Authentication method and system for acquiring land parcel information based on image

Abstract

The invention discloses a right determination method for acquiring land parcel information based on an image, and the method is characterized in that the method comprises the following steps: obtaining a remote sensing image of a land parcel with an insurance range, coloring the area of the insurance range, and drawing a bounding rectangle; an OpenCV image recognition technology is utilized, and the image coordinate of each vertex of the coloring area is calculated; calculating image coordinates of four points of the bounding rectangle according to known information; acquiring longitude and latitude information of four points of the external rectangle; calculating four parameters according to the obtained longitudes and latitudes of the four points of the external rectangle and the image coordinates of the four points; and calculating the geographic coordinate corresponding to each image coordinate according to the image coordinate of each vertex of the coloring area and the calculated four parameters, and by adopting the method, an agricultural insurance company can be helped to quickly obtain an accurate land parcel geographic range, formulate a reasonable premium rate, improve the underwriting and claim settlement efficiency, reduce manual operation and reduce the operation cost, so that the economic benefit of the agricultural insurance company is improved. Area is quickly determined, and claim settlement speed and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of digital agriculture, and particularly to a method and system for land right confirmation based on image acquisition of plot information. Background Art

[0002] Digital agriculture refers to the organic combination of high-tech such as remote sensing, geographic information system, global positioning system, computer technology, communication and network technology, and automation technology with basic disciplines such as geography, agronomy, ecology, plant physiology, and soil science, so as to achieve real-time monitoring of crops and soil from macro to micro during the agricultural production process, to regularly obtain information on the growth, development status, pests and diseases, water and fertilizer status of crops and the corresponding environment, generate a dynamic spatial information system, simulate the phenomena and processes in agricultural production, and achieve the purpose of reasonably utilizing agricultural resources, reducing production costs, improving the ecological environment, and enhancing the quality of crop products.

[0003] Currently, in order to reduce planting risks, large-area agricultural growers usually purchase agricultural planting insurance for their crops, so as to obtain compensation from agricultural insurance companies in case of disasters, thereby reducing losses. When the agricultural insurance company underwrites, it needs to determine the farmers, insured land, insured area, etc. When it comes to the insured area, the agricultural insurance company needs to determine it. Usually, it is through manual on-site measurement. This method is accurate in measurement, but it is time-consuming and laborious. In the case of a large number of insured persons, this method will undoubtedly greatly increase the labor cost.

[0004] Therefore, there is an urgent need to design a method and system for land right confirmation based on image acquisition of plot information to overcome one or more of the above-mentioned deficiencies of the prior art. Summary of the Invention

[0005] The technical solution adopted by the present invention to achieve the above technical purpose is: a method for land right confirmation based on image acquisition of plot information, characterized by including the following steps:

[0006] S1. Obtain a remote sensing image of a plot with an insured scope, import it into an operation platform, pre-define the color of the insured scope area, and draw a circumscribed rectangle according to the colored range;

[0007] S2. Use the OpenCV image recognition technology to identify the colored area in the remote sensing image of the plot, and calculate the image coordinates of each vertex of the colored area;

[0008] S3. According to the vertex image coordinates obtained in step S2, calculate the image coordinates of the four points of the circumscribed rectangle;

[0009] S4. Obtain the longitude and latitude information of the four points of the circumscribed rectangle according to the reference objects corresponding to the area of the circumscribed rectangle;

[0010] S5. Select two of the longitude and latitude coordinates and image coordinates of the four points of the obtained circumscribed rectangle, and use the least squares method to calculate four parameters;

[0011] S6. Use the four-parameter transformation model formula with the image coordinates of each vertex in the colored area in step S2 and the four parameters calculated in step S5 to calculate the geographic coordinates corresponding to each image coordinate.

[0012] In a preferred embodiment, the image coordinate acquisition steps in step S2 are as follows:

[0013] S21. Read the remote sensing image and convert the remote sensing image from the BGR color space to the HSV color space;

[0014] S22. Set a threshold range for the colored area in the HSV color space;

[0015] S23. Use the cv2.inRange() function to segment the image according to the set threshold to obtain a binary image;

[0016] S24. Use the cv2.findContours() function to detect the contours in the binary image and analyze the contours to extract the contours of the colored area plot;

[0017] S25. For the contour of the colored area, use the cv2.approxPolyDP() function to approximate the contour and obtain the coordinates of each vertex.

[0018] In a preferred embodiment, in step S4, after obtaining the longitude and latitude information of the four points of the circumscribed rectangle, use the OCR recognition technology to extract the longitude and latitude information of the four points.

[0019] In a preferred embodiment, the four parameters in step S5 are respectively the X-axis translation parameter, the Y-axis translation parameter, the rotation parameter and the scale parameter.

[0020] In a preferred embodiment, the expression of the four-parameter transformation model in step S5 is:

[0021]

[0022] Among them, x1, y1 are the coordinates on the image; x2, y2 are the actual geographic coordinates; Δy, Δx are the translation parameters; α is the rotation parameter; m is the scale parameter.

[0023] The second aspect of the present invention provides a land parcel information confirmation system based on images, and the system includes:

[0024] Boundary delineation module: After obtaining the remote sensing image of the plot, it is used to predefine and color the insured area, and draw the circumscribed rectangle according to the colored area;

[0025] Coordinate calculation module: Using OpenCV image recognition technology, calculate the image coordinates of each vertex of the colored area, and synchronously calculate the image coordinates of the four points of the circumscribed rectangle;

[0026] Latitude and longitude acquisition module: Used to obtain the latitude and longitude information of the four points of the circumscribed rectangle according to the reference objects in the area corresponding to the circumscribed rectangle;

[0027] Coordinate conversion module: Used to calculate four parameters by using the least squares method according to the latitude and longitude information and image coordinates of the four points of the obtained circumscribed rectangle, and then substitute the known four parameters and the image coordinates of each vertex of the colored area into the four-parameter conversion model to calculate the geographic coordinates corresponding to each image coordinate.

[0028] The third aspect of the present invention provides an electronic device, including: at least one processor, at least one memory, a communication interface, and a bus; wherein, the processor, the memory, and the communication interface complete mutual communication through the bus; the memory stores program instructions executable by the processor, and the processor calls the program instructions to implement the method according to any one of claims 1 to 5.

[0029] The fourth aspect of the present invention provides a computer-readable storage medium, and the computer-readable storage medium stores computer instructions, and the computer instructions enable the computer to implement the method according to any one of claims 1 to 5.

[0030] The beneficial effects of the present invention are: It can help agricultural insurance companies obtain the accurate geographical scope of plots more quickly, formulate reasonable insurance rates, improve the efficiency of underwriting and claims settlement, and the process of agricultural insurance underwriting and claims settlement is more convenient and efficient. By electronically collecting and processing land information, manual operations can be reduced, operating costs can be lowered, the affected plots and areas can be quickly determined, and the speed and accuracy of claims settlement can be improved. Description of the Drawings

[0031] Figure 1 It is a flowchart of a method for confirming plot information based on images provided in Embodiment 1 of the present invention. Detailed Embodiments

[0032] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the specific embodiments of the present invention in detail with reference to the accompanying drawings. Many specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0033] In the description of the embodiments of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "connection" and "installation" should be understood in a broad sense. For example, "connection" can be a detachable connection or a non-detachable connection; it can be a direct connection or an indirect connection through an intermediate medium. In addition, "communication" can be a direct communication or an indirect communication through an intermediate medium. Among them, "fixing" means being connected to each other and the relative positional relationship after connection remains unchanged. The directional terms mentioned in the embodiments of the present invention, such as "inside", "outside", "top", "bottom", etc., are only with reference to the direction of the accompanying drawings. Therefore, the directional terms used are for better and clearer explanation and understanding of the embodiments of the present invention, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus cannot be understood as a limitation to the embodiments of the present invention.

[0034] In the embodiments of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features.

[0035] In the embodiments of the present invention, "and / or" is merely a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0036] References to "one embodiment" or "some embodiments" etc. described in this specification mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of the present invention. Thus, statements such as "in one embodiment", "in some embodiments", "in some other embodiments", "in still some other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0037] Embodiment 1

[0038] As Figure 1 shown, the present invention provides a method for confirming the rights of land parcels based on image acquisition, which is characterized by including the following steps:

[0039] S1. Obtain a remote sensing image of the land parcel with the insured scope, import it into the operation platform, pre-define the coloring of the insured scope area, and draw an external rectangle according to the coloring range;

[0040] S2. Use the OpenCV image recognition technology to identify the colored area in the remote sensing image of the land parcel, and calculate the image coordinates of each vertex of the colored area;

[0041] S3. According to the vertex image coordinates obtained in step S2, calculate the image coordinates of the four points of the external rectangle;

[0042] S4. Obtain the longitude and latitude information of the four points of the external rectangle according to the reference objects corresponding to the area of the external rectangle;

[0043] S5. Select two of the longitude and latitude and the image coordinates of the four points of the obtained external rectangle, and use the least squares method to calculate four parameters;

[0044] S6. Use the four-parameter transformation model formula with the image coordinates of each vertex of the colored area in step S2 and the four parameters calculated in step S5 to calculate the geographic coordinates corresponding to each image coordinate.

[0045] Specifically, the agricultural insurance company will provide a remote sensing image marked with the insured scope of the land. This remote sensing image only has the insured scope and no actual area, and a third party is required to calculate the land area. The calculation method is as follows:

[0046] After obtaining the joystick image, import the remote sensing image into the operation platform. The computer predefines the coloring of the insured area for subsequent identification, and draws an external rectangle based on the colored area. This external rectangle is the smallest rectangle of the colored area, that is, the sides of the external rectangle intersect with several of the most protruding vertices of the colored area. Subsequently, through the OpenCV image recognition technology, the colored area in the remote sensing image is recognized, and the image coordinates of each vertex of the colored area are calculated. This step also includes the following calculation methods:

[0047] S21. First, read the remote sensing image and convert the remote sensing image from the BGR color space to the HSV space. The HSV color space is more suitable for color threshold processing, and the HSV color space can separate color information from brightness information;

[0048] S22. In the HSV color space, set a threshold range for the predefined color. This range can be determined through experiments or obtained by analyzing the histogram of the image. In this embodiment, taking blue as an example, the blue range of HSV can be set from [100, 150, 0] to [140, 255, 255].

[0049] S23. Use the cv2.inRange() function to segment the image according to the set threshold to obtain a binary image, where the blue area is white and the other parts are black. Perform morphological operations on the binary image, such as erosion and dilation, to remove noise and fill the holes within the blue plot.

[0050] S24. Use the cv2.findContours() function to detect the contours in the binary image. These contours represent the boundaries of the blue area, and analyze the contours to extract the contours of the blue area.

[0051] S25. For the contours of the blue area, use the cv2.approxPolyDP() function to approximate the contours, thereby obtaining the coordinates of each vertex of each blue area. This function can approximate the contour as a polygon and return the vertex coordinates of the polygon.

[0052] Among them, the image coordinates are determined by the pixel position. Each pixel point has a unique coordinate in the image, expressed as (X, Y), where X is horizontally to the right and Y is vertically downward, and the coordinate origin is located at the upper left corner of the picture.

[0053] After obtaining the image coordinates of each vertex of the colored area, the image coordinates of the four points of the circumscribed rectangle can be calculated through these image coordinates. After obtaining the image coordinates of the four points of the circumscribed rectangle, the step of obtaining the longitude and latitude information of the four points of the circumscribed rectangle can be carried out; there are two ways to obtain the longitude and latitude information of the circumscribed rectangle; one is to use RTK technology to obtain the accurate longitude and latitude coordinates of the reference object corresponding to the colored area in the image on the ground. This requires using RTK equipment to measure on the ground to obtain centimeter-level positioning accuracy; the other is to select a platform that provides high-precision map services, such as Google Earth, ArcGIS Online or other professional geographic information systems, find the accurate location of the survey area in the map service, use the tools provided by the map service to obtain the coordinate points of the same reference object, so as to obtain the longitude and latitude information of the four points of the circumscribed rectangle. In this embodiment, the second method is preferably used, and the longitude and latitude information can be obtained more conveniently and quickly without on-site measurement.

[0054] After obtaining the four image coordinates and four longitude and latitude information of the circumscribed rectangle, four parameters can be calculated through the least squares method. These four parameters are the X-axis translation parameter, the Y-axis translation parameter, the rotation parameter and the scale parameter respectively; when calculating, substitute the two corresponding values in the image coordinates and the longitude and latitude information into the formula to calculate the four parameters. At this time, the conversion relationship between the image coordinates and the actual geographic coordinates is formally established.

[0055] After that, the image coordinates of each vertex of the colored area and the four calculated parameters can be substituted into the four-parameter conversion model formula to calculate the geographic coordinates corresponding to each image coordinate; the expression of the four-parameter conversion model is:

[0056]

[0057] where x1, y1 are the coordinates on the image; x2, y2 are the actual geographic coordinates; Δ y , Δ x are the translation parameters; α is the rotation parameter; m is the scale parameter.

[0058] Through this formula, the actual geographic coordinates of each vertex in the colored area can be calculated, so that the total area of the colored area can be calculated by computer.

[0059] Embodiment 2

[0060] The difference between Embodiment 2 and Embodiment 1 is that the agricultural insurance company provides a remote sensing image with longitude and latitude information. At this time, step S4 can be omitted, and the longitude and latitude information of the four points of the circumscribed rectangle can be extracted through OCR recognition technology.

[0061] Embodiment 3

[0062] Corresponding to the method of Embodiment 1, a land right confirmation system for obtaining plot information based on images is provided. The system includes:

[0063] Boundary description module: After obtaining the remote sensing image of the plot, it is used to perform pre-determined coloring on the insured range and draw a circumscribed rectangle according to the colored area;

[0064] Coordinate calculation module: Using OpenCV image recognition technology, calculate the image coordinates of each vertex of the colored area, and synchronously calculate the image coordinates of the four points of the circumscribed rectangle;

[0065] Latitude and longitude acquisition module: Used to obtain the latitude and longitude information of the four points of the circumscribed rectangle according to the reference objects corresponding to the circumscribed rectangle area;

[0066] Coordinate conversion module: Used to calculate four parameters by using the least squares method according to the latitude and longitude information and image coordinates of the four points of the obtained circumscribed rectangle, and then substitute the known four parameters and the image coordinates of each vertex of the colored area into the four-parameter conversion model to calculate the geographic coordinates corresponding to each image coordinate.

[0067] After calculating the corresponding geographic coordinates, generate plot surface data, form a kml file, upload it to the system, and display all farmer and plot information on the large map.

[0068] The present invention also discloses an electronic device, including: at least one processor, at least one memory, a communication interface, and a bus; wherein, the processor, the memory, and the communication interface complete mutual communication through the bus; the memory stores program instructions executable by the processor, and the processor calls the program instructions to implement the method described above in the present invention.

[0069] The present invention also discloses a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and the computer instructions enable a computer to implement the method described above in the present invention.

[0070] In summary, the present invention can help agricultural insurance companies obtain accurate plot geographical ranges more quickly, formulate reasonable insurance rates, improve the efficiency of underwriting and claims settlement, and the agricultural insurance underwriting and claims settlement processes are more convenient and efficient. By electronically collecting and processing land information, manual operations can be reduced, operating costs can be lowered, the affected plots and areas can be quickly determined, and the claims settlement speed and accuracy can be improved.

[0071] The present invention is not limited solely to what is described in the specification and embodiments. Therefore, for those skilled in the art, additional advantages and modifications can be easily achieved. Thus, without departing from the spirit and scope of the general concept defined by the claims and their equivalents, the present invention is not limited to specific details, representative devices, and the illustrated examples shown and described herein.

Claims

1. A right confirmation method for obtaining plot information based on images, characterized in that, It includes the following steps: S1. Obtain the remote sensing image of the plot with the insurance coverage, import it into the operation platform, pre-define the coloring for the insurance coverage area, and draw an enclosing rectangle based on the coloring range; S2. Use the OpenCV image recognition technology to identify the colored area in the remote sensing image of the plot, and calculate the image coordinates of each vertex of the colored area; S3. Calculate the image coordinates of the four points of the enclosing rectangle according to the vertex image coordinates obtained in step S2; S4. Obtain the longitude and latitude information of the four points of the enclosing rectangle according to the reference objects corresponding to the enclosing rectangle area; S5. Select two of the obtained longitude and latitude and image coordinates of the four points of the enclosing rectangle, and use the least squares method to calculate four parameters; S6. Use the four-parameter conversion model formula with the image coordinates of each vertex of the colored area in step S2 and the four parameters calculated in step S5 to calculate the geographical coordinates corresponding to each image coordinate.

2. The land right confirmation method for obtaining land parcel information based on images according to claim 1, wherein The steps for obtaining the image coordinates in step S2 are as follows: S21. Read the remote sensing image and convert the remote sensing image from the BGR color space to the HSV color space; S22. Set a threshold range for the colored area in the HSV color space; S23. Use the cv2.inRange() function to segment the image according to the set threshold to obtain a binary image; S24. Use the cv2.findContours() function to detect the contours in the binary image, and analyze the contours to extract the contours of the plot in the colored area; S25. Use the cv2.approxPolyDP() function for the contours of the colored area to approximate the contours and obtain the coordinates of each vertex.

3. The method for confirming land ownership based on image acquisition according to claim 1, characterized in that: In step S4, after obtaining the longitude and latitude information of the four points of the enclosing rectangle, use the OCR recognition technology to extract the longitude and latitude information of the four points.

4. The right confirmation method for obtaining plot information based on an image according to claim 1, wherein The four parameters in step S5 are respectively the X-axis translation parameter, the Y-axis translation parameter, the rotation parameter, and the scale parameter.

5. The method for confirming land ownership based on image acquisition according to claim 1, characterized in that: The expression of the four-parameter conversion model in step S5 is: where x1, y1 are the coordinates on the image; x2, y2 are the actual geographical coordinates; Δ y , Δ x are the translation parameters; α is the rotation parameter; m is the scale parameter.

6. A right confirmation system for obtaining plot information based on images, characterized in that, The system includes: Boundary description module: used to pre-define the coloring for the insurance coverage after obtaining the remote sensing image of the plot, and draw an enclosing rectangle according to the colored area; Coordinate calculation module: use the OpenCV image recognition technology to calculate the image coordinates of each vertex of the colored area, and synchronously calculate the image coordinates of the four points of the enclosing rectangle; Longitude and latitude acquisition module: used to obtain the longitude and latitude information of the four points of the enclosing rectangle according to the reference objects corresponding to the enclosing rectangle area; Coordinate conversion module: used to calculate four parameters using the least squares method according to the obtained longitude and latitude information and image coordinates of the four points of the enclosing rectangle, and then substitute the known four parameters and the image coordinates of each vertex of the colored area into the four-parameter conversion model to calculate the geographical coordinates corresponding to each image coordinate.

7. An electronic device, characterized in that, It includes: At least one processor, at least one memory, a communication interface, and a bus; wherein, the processor, the memory, and the communication interface complete the communication with each other through the bus; The memory stores program instructions executable by the processor, and the processor invokes the program instructions to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a computer to implement the method according to any one of claims 1 to 5.

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