​of the camera according to the selected PTZ camera geographic location and the three-dimensional geographic coordinates of the image spot; when the suspected image spot for farmland protection is a clustered batch of image spots, the batch of image spots are integrated into a large image spot A. 整合 , calculate the image spot A of the PTZ camera relative to the batch image spot integration 整合 P 整合 Value, T 整合 Value, Z 整合 Value; According to the spot A on the three-dimensional map 整合 The spatial distance direction between the center point position and the virtual camera position, and the azimuth angle are used as the P of the PTZ camera. 整合 value, the pitch angle as the T of the PTZ camera 整合Value; use the MAX and MIN functions to get the Z value of each spot [Z min ,Z max ], sort the spots according to Z min and Z max Determine different segments and determine different Z values ​​for different segments as the Z of the segment 整合 value;

[0025] Step 4, the position association unit converts the three-dimensional geographic coordinates of the image spot into the pixel coordinates of the PTZ camera, and marks the corresponding image spot position on the PTZ camera image;

[0026] Step 5: The image spot checking unit checks the illegal image spots and stores them in the image spot database.

[0027] (III) Beneficial effects: The present invention provides a system and method for online verification and monitoring of cultivated land change spots. First, by combining PTZ cameras and three-dimensional maps, a high degree of interaction and integration of the virtual world based on video is achieved, and the consistency of video and three-dimensional maps in time and space is established, which provides a realistic scene for online verification of suspected illegal spots. Secondly, the three-dimensional geographic location of the suspected illegal spots is transformed into a specific PTZ camera monitoring scene, and a spot file is established to facilitate the identification of repeated spots and key area spots, facilitate the handling and tracking of illegal change spots, and regular monitoring and management, effectively reducing workload and improving efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a structural diagram of an online verification and monitoring system for cultivated land change patterns of the present invention;

[0029] Figure 2 This is a flow chart of a method for online checking and monitoring of cultivated land change spots of the present invention;

[0030] Figure 3 It is the observation pattern of the matching PTZ camera;

[0031] Figure 4 It is a schematic diagram of the method for determining P value and T value;

[0032] Figure 5 It is a schematic diagram of the method of determining different Z values;

[0033] Figure 6 It is a schematic diagram that the integrated Z value of batch patches is greater than the minimum Z value of all patches;

[0034] Figure 7 It is a schematic diagram that the integrated Z value of batch patches is greater than the minimum Z value of all patches;

[0035] Figure 8This is a schematic diagram of the conversion of world coordinates into pixel coordinates. DETAILED DESCRIPTION

[0036] The present invention is further described in detail below in conjunction with preferred embodiments. More details are elaborated in the following description to facilitate a full understanding of the present invention. However, the present invention can obviously be implemented in a variety of other ways different from the description. Those skilled in the art can make similar generalizations and deductions based on actual application situations without violating the connotation of the present invention. Therefore, the protection scope of the present invention should not be limited by the content of this specific embodiment.

[0037] The accompanying drawings are schematic diagrams of embodiments of the present invention. It should be noted that the drawings are only examples and are not drawn to scale, and should not be used to limit the actual protection scope of the present invention.

[0038] An online verification and monitoring system for cultivated land change maps, such as Figure 1 As shown, it includes a spot positioning unit, a camera matching unit, a position association unit and a spot verification unit. The spot positioning unit locates the three-dimensional geographic coordinates of the vector map spots of suspected illegal changes in farmland protection. The camera matching unit matches the adapted PTZ camera according to the three-dimensional geographic coordinates of the spots obtained by the spot positioning unit; and also determines the P, T, and Z values ​​of the camera according to the selected PTZ camera geographic location and the three-dimensional geographic coordinates of the spots. The position association unit converts the three-dimensional geographic coordinates of the spots into pixel coordinates of the PTZ camera, and marks the corresponding spot position on the image of the PTZ camera. The spot verification unit includes a spot database, and the verified illegal spots are stored in the spot database to facilitate key spot inquiries, illegal event tracking and normalized supervision of key areas.

[0039] A method for online verification and monitoring of cultivated land change spots, applicable to the online verification and monitoring system of cultivated land change spots, such as Figure 2 As shown, the specific steps include:

[0040] Step 1: The map spot positioning unit locates the three-dimensional geographic coordinates of the vector map spots of suspected illegal changes in farmland protection.

[0041] Step 2: The camera matching unit matches the adapted PTZ camera according to the three-dimensional geographic coordinates of the pattern obtained by the pattern positioning unit.

[0042] Step 3: The camera matching unit determines the P, T, and Z values ​​of the camera according to the geographical location of the selected PTZ camera and the three-dimensional geographical coordinates of the image spot.

[0043] Step 4: The position association unit converts the three-dimensional geographic coordinates of the image spot into PTZ camera pixel coordinates, and marks the corresponding image spot position on the PTZ camera image.

[0044] Step 5: The image spot checking unit checks the illegal image spots and stores them in the image spot database.

[0045] More specifically, the specific operation of the spot positioning unit in step 1 is:

[0046] Step 101, obtain the vector map of suspected illegal changes in farmland protection.

[0047] The vector spots of suspected illegal changes in farmland protection include but are not limited to the spots of suspected illegal changes in farmland protection issued by the national natural resources supervision department, the spots of suspected illegal changes submitted by the provincial level through satellite images or drone images through artificial intelligence identification and preliminary manual interpretation, and the spots of suspected illegal changes reported by video alarms or discovered by the public.

[0048] The suspected illegal changes in farmland protection vector map is also vector data, which is a series of lines connected by points. It is generally a geographic vector range outlined on a topographic map and is stored using Shapefile or GeoJSON. The suspected illegal changes in farmland protection vector map is a terrain range with longitude and latitude coordinates.

[0049] Step 102: locate the three-dimensional geographic location of the vector map patch of suspected illegal changes in farmland protection, and obtain the three-dimensional geographic coordinates of the map patch.

[0050] First, determine the longitude and latitude position information of the acquired vector map of suspected illegal changes in cultivated land protection, and obtain the elevation data of the corresponding area of ​​the vector map of suspected illegal changes in cultivated land protection, and use GIS software to combine the longitude and latitude position information of the vector map of suspected illegal changes in cultivated land protection with the elevation data of each point, and construct a three-dimensional geographic coordinate system, so as to assign corresponding elevation values ​​to the vertices of the vector map of suspected illegal changes in cultivated land protection, thereby converting the two-dimensional longitude and latitude coordinates of the vector map of suspected illegal changes in cultivated land protection into three-dimensional geographic coordinates. The vector map of suspected illegal changes in cultivated land protection that has been converted into three-dimensional geographic coordinates is superimposed with high-resolution satellite remote sensing images to form a three-dimensional spatial structure of the vector map of suspected illegal changes in cultivated land protection.

[0051] The longitude and latitude position information of the vector map of suspected illegal changes in farmland protection is usually stored in a vector data format, which can be Shapefile, GeoJSON, etc. The elevation data (DEM), called absolute elevation, refers to the distance from a point to the absolute base surface along the plumb line, which can be obtained through a digital elevation model. The three-dimensional image data can be drone aerial photography, satellite remote sensing images, etc. The GIS software can be ArcGIS, QGIS, etc. There are no specific restrictions on the above, as long as the corresponding operations can be performed and the required results are obtained. The high-resolution satellite remote sensing image mainly refers to a world map or a three-dimensional base map based on satellite remote sensing image processing.

[0052] More specifically, the specific operation of the camera matching unit matching the PTZ camera in step 2 is:

[0053] In view of the complexity of the geometric relationship between the camera field of view and the target spot position, it is necessary to select the camera based on the spot position information. Perform a spatial query in the first buffer area around the suspected illegal change spot and match the PTZ camera in the first buffer area. Perform line of sight analysis and visual area analysis on the selected camera based on the elevation data, use ray in Cesium to pick up points on the map to determine whether there are obstacles between the PTZ camera and the suspected illegal change spot, determine whether the spot position is visible, and select the PTZ camera in the best position as the spot observation camera, such as Figure 3 shown.

[0054] The PTZ camera in the best position at least meets the following conditions: First, within the field of view of the PTZ camera, with the PTZ camera position as the center, divide the first buffer area according to the field of view parameters of the PTZ camera, and filter out the PTZ cameras that meet the spatial position: the first screening camera. Then, according to the ray in Cesium, select the PTZ camera with no obstacles between it and the suspected illegal change pattern, and then filter out the PTZ cameras with visible suspected illegal change patterns from the first screening camera: the second screening camera. Finally, select the PTZ camera with the closest position, clear view, and full viewing angle: the PTZ camera in the best position.

[0055] The first buffer area refers to the farthest observation distance of the PTZ camera, which is preferably 10 km in the present invention.

[0056] In security monitoring applications, PTZ is the abbreviation of Pan / Tilt / Zoom, which represents the full-scale (left / right / up / down) movement of the pan / tilt and the zoom and zoom control of the lens. The PTZ camera refers to a camera that can perform full-scale movement of the pan / tilt and zoom and zoom control of the lens. Most PTZ cameras are high-tower PTZ cameras, which have the advantages of multiple stations, high towers, and real-time high definition. Combined with the full-scale movement of the pan / tilt and the zoom and zoom control functions of the lens, the shooting angle, coverage range and clarity can be changed at any time to obtain better overall and local high-definition monitoring effects.

[0057] More specifically, the specific operation of the camera matching unit in step 3 is:

[0058] First, according to the actual spatial position of the selected PTZ camera, calibrate the virtual camera corresponding to the PTZ camera in the three-dimensional geographic coordinate system. Use the virtual camera as the origin to build a spatial coordinate system, calculate the azimuth angle α and the pitch angle β between the virtual camera and the image spot, and use the azimuth angle α as the P value of the PTZ camera and the pitch angle β as the T value of the PTZ camera. Assign the P value and T value to the PTZ camera, and synchronously associate the virtual camera with the PTZ camera. By changing the focal length of the PTZ camera, different Z values ​​are obtained, and the maximum Z value when the image spot is included is determined, which is the Z value of the PTZ camera.

[0059] Synchronizing the virtual camera with the PTZ camera mainly involves synchronizing the camera's field of view, field of view height, far-sightedness, near-sightedness, orientation p, pitch angle t, magnification, etc., to the virtual camera in the three-dimensional system. The position and orientation of the virtual camera must closely match the position and orientation of the actual PTZ camera, and its tracking information must match the exact timing of the video content to ensure that each video frame is accurately synchronized to the position of the camera at each moment, accurately simulating a PTZ camera used to capture real-world video footage.

[0060] More specifically, Figure 4 As shown, according to the spatial distance direction O′A′ between the center point of the target spot and the virtual camera position on the three-dimensional map, the azimuth angle α and the pitch angle β of O′A′ in the spatial coordinate system with the virtual camera position as the origin are calculated. That is, in the three-dimensional rectangular coordinate system constructed with the virtual camera position as the origin, the acute angle between the projection of the straight-line distance between the center point of the target spot and the spatial distance direction O′A′ of the virtual camera position on the same height plane and the azimuth direction is taken as the azimuth angle α, and the angle between the spatial distance direction O′A′ between the center point of the target spot and the virtual camera position and its projection is taken as the pitch angle β.

[0061] The azimuth angle α is used as the P value of the virtual camera, and the pitch angle β is used as the T value of the virtual camera. The P and T values ​​are then assigned to the PTZ camera through remote operation.

[0062] like Figure 5 As shown, refer to the relative position of the virtual camera and the image spot in the three-dimensional map, adjust the zoom factor of the PTZ camera to focus on the target image spot, use CG rendering and real-time video to create an accurate composition, and obtain the position, height, PTZ value, camera resolution, camera field of view and other parameters of the camera. According to different Z values, the screen coordinates of the four viewpoints of the upper left, lower left, upper right and lower right are converted into world coordinates, and the relationship calculation is performed with the vector image spot. The maximum value of the Z value when the vector image spot is included is determined as the Z value.

[0063] When the suspected cultivated land protection spots are clustered batch spots, it is necessary to integrate the batch spots into a large spot A if the batch spots are dense in the area. 整合 , calculate the image spot A of the PTZ camera relative to the batch image spot integration 整合 P 整合 Value, T 整合 Value, Z 整合 value.

[0064] For P 整合 Value, T 整合 Value: Still based on the map spot A on the 3D map 整合 The spatial distance direction between the center point position and the virtual camera position is calculated, and the azimuth angle α and pitch angle β in the spatial coordinate system with the virtual camera position as the origin are calculated. The azimuth angle α is used as the P 整合 value, the pitch angle β is the T of the PTZ camera 整合 Value. And for Z 整合 Value: The appropriate Z value is determined based on the actual situation of each spot. 整合 value, and perform batch image segmentation with the best viewing angle.

[0065] The Z value of each spot is obtained by using the MAX and MIN functions. min ,Z max ], when n batches of clustered spots, a total of n sets of values ​​[Z 1min ,Z 1max ],[Z 2min ,Z 2max ],[Z 3min ,Z 3max ],[Z 4min ,Z 4max ],[Z 5min ,Z 5max ],[Z 6min ,Z6max ]……[Z nmin ,Z nmax ]. Assume that the visible clustered batch spots are a, b, c, d, e, f, g, and h. For each visible clustered batch spot, use the MAX function to determine the maximum Z value of each spot: Z amax , Z bmax , Z cmax , Z dmax , Z emax , Z fmax , Z gmax , Z hmax According to the same method, the MIN function is used to determine the minimum Z value of each containing spot: Z amin , Z bmin , Z cmin , Z dmin , Z emin , Z fmin , Z gmin , Z hmin Similarly, when determining the inclusion of batch spots, A 整合 Maximum Z value: Z 整合 .

[0066] Use RANK or RANK.EQ to sort the maximum and minimum Z values ​​of each patch from small to large. imin / jmax ), according to Z min and Z max Determine in sequence (Z imin ≤Z jmin…… ≤Z kmin )≤Z≤(Z omax ≤Z pmax…… ≤Z qmax ) segment, and determine different maximum Z values ​​for different segments as the Z value of this segment, where: the number of Z values ​​depends on the number of segments; the visible spots are (i, j...k) and (o, p...q), and the best Z value is the spot A after the corresponding visible spots (i, j...k, o, p...q) are integrated 整合 The maximum value Z 整合 .

[0067] like Figure 6 As shown, Z dmin <Z emin <Z fmin <Z cmin <Z hmin <Z bmin <Z gmin <Z amin <Z emax <Z hmax <Z dmax <Z fmax <Zgmax <Z amax <Z cmax <Z bmax , when Z 整合 ≥ Maximum Z min , at this time Z 整合 Than the smallest Z among all the spots min If it is still large, then determine P 整合 , T 整合 , Z 整合 All the spots a, b, c, d, e, f, g, h are visible under the value, and the corresponding P is adjusted. i T i You can view the corresponding spots.

[0068] When Z imin ≤Z 整合 ≤Z i , at this time only part of the image is visible, for example, a and h meet the requirements, then determine Z 整合 value, adjust the corresponding P a T a , P h T h Check the corresponding spots. For the spots that cannot be seen, you need to reselect the appropriate Z value and re-determine the Z 1 Value, Z 1 >Z 整合 , when Z jmin ≤Z 1 ≤Z jmax , and some spots are visible, such as b, d, f, and g, which meet the requirements. Adjust the corresponding P b T b , P d T d , P f T f , P g T g You can view the corresponding image spot and surrounding areas. If some of the image spots are still not visible, continue to determine the Z 2 Value, Z 2 >Z 1 , when Z kmin ≤Z 2 ≤Z kmax , at this time, some spots are visible, such as c and e meet the requirements, and the corresponding P is adjusted c T c , P e T e You can view the corresponding image spot and the surrounding area. If there are still image spots that are not visible at this time, then determine Z 3 Value, Z 3 >Z 2 , continue to adjust and view the corresponding spots.

[0069] It should be noted that for Z 1 , Z 2 , Z 3 The determination of the numerical values ​​follows the following rules: according to the actual area size, choose the appropriate Z value as much as possible to view as many batches of spots as possible at one time; when the interval requirements are met, choose the smallest Z value possible to increase the degree of clustering of visible spots; when the first two conditions are met, choose the smallest Z value possible to improve the efficiency of online verification; when the same spot can be viewed at different Z values, try to choose the smaller Z value for verification.

[0070] like Figure 7 As shown, Z hmin <Z amin <Z hmax <Z fmin <Z dmin <Z bmin <Z amax <Z gmin <Z fmax <Z dmax <Z bmax <Z cmin <Z emin <Z gmax <Z cmax <Z emax According to the above rules: Z hmin <Z amin <Z hmax , Z amin <Z 1 <Z hmax , in Z 1 The values ​​of Z are a and h. 1 The value is a, h patch integration A 1整合 Z 1整合 Value. Z fmin <Z dmin <Z bmin <Z amax <Z gmin <Z fmax <Z dmax <Z bmax ,

[0071] Z 1 The visible spots a and h of the value are not considered, and Z gmin <Z 2 <Z fmax , in Z 2 The spots b, d, f, and g can be seen under the value; Z 2 The value is b, d, f, g patch integration A 2整合 Z 2整合 Value. Z cmin <Zemin <Z gmax <Z cmax <Z emax , it can be seen that spots a, b, d, f, g, h are not considered, Z emin <Z 3 <Z gmax , in Z 3 The spots c and e can be seen under the value; Z 3 The value is c, e patch integration A 3整合 Z 3整合 From this, we can know that the three Z values ​​of spots a, b, c, d, e, f, g, and h can be determined as needed, which are Z 1、 Z 2、 Z 3 .

[0072] More specifically, the specific operation of the position association unit in step 4 is:

[0073] like Figure 8 As shown, firstly, the three-dimensional geographic coordinates of the image spot are converted into PTZ camera coordinates, that is, the position of the image spot is converted from the three-dimensional geographic coordinate system into a coordinate system with the optical center of the PTZ camera as the origin, and the PTZ camera coordinates are also three-dimensional coordinates.

[0074] Secondly, through the perspective projection relationship, the PTZ camera coordinates are converted into two-dimensional image coordinates, that is, the position of the image spot is converted from the coordinate system with the optical center of the PTZ camera as the origin into the coordinate system with the intersection of the PTZ camera optical axis and the image physical coordinate system as the origin through the projection relationship.

[0075] Finally, the pixel coordinates on the PTZ camera screen are generated through secondary conversion, and the corresponding spot position is identified on the PTZ camera image through the relationship between the three-dimensional geometric position and its corresponding point in the image.

[0076] More specifically, the specific operation of the spot checking unit in step 5 is:

[0077] The spot verification unit verifies the input suspected illegal spots of farmland protection, determines the illegal occupation and area of ​​the suspected illegal change spots, and then stores the verified spot information in the illegal spot database.

[0078] The image spot information includes time, personnel, image spot information, matching PTZ value camera, PTZ value, verification results, images and videos, transfer status and other information.

[0079] More preferably, the image patch verification unit may also include an AI alarm algorithm model, which can carry out regular monitoring of important images and key areas according to the aggregation of key images, and display monitoring information and issue alarm information through a variety of means such as a monitoring center, mobile phone APP and Web terminal, so as to conduct more comprehensive multi-mode monitoring and multi-path display, and can more efficiently identify illegal occupation of cultivated land and respond in a timely manner.

[0080] The spot checking unit also includes a checking sequence table. When the suspected spots for farmland protection are clustered batch spots, each spot in the batch is checked according to the checking sequence table to determine whether the batch spots are illegal spots, and the corresponding spot information is output and stored in the illegal spot library.

[0081] Specifically, the spot verification unit sets different verification sequence identifiers for different administrative regions, and sets different verification priorities according to the spot area based on the different verification sequence identifiers. The spot information corresponding to different verification sequence identifiers is encapsulated into different class objects, and the different class objects are respectively mounted to the spot information, and the class objects corresponding to different verification sequence identifiers are independent of each other. Each spot is verified, and the verification result is fed back to the spot information list corresponding to the corresponding spot.

[0082] First, the spots are distinguished in order according to the provincial, prefectural, county, and township levels, and the verification series identifiers corresponding to different vector spots are obtained. A spot corresponds to a unique verification sequence identifier. Then the verification priority is sorted according to the size of the spot. The larger the spot area, the higher the verification priority, that is, the larger the spot area, the earlier the verification; the smaller the spot area, the lower the verification priority, that is, the smaller the spot area, the later the verification order.

[0083] The corresponding spot difference ratio is obtained according to the ratio of the spot input by the client and the spot information stored in the illegal spot library. When the spot difference ratio is less than or equal to the difference ratio threshold, it indicates that the corresponding spot is similar or identical to the spot in the illegal spot library. At this time, the difference ratio corresponding to the spot is output to the client, and the spot difference product is obtained by calculation based on the spot area and the spot difference ratio. The spot difference product is sorted in a certain order, and the frame synchronization calculation of the difference contour is performed according to the spot difference product. The final result is output to the client and stored in the illegal spot library. When the spot difference ratio is greater than the spot difference ratio threshold, it indicates that the corresponding spot is not similar to the spot in the illegal spot library. At this time, the spot is not an illegal spot, and the result is directly output to the client.

[0084] The spot difference ratio is a value greater than or equal to 0 and less than or equal to 1. When the spot difference ratio is equal to 0, it indicates that the spot input by the client at this time is completely different from the spot stored in the illegal spot library; when the spot difference ratio is equal to 1, it indicates that the spot input by the client at this time is completely the same as the spot stored in the illegal spot library.

[0085] The calculation of the difference profile is performed through frame synchronization, and consistent logic is applied to drive all states to update synchronously. Only the client needs to manage and maintain its own information. As long as the suspected illegal spots are input, the verification results and the difference profile of the spots can be obtained by running it by itself.

[0086] The present invention uses frame synchronization to calculate and display the difference profile in real time on the client in a frame-by-frame order, thereby reducing the workload of the server. Frame synchronization has a certain anti-interference ability, and the whole process is faster, more convenient, and more in line with the actual use process.

[0087] The present invention provides an online verification and monitoring system and method for cultivated land change spots. First, based on the PTZ camera video or image sequence, it can truly and dynamically reflect the objective world, and the three-dimensional map can reflect the three-dimensional structure of the actual scene. The two are combined to achieve a high degree of interaction and integration of the video-based virtual world, and establish the consistency of the video and the three-dimensional map in time and space, which is a realistic scene for the online verification of suspected illegal spots. Secondly, the three-dimensional geographical location of the suspected illegal spots is transformed into a specific PTZ camera monitoring scene, and the number, date, location, violation, and disposal process of the spots are associated with the number, location, posture, and PTZ value of the corresponding PTZ camera. A spot file is established to facilitate the identification of repeated spots and key area spots, and to facilitate the tracking of illegal change spot disposal and regular monitoring and management, effectively reducing workload and improving efficiency.

[0088] The above content is an explanation of the preferred embodiments of the present invention, which can help those skilled in the art to more fully understand the technical solution of the present invention. However, these embodiments are merely illustrative, and it cannot be determined that the specific implementation methods of the present invention are limited to the description of these embodiments. For ordinary technicians in the technical field to which the present invention belongs, without departing from the concept of the present invention, several simple deductions and transformations can be made, which should be regarded as belonging to the protection scope of the present invention.

Claims

1. An online verification and monitoring system for cultivated land change patterns, characterized in that: It includes a spot positioning unit, a camera matching unit, a position association unit and a spot verification unit; The map spot positioning unit locates the three-dimensional geographic coordinates of the vector map spots of suspected illegal changes in farmland protection; The camera matching unit matches the adapted PTZ camera according to the three-dimensional geographic coordinates of the spots obtained by the spot positioning unit; and determines the P, T, and Z values ​​of the PTZ camera according to the selected PTZ camera geographic location and the three-dimensional geographic coordinates of the spots; when the suspected spots of cultivated land protection are clustered batch spots, the batch spots are integrated into a large spot A. 整合 , calculate the image spot A of the PTZ camera relative to the batch image spot integration 整合 P 整合 Value, T 整合 Value, Z 整合 Value; According to the spot A on the three-dimensional map 整合 The spatial distance direction between the center point position and the virtual camera position, and the azimuth angle are used as the P of the PTZ camera. 整合 value, the pitch angle as the T of the PTZ camera 整合 Value; use the MAX and MIN functions to get the Z value of each spot [Z min ,Z max ], sort the spots according to Z min and Z max Determine different segments and determine different Z values ​​for different segments as the Z of the segment 整合 value; according to the relative position of the virtual camera and the image spot, adjust the zoom multiple of the PTZ camera to focus on the target image spot, and according to different Z values, convert the screen coordinates of the four viewpoints of the upper left, lower left, upper right and lower right into world coordinates, calculate the relationship with the vector image spot, and determine the maximum value of the Z value when the vector image spot is included as the Z value; according to the actual area size, select the Z value that can view the largest number of image spots at one time; if the interval requirements are met, select a small Z value; select a small number of Z values; if the same image spot can be viewed at different Z values, select a small Z value; Sort the maximum and minimum Z values ​​of each patch. 整合 ≥ Maximum Z min , Z 整合 All the spots under the value are visible, and the corresponding P is adjusted i T i Check the corresponding spots; When Z imin ≤Z 整合 ≤Z imax , then determine Z 整合 value, adjust the corresponding P and T values ​​to view the corresponding spots; for the spots that cannot be seen, you need to reselect the Z value: Z1 value, Z1>Z 整合 , when Z jmin ≤Z1≤Z jmax , then some spots are visible again, adjust the corresponding P and T values ​​to view the corresponding spots; when some spots are still invisible, continue to determine the Z2 value, Z2>Z1, when Z kmin ≤Z2≤Z kmax , adjust the corresponding P and T values ​​to view the corresponding spots, and so on, until all spots are visible; The position association unit converts the three-dimensional geographic coordinates of the image spot into the pixel coordinates of the PTZ camera, and marks the corresponding image spot position on the PTZ camera image; The image spot checking unit includes an image spot database, and the checked illegal image spots are stored in the image spot database.

2. The online verification and monitoring system for cultivated land change patterns according to claim 1 is characterized in that: The spot positioning unit first obtains the vector spot of suspected illegal changes in farmland protection; then locates the three-dimensional geographical location of the vector spot of suspected illegal changes in farmland protection to obtain the three-dimensional geographical coordinates of the spot.

3. The online verification and monitoring system for cultivated land change patterns according to claim 2 is characterized in that: The map spot positioning unit determines the longitude and latitude position information of the acquired vector map spot of suspected illegal changes in farmland protection, and obtains the elevation data of the area corresponding to the vector map spot of suspected illegal changes in farmland protection, and uses GIS software to combine the longitude and latitude position information of the vector map spot of suspected illegal changes in farmland protection with the elevation data to construct a three-dimensional geographic coordinate system, assign corresponding elevation values ​​to the vertices of the vector map spot of suspected illegal changes in farmland protection, and obtain the three-dimensional geographic coordinates of the map spot.

4. The online verification and monitoring system for cultivated land change patterns according to claim 1 is characterized in that: The camera matching unit performs a spatial query in the first buffer area around the suspected illegal change spot, matches the PTZ camera in the first buffer area, performs line of sight analysis and visual area analysis on the selected camera based on elevation data, uses ray in Cesium to pick up points on the map to determine whether there are obstacles between the camera and the spot, determines whether the spot position is visible, and selects the PTZ camera in the best position as the spot observation camera.

5. The online verification and monitoring system for cultivated land change patterns according to claim 1 is characterized in that: According to the spatial distance direction between the center point of the target spot on the three-dimensional map and the position of the virtual camera, the azimuth angle α and pitch angle β in the spatial coordinate system with the virtual camera position as the origin are calculated; the azimuth angle α is used as the P value of the virtual camera, and the pitch angle β is used as the T value of the virtual camera.

6. The online verification and monitoring system for cultivated land change patterns according to claim 1 is characterized in that: For each visible clustered batch of spots, the MAX function is used to determine the maximum Z value of each spot: Z max , use the MIN function to determine the minimum Z value of each containing the spot: Z min , including batch patches A 整合 Maximum Z value: Z 整合 .

7. A method for online verification and monitoring of cultivated land change spots, applicable to an online verification and monitoring system for cultivated land change spots, characterized in that: The specific steps include: Step 1: The map location unit locates the three-dimensional geographic coordinates of the vector map of suspected illegal changes in farmland protection; Step 2: The camera matching unit matches the adapted PTZ camera according to the three-dimensional geographic coordinates of the image spot obtained by the image spot positioning unit; Step 3: The camera matching unit determines the P, T, and Z values ​​of the camera according to the selected PTZ camera's geographic location and the three-dimensional geographic coordinates of the image patch; when the suspected image patch of cultivated land protection is a clustered batch of image patches, the batch of image patches are integrated into a large image patch A. 整合 , calculate the image spot A of the PTZ camera relative to the batch image spot integration 整合 P 整合 Value, T 整合 Value, Z 整合 Value; According to the spot A on the three-dimensional map 整合 The spatial distance direction between the center point position and the virtual camera position, and the azimuth angle are used as the P of the PTZ camera. 整合 value, the pitch angle as the T of the PTZ camera 整合 Value; use the MAX and MIN functions to get the Z value of each spot [Z min ,Z max ], sort the spots according to Z min and Z max Determine different segments and determine different Z values ​​for different segments as the Z of the segment 整合 value; according to the relative position of the virtual camera and the image spot, adjust the zoom multiple of the PTZ camera to focus on the target image spot, and according to different Z values, convert the screen coordinates of the four viewpoints of the upper left, lower left, upper right and lower right into world coordinates, calculate the relationship with the vector image spot, and determine the maximum value of the Z value when the vector image spot is included as the Z value; according to the actual area size, select the Z value that can view the largest number of image spots at one time; if the interval requirements are met, select a small Z value; select a small number of Z values; if the same image spot can be viewed at different Z values, select a small Z value; Sort the maximum and minimum Z values ​​of each patch. 整合 ≥ Maximum Z min , Z 整合 All the spots under the value are visible, and the corresponding P is adjusted i T i Check the corresponding spots; When Z imin ≤Z 整合 ≤Z imax , then determine Z 整合 value, adjust the corresponding P and T values ​​to view the corresponding spots; for the spots that cannot be seen, you need to reselect the Z value: Z1 value, Z1>Z 整合 , when Z jmin ≤Z1≤Z jmax , then some spots are visible again, adjust the corresponding P and T values ​​to view the corresponding spots; when some spots are still invisible, continue to determine the Z2 value, Z2>Z1, when Z kmin ≤Z2≤Z kmax , adjust the corresponding P and T values ​​to view the corresponding spots, and so on, until all spots are visible; Step 4: The position association unit converts the three-dimensional geographic coordinates of the image spot into the pixel coordinates of the PTZ camera, and marks the corresponding image spot position on the PTZ camera image; Step 5: The image spot verification unit verifies the illegal image spots and stores them in the image spot database.

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