A method and device for monitoring a slope, an electronic device and a storage medium

Abstract

This application provides a method, apparatus, electronic device, and storage medium for slope monitoring. The monitoring method includes: acquiring an initial image of a target slope monitoring area, and identifying multiple areas within the initial image; acquiring a current image of the target slope monitoring area, and extracting feature points from the current image and the initial image; for each area, performing feature point matching between each feature point in the current image and the feature points in the initial image, obtaining the number of successfully matched feature points and a homography matrix; based on the number of successfully matched feature points and the homography matrix corresponding to each area, determining whether the target slope has changed within the corresponding area; if the target slope has changed within the corresponding area, generating an alarm message indicating a change in the target slope within the corresponding area. The technical solution provided in this application can improve the sensitivity of slope monitoring.

Description

Technical Field

[0001] This application relates to the field of slope monitoring technology, and in particular to a slope monitoring method, device, electronic equipment and storage medium. Background Technology

[0002] Because some important infrastructure projects such as highways and railways, as well as densely populated residential and commercial areas, are built along rock or soil slopes, natural disasters such as landslides, collapses, mudslides, and rockfalls seriously endanger the lives and property of the people. Furthermore, open-pit mining operations, which involve blasting, also pose a risk of landslides and collapses. Therefore, whether the slope is natural or formed by mining, its stability requires continuous monitoring during operation.

[0003] Currently, most slope monitoring methods employ contact-based measurement techniques, requiring installation work on the slope. However, for slopes with exposed rock or those at constant risk of landslides or collapses, these operations pose significant risks. Furthermore, during the operational phase of the slope, manual on-site work is still necessary, especially after a landslide or collapse, as personnel cannot promptly assess the situation and make timely decisions, increasing the risk of secondary disasters. Additionally, slope monitoring methods include those using machine vision. Some methods require fixed targets on the slope, limiting monitoring to a few points and failing to cover the entire slope surface. Other methods require feature matching of the entire image, aligning the current image with historical images, and then calculating the difference between the two. However, if slight settlement occurs on the right side of the slope, the feature matching algorithm may rotate the entire image to ensure complete overlap, resulting in the final difference image failing to reflect the settlement on the right side, thus reducing monitoring sensitivity. Therefore, how to effectively monitor slopes has become a pressing issue. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a slope monitoring method, device, electronic device and storage medium, which can divide an initial image into multiple regions, match each region with the corresponding region in the current image, obtain the number of successfully matched feature points and the homography matrix, and determine whether each region has changed in the current image based on the number of successfully matched feature points and the homography matrix, thereby realizing non-contact slope monitoring, which not only reduces the risk of secondary disasters, but also improves the sensitivity of monitoring.

[0005] This application mainly includes the following aspects:

[0006] In a first aspect, embodiments of this application provide a method for monitoring slopes, the monitoring method comprising:

[0007] An initial image of the target slope monitoring area is acquired, and multiple areas are identified in the initial image based on the surface features of the target slope monitoring area.

[0008] Acquire the current image of the target slope monitoring area, and extract the feature points of the current image and the feature points of the initial image;

[0009] For each region, based on the feature points of the current image and the feature points of the initial image, feature point matching is performed between each feature point in that region of the current image and the feature points in that region of the initial image to obtain the number of successfully matched feature points and the homography matrix.

[0010] Based on the number of successfully matched feature points corresponding to each region and the homography matrix, it is determined whether the target slope has changed in the corresponding region. If the target slope has changed in the corresponding region, an alarm message indicating that the target slope has changed in the corresponding region is generated.

[0011] Furthermore, the step of matching each feature point in the current image with the feature points in the same region of the initial image based on the feature points of the current image and the feature points of the initial image, to obtain the number of successfully matched feature points and the homography matrix, includes:

[0012] Based on the feature points of the current image, determine the current feature points of the current image in this region from the feature points of the current image;

[0013] Based on the feature points of the initial image, the initial feature points of the initial image in this region are determined from the feature points of the initial image;

[0014] For each current feature point in the region, feature point matching is performed with the initial feature points in the region to obtain the initial feature points that match each current feature point and the matching degree. For each current feature point, if the matching degree of the current feature point is greater than the preset matching degree, then the current feature point is determined as a successfully matched feature point.

[0015] Based on the successfully matched feature points within the region, the number of successfully matched feature points and the homography matrix in the region are obtained.

[0016] Furthermore, the region includes a reference region and multiple control regions. The step of determining whether the target slope has changed within the corresponding region based on the number of successfully matched feature points corresponding to each region and the homography matrix, and generating an alarm message indicating that the target slope has changed within the corresponding region if the target slope has changed within the corresponding region, includes:

[0017] Based on the number of successfully matched feature points corresponding to each region and the homography matrix, if the region is a reference region, then the number of successfully matched feature points in the reference region is determined as the first number of matched points, and the homography matrix corresponding to the reference region is determined as the first homography matrix;

[0018] If the region is a control region, the number of successfully matched feature points in the control region is determined as the second number of matching points, and the homography matrix corresponding to the control region is determined as the second homography matrix;

[0019] Based on the number of the first matching points corresponding to the reference area, if the number of the first matching points is less than a first preset threshold, it is determined that the reference area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the reference area.

[0020] Based on the number of the second matching points corresponding to each control area, for each control area, if the number of the second matching points corresponding to the control area is less than the second preset threshold, it is determined that the control area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the control area.

[0021] If the number of the first matching points is not less than the first preset threshold, then based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each control region, it is determined whether each control region has been displaced and deformed in the current image. If displacement occurs, an alarm message is generated indicating that the target slope has been displaced in the corresponding control region. If deformation occurs, an alarm message is generated indicating that the target slope has been deformed in the corresponding control region.

[0022] Furthermore, the step of determining whether each reference region has undergone displacement and deformation in the current image based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each reference region if the number of the first matching points is not less than the first preset threshold includes:

[0023] If the number of the first matching points is not less than the first preset threshold, then the first homography matrix corresponding to the reference region is decomposed to obtain the first rotation angle and the first translation vector corresponding to the reference region.

[0024] For each control region, if the number of the second matching points corresponding to the control region is not less than the second preset threshold, the second homography matrix corresponding to the control region is decomposed to obtain the second rotation angle and the second translation vector corresponding to the control region.

[0025] Based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the control region, it is determined whether the control region has been displaced in the current image;

[0026] Based on the first rotation angle corresponding to the reference area and the second rotation angle corresponding to the control area, it is determined whether the control area is deformed in the current image.

[0027] Furthermore, the step of determining whether the reference region has shifted in the current image based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the reference region includes:

[0028] Based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the control region, the distance between the second translation vector corresponding to the control region and the first translation vector corresponding to the reference region is determined as the translation distance;

[0029] Determine whether the translation distance is greater than a third preset threshold;

[0030] If the value is not greater than the third preset threshold, it is determined that the control area has not been displaced in the current image;

[0031] If the displacement is greater than the third preset threshold, it is determined that the control area has shifted in the current image.

[0032] Furthermore, the step of determining whether the reference region is deformed in the current image based on the first rotation angle corresponding to the reference region and the second rotation angle corresponding to the reference region includes:

[0033] Based on the first rotation angle corresponding to the reference area and the second rotation angle corresponding to the control area, the difference between the second rotation angle corresponding to the control area and the first rotation angle corresponding to the reference area is determined as the rotation difference.

[0034] Determine whether the rotation difference is greater than a fourth preset threshold;

[0035] If the value is not greater than the fourth preset threshold, then it is determined that the control area has not been deformed in the current image;

[0036] If the value is greater than the fourth preset threshold, then it is determined that the control area has been deformed in the current image.

[0037] Secondly, embodiments of this application also provide a slope monitoring device, the monitoring device comprising:

[0038] The acquisition module is used to acquire an initial image of the target slope monitoring area and, based on the surface features of the target slope monitoring area, determine multiple regions in the initial image;

[0039] The extraction module is used to acquire the current image of the target slope monitoring area and extract the feature points of the current image and the feature points of the initial image;

[0040] The matching module is used to perform feature point matching for each region, based on the feature points of the current image and the feature points of the initial image, to match each feature point in the current region with the feature points in the initial image, and to obtain the number of successfully matched feature points and the homography matrix.

[0041] The determination module is used to determine whether the target slope has changed in the corresponding region based on the number of successfully matched feature points corresponding to each region and the homography matrix. If the target slope has changed in the corresponding region, an alarm message indicating that the target slope has changed in the corresponding region is generated.

[0042] Furthermore, the matching module is specifically used for:

[0043] Based on the feature points of the current image, determine the current feature points of the current image in this region from the feature points of the current image;

[0044] Based on the feature points of the initial image, the initial feature points of the initial image in this region are determined from the feature points of the initial image;

[0045] For each current feature point in the region, feature point matching is performed with the initial feature points in the region to obtain the initial feature points that match each current feature point and the matching degree. For each current feature point, if the matching degree of the current feature point is greater than the preset matching degree, then the current feature point is determined as a successfully matched feature point.

[0046] Based on the successfully matched feature points within the region, the number of successfully matched feature points and the homography matrix in the region are obtained.

[0047] Thirdly, embodiments of this application also provide an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the slope monitoring method described above are performed.

[0048] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the slope monitoring method described above.

[0049] This application provides a slope monitoring method, device, electronic device, and storage medium. The monitoring method includes: acquiring an initial image of a target slope monitoring area, and determining multiple areas in the initial image based on the surface features of the target slope monitoring area; acquiring a current image of the target slope monitoring area, and extracting feature points from the current image and the initial image; for each area, matching each feature point in the current image with the feature points in the initial image based on the feature points in the current image and the initial image, obtaining the number of successfully matched feature points and a homography matrix; determining whether the target slope has changed in the corresponding area based on the number of successfully matched feature points and the homography matrix corresponding to each area, and generating an alarm message indicating that the target slope has changed in the corresponding area if the target slope has changed in the corresponding area.

[0050] In this way, the technical solution provided in this application can divide the initial image into multiple regions, match each region with the corresponding region in the current image, obtain the number of successfully matched feature points and the homography matrix, and determine whether each region has changed in the current image based on the number of successfully matched feature points and the homography matrix, thus realizing non-contact monitoring of slopes, which not only reduces the risk of secondary disasters but also improves the sensitivity of monitoring.

[0051] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0052] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 A flowchart illustrating a slope monitoring method provided in an embodiment of this application is shown;

[0054] Figure 2 A flowchart illustrating another slope monitoring method provided in an embodiment of this application is shown;

[0055] Figure 3 A structural diagram of a slope monitoring device provided in an embodiment of this application is shown;

[0056] Figure 4A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0058] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0059] In order to enable those skilled in the art to use the content of this application, and in combination with the specific application scenario of "slope monitoring", the following implementation method is given. For those skilled in the art, the general principles defined herein can be applied to other embodiments and application scenarios without departing from the spirit and scope of this application.

[0060] The methods, apparatus, electronic devices, or computer-readable storage media described in this application can be applied to any scenario requiring slope monitoring. This application does not limit the specific application scenario. Any scheme using a slope monitoring method, apparatus, electronic device, and storage medium provided in this application is within the protection scope of this application.

[0061] It is worth noting that some important infrastructure projects such as highways and railways, as well as densely populated residential and commercial areas, are built along rock or soil slopes. Natural disasters such as landslides, collapses, mudslides, and rockfalls seriously endanger the lives and property of the people. During open-pit mining, blasting operations are required, posing a risk of landslides and collapses. In summary, both natural slopes and slopes formed by mining require continuous monitoring of their stability during operation. Traditional slope monitoring collects various data on the slope surface and within the slope, including data measurement using traditional monitoring equipment such as surface weather stations, inclinometers, earth pressure cells, and crack gauges.

[0062] Currently, most existing monitoring methods employ contact-based measurement techniques, requiring installation work on the slope. However, for slopes with exposed rock or those at constant risk of landslides or collapses, such construction work poses a high degree of danger. Furthermore, manual on-site work is still necessary during the slope's operational phase. Especially after a landslide or collapse occurs, the inability of personnel to promptly understand the situation and make timely decisions increases the risk of secondary disasters. In some cases using synthetic aperture radar (SAR) for slope monitoring, there are issues such as long radar imaging times, high costs, and the sparse point cloud over long distances, leading to missed detections. Existing slope monitoring methods using machine vision require the fixed installation of targets on the slope, limiting monitoring to a few points and failing to cover the entire slope surface. Another method requires feature matching of the entire image, aligning the current image with historical images, and then calculating the difference between the two images. If there is slight settlement on the right slope of the image, the feature matching algorithm will rotate the entire image to make the two images completely overlap, resulting in the final difference image not reflecting the settlement of the right slope, thus reducing the monitoring sensitivity. Therefore, how to monitor the slope has become an urgent problem to be solved.

[0063] Based on this, this application proposes a slope monitoring method, device, electronic device, and storage medium. The monitoring method includes: acquiring an initial image of a target slope monitoring area, and determining multiple areas in the initial image based on the surface features of the target slope monitoring area; acquiring a current image of the target slope monitoring area, and extracting feature points from the current image and the initial image; for each area, matching each feature point in that area of ​​the current image with the feature points in the initial image based on the feature points of the current image and the initial image, obtaining the number of successfully matched feature points and a homography matrix; determining whether the target slope has changed in the corresponding area based on the number of successfully matched feature points and the homography matrix corresponding to each area, and generating an alarm message indicating that the target slope has changed in the corresponding area if the target slope has changed in the corresponding area.

[0064] In this way, the technical solution provided in this application can divide the initial image into multiple regions, match each region with the corresponding region in the current image, obtain the number of successfully matched feature points and the homography matrix, and determine whether each region has changed in the current image based on the number of successfully matched feature points and the homography matrix, thus realizing non-contact monitoring of slopes, which not only reduces the risk of secondary disasters but also improves the sensitivity of monitoring.

[0065] To facilitate understanding of this application, the technical solutions provided in this application will be described in detail below with reference to specific embodiments.

[0066] Please see Figure 1 , Figure 1 A flowchart illustrating a slope monitoring method provided in this application embodiment is shown below. Figure 1 As shown, the monitoring method includes:

[0067] S101. Obtain an initial image of the target slope monitoring area, and determine multiple areas in the initial image based on the surface features of the target slope monitoring area;

[0068] In this step, this embodiment can divide the image into multiple regions based on the surface features of the target slope monitoring area, thereby calculating the relative displacement and deformation between regions, realizing non-contact monitoring of the slope, which not only reduces the risk of secondary disasters, but also improves monitoring sensitivity.

[0069] Here, the area can include a reference area and multiple control areas. Both the reference area and the control areas can be represented by irregular polygons. For example, if there is a crack that splits from left to right on the target slope monitoring area, then the left side of the crack can be used as the reference area and the right side of the crack can be used as the control area. As another example, if the target slope monitoring area contains a cross section, then the left side of the cross section can be used as the reference area and the right side can be used as the control area.

[0070] It should be noted that surface features include not only the distribution of soil and rock but also the growth of surface vegetation. When delineating regions, areas with dense vegetation should be avoided as much as possible to prevent vegetation growth from affecting the feature matching results.

[0071] S102. Obtain the current image of the target slope monitoring area, and extract the feature points of the current image and the feature points of the initial image;

[0072] In this step, images of the target slope monitoring area are periodically acquired using the same shooting parameters as the initial image. Specifically, when the current image is taken, its camera focal length, shooting angle, and shooting distance are consistent with the initial image. For example, a fixed-angle camera, a camera with a rotating gimbal taking pictures at the same gimbal angle, or a drone taking pictures at the same coordinates.

[0073] Here, image feature point calculation algorithms (e.g., scale-invariant feature transform SIFT) can be used to calculate the feature point set of the initial image and the feature point set of the current image, respectively.

[0074] S103. For each region, based on the feature points of the current image and the feature points of the initial image, perform feature point matching between each feature point in that region of the current image and the feature points in that region of the initial image to obtain the number of successfully matched feature points and the homography matrix.

[0075] It should be noted that you should refer to [link / reference]. Figure 2 , Figure 2 A flowchart illustrating another slope monitoring method provided in this application embodiment, such as... Figure 2 As shown, the steps of matching each feature point in the current image with the feature points in the initial image within the same region, based on the feature points of the current image and the initial image, to obtain the number of successfully matched feature points and the homography matrix, include:

[0076] S201. Based on the feature points of the current image, determine the current feature points of the current image in this region from the feature points of the current image;

[0077] S202. Based on the feature points of the initial image, determine the initial feature points of the initial image in this region from the feature points of the initial image;

[0078] S203. Perform feature point matching between the current feature point in the region and the initial feature point in the region to obtain the initial feature point and matching degree that match each current feature point. For each current feature point, if the matching degree of the current feature point is greater than the preset matching degree, then the current feature point is determined as a successfully matched feature point.

[0079] S204. Based on the successfully matched feature points in the region, obtain the number of successfully matched feature points in the region and the homography matrix.

[0080] In this step, based on the pixel coordinates of each region, a subset of initial image feature points within that region can be obtained from the feature point set of the initial image, and a subset of current image feature points within that region can be obtained from the feature point set of the current image. Then, using an image feature point matching algorithm, the number of successfully matched feature points and the homography matrix within that region are calculated. Here, the homography matrix is ​​the projection transformation matrix.

[0081] Here, when performing feature point matching, the preset matching degree can be set in advance based on historical experience and experimental data.

[0082] S104. Based on the number of successfully matched feature points corresponding to each region and the homography matrix, determine whether the target slope has changed in the corresponding region. If the target slope has changed in the corresponding region, generate an alarm message indicating that the target slope has changed in the corresponding region.

[0083] It should be noted that the steps for determining whether the target slope has changed within the corresponding region based on the number of successfully matched feature points and the homography matrix for each region, and generating an alarm message indicating that the target slope has changed within the corresponding region if it has changed, include:

[0084] S1041. Based on the number of successfully matched feature points corresponding to each region and the homography matrix, if the region is a reference region, the number of successfully matched feature points in the reference region is determined as the first number of matching points, and the homography matrix corresponding to the reference region is determined as the first homography matrix.

[0085] S1042. If the region is a control region, the number of successfully matched feature points in the control region is determined as the second number of matching points, and the homography matrix corresponding to the control region is determined as the second homography matrix.

[0086] S1043. Based on the number of the first matching points corresponding to the reference area, if the number of the first matching points is less than a first preset threshold, it is determined that the reference area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the reference area.

[0087] In this step, if the number of first matching points is less than the first preset threshold, it indicates that the reference area is suspected to be deformed in the current image compared with the initial image, and an alarm for the deformation of the reference area can be issued for maintenance personnel to investigate; if the number of first matching points is not less than the first preset threshold, it indicates that the reference area has not changed significantly in the current image compared with the initial image.

[0088] Here, the first preset threshold can be set in advance based on historical experience and experimental data.

[0089] S1044. Based on the number of the second matching points corresponding to each control area, for each control area, if the number of the second matching points corresponding to the control area is less than the second preset threshold, it is determined that the control area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the control area.

[0090] In this step, if the number of second matching points is less than the second preset threshold, it indicates that the control area is suspected of being deformed in the current image compared with the initial image, and an alarm for deformation of the control area can be issued for maintenance personnel to investigate; if the number of second matching points is not less than the second preset threshold, it indicates that the control area has not changed significantly in the current image compared with the initial image.

[0091] For example, the reference area can be a region containing a rock. The number of second matching points can be used to determine whether the rock still exists in the reference area of ​​the current image. If the rock still exists in the reference area of ​​the current image, it can be further determined whether the rock's pose has changed. For example, on a slope containing a fault zone, when the fault zone moves vertically and horizontally, the rock sandwiched in the middle may tilt or fall. Therefore, the following step S1045 can be used to further determine whether the rock has been displaced and deformed (e.g., angle change).

[0092] Here, the second preset threshold can be preset based on historical experience and experimental data.

[0093] S1045. If the number of the first matching points is not less than the first preset threshold, then based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each control region, determine whether each control region has been displaced and deformed in the current image. If displacement occurs, generate an alarm message indicating that the target slope has been displaced in the corresponding control region. If deformation occurs, generate an alarm message indicating that the target slope has been deformed in the corresponding control region.

[0094] It should be noted that if the number of first matching points is not less than the first preset threshold, the step of determining whether each control region has undergone displacement and deformation in the current image based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each control region includes:

[0095] 1) If the number of the first matching points is not less than the first preset threshold, then the first homography matrix corresponding to the reference region is decomposed to obtain the first rotation angle and the first translation vector corresponding to the reference region.

[0096] 2) For each control region, if the number of the second matching points corresponding to the control region is not less than the second preset threshold, then the second homography matrix corresponding to the control region is decomposed to obtain the second rotation angle and the second translation vector corresponding to the control region.

[0097] In this step, if the reference region has not changed in the current image, the reference region can be used as a reference to determine whether the reference region has been displaced or deformed when the number of second matching points corresponding to the reference region is not less than the second preset threshold. Here, the first rotation angle and the first translation vector can be obtained by decomposing the first homography matrix using mathematical formulas, and the second rotation angle and the second translation vector can be obtained by decomposing the second homography matrix. The specific decomposition process will not be described in detail here.

[0098] 3) Based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the control region, determine whether the control region has been displaced in the current image;

[0099] It should be noted that the step of determining whether the reference region has been displaced in the current image based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the reference region includes:

[0100] (1) Based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the control region, the distance between the second translation vector corresponding to the control region and the first translation vector corresponding to the reference region is determined as the translation distance;

[0101] (2) Determine whether the translation distance is greater than a third preset threshold;

[0102] (3) If it is not greater than the third preset threshold, then it is determined that the control area has not been displaced in the current image;

[0103] (4) If the value is greater than the third preset threshold, it is determined that the control area has shifted in the current image.

[0104] In this step, if the distance between the second translation vector and the first translation vector of any control area is greater than the third preset threshold, an alarm is issued for the suspected displacement of the control area; here, the third preset threshold can be preset based on historical experience and experimental data.

[0105] 4) Based on the first rotation angle corresponding to the reference area and the second rotation angle corresponding to the comparison area, determine whether the comparison area is deformed in the current image.

[0106] It should be noted that the step of determining whether the reference region is deformed in the current image based on the first rotation angle corresponding to the reference region and the second rotation angle corresponding to the reference region includes:

[0107] (1) Based on the first rotation angle corresponding to the reference area and the second rotation angle corresponding to the control area, the difference between the second rotation angle corresponding to the control area and the first rotation angle corresponding to the reference area is determined as the rotation difference.

[0108] (2) Determine whether the rotation difference is greater than the fourth preset threshold;

[0109] (3) If it is not greater than the fourth preset threshold, then it is determined that the control area has not been deformed in the current image;

[0110] (4) If the value is greater than the fourth preset threshold, it is determined that the control area is deformed in the current image.

[0111] In this step, if the difference between the second rotation angle and the first rotation angle of any control area is greater than the fourth preset threshold, an alarm is issued indicating that the control area is suspected of being deformed. Here, the fourth preset threshold can be preset based on historical experience and experimental data.

[0112] In summary, this embodiment can divide the image into multiple regions based on the surface characteristics of the target slope monitoring area, calculate the homography matrix for each region, and use the homography matrix to calculate the relative displacement and deformation between regions, thereby improving the sensitivity of slope monitoring.

[0113] This application provides a slope monitoring method, which includes: acquiring an initial image of a target slope monitoring area, and determining multiple areas in the initial image based on the surface features of the target slope monitoring area; acquiring a current image of the target slope monitoring area, and extracting feature points from the current image and the initial image; for each area, matching each feature point in the current image with the feature points in the initial image based on the feature points in the current image and the initial image, obtaining the number of successfully matched feature points and a homography matrix; determining whether the target slope has changed in the corresponding area based on the number of successfully matched feature points and the homography matrix corresponding to each area, and generating an alarm message indicating that the target slope has changed in the corresponding area if the target slope has changed in the corresponding area.

[0114] In this way, the technical solution provided in this application can divide the initial image into multiple regions, match each region with the corresponding region in the current image, obtain the number of successfully matched feature points and the homography matrix, and determine whether each region has changed in the current image based on the number of successfully matched feature points and the homography matrix, thus realizing non-contact monitoring of slopes, which not only reduces the risk of secondary disasters but also improves the sensitivity of monitoring.

[0115] Based on the same application concept, this application also provides a slope monitoring device corresponding to the slope monitoring method provided in the above embodiment. Since the principle of the device in this application is similar to the slope monitoring method in the above embodiment, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0116] Please see Figure 3 , Figure 3 This is a structural diagram of a slope monitoring device provided in an embodiment of this application. Figure 3 As shown, the monitoring device 310 includes:

[0117] The acquisition module 311 is used to acquire an initial image of the target slope monitoring area and, based on the surface features of the target slope monitoring area, determine multiple areas in the initial image;

[0118] Extraction module 312 is used to acquire the current image of the target slope monitoring area and extract the feature points of the current image and the feature points of the initial image;

[0119] The matching module 313 is used to perform feature point matching between each feature point in the current image and the feature points in the initial image for each region, based on the feature points of the current image and the feature points of the initial image, to obtain the number of successfully matched feature points and the homography matrix.

[0120] The determination module 314 is used to determine whether the target slope has changed in the corresponding area based on the number of successfully matched feature points corresponding to each area and the homography matrix. If the target slope has changed in the corresponding area, an alarm message indicating that the target slope has changed in the corresponding area is generated.

[0121] Optionally, the matching module 313 is specifically used for:

[0122] Based on the feature points of the current image, determine the current feature points of the current image in this region from the feature points of the current image;

[0123] Based on the feature points of the initial image, the initial feature points of the initial image in this region are determined from the feature points of the initial image;

[0124] For each current feature point in the region, feature point matching is performed with the initial feature points in the region to obtain the initial feature points that match each current feature point and the matching degree. For each current feature point, if the matching degree of the current feature point is greater than the preset matching degree, then the current feature point is determined as a successfully matched feature point.

[0125] Based on the successfully matched feature points within the region, the number of successfully matched feature points and the homography matrix in the region are obtained.

[0126] Optionally, the region includes a reference region and multiple control regions. When the determining module 314 determines whether the target slope has changed within the corresponding region based on the number of successfully matched feature points and the homography matrix for each region, and generates an alarm message indicating that the target slope has changed within the corresponding region if it has, the determining module 314 is specifically used for:

[0127] Based on the number of successfully matched feature points corresponding to each region and the homography matrix, if the region is a reference region, then the number of successfully matched feature points in the reference region is determined as the first number of matched points, and the homography matrix corresponding to the reference region is determined as the first homography matrix;

[0128] If the region is a control region, the number of successfully matched feature points in the control region is determined as the second number of matching points, and the homography matrix corresponding to the control region is determined as the second homography matrix;

[0129] Based on the number of the first matching points corresponding to the reference area, if the number of the first matching points is less than a first preset threshold, it is determined that the reference area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the reference area.

[0130] Based on the number of the second matching points corresponding to each control area, for each control area, if the number of the second matching points corresponding to the control area is less than the second preset threshold, it is determined that the control area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the control area.

[0131] If the number of the first matching points is not less than the first preset threshold, then based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each control region, it is determined whether each control region has been displaced and deformed in the current image. If displacement occurs, an alarm message is generated indicating that the target slope has been displaced in the corresponding control region. If deformation occurs, an alarm message is generated indicating that the target slope has been deformed in the corresponding control region.

[0132] Optionally, when the determining module 314 is used to determine whether each reference region has undergone displacement and deformation in the current image based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each reference region if the number of the first matching points is not less than a first preset threshold, the determining module 314 is specifically used for:

[0133] If the number of the first matching points is not less than the first preset threshold, then the first homography matrix corresponding to the reference region is decomposed to obtain the first rotation angle and the first translation vector corresponding to the reference region.

[0134] For each control region, if the number of the second matching points corresponding to the control region is not less than the second preset threshold, the second homography matrix corresponding to the control region is decomposed to obtain the second rotation angle and the second translation vector corresponding to the control region.

[0135] Based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the control region, it is determined whether the control region has been displaced in the current image;

[0136] Based on the first rotation angle corresponding to the reference area and the second rotation angle corresponding to the control area, it is determined whether the control area is deformed in the current image.

[0137] Optionally, when determining whether the reference region has shifted in the current image based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the reference region, the determining module 314 is specifically used for:

[0138] Based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the control region, the distance between the second translation vector corresponding to the control region and the first translation vector corresponding to the reference region is determined as the translation distance;

[0139] Determine whether the translation distance is greater than a third preset threshold;

[0140] If the value is not greater than the third preset threshold, it is determined that the control area has not been displaced in the current image;

[0141] If the displacement is greater than the third preset threshold, it is determined that the control area has shifted in the current image.

[0142] Optionally, when determining whether the reference region is deformed in the current image based on the first rotation angle corresponding to the reference region and the second rotation angle corresponding to the reference region, the determining module 314 is specifically used for:

[0143] Based on the first rotation angle corresponding to the reference area and the second rotation angle corresponding to the control area, the difference between the second rotation angle corresponding to the control area and the first rotation angle corresponding to the reference area is determined as the rotation difference.

[0144] Determine whether the rotation difference is greater than a fourth preset threshold;

[0145] If the value is not greater than the fourth preset threshold, then it is determined that the control area has not been deformed in the current image;

[0146] If the value is greater than the fourth preset threshold, then it is determined that the control area has been deformed in the current image.

[0147] This application provides a slope monitoring device, comprising: an acquisition module for acquiring an initial image of a target slope monitoring area and determining multiple areas in the initial image based on the surface features of the target slope monitoring area; an extraction module for acquiring a current image of the target slope monitoring area and extracting feature points from the current image and the initial image; a matching module for matching each feature point in the current image with the feature points in the initial image for each area, based on the feature points in the current image and the initial image, to obtain the number of successfully matched feature points and a homography matrix; and a determination module for determining whether the target slope has changed in the corresponding area based on the number of successfully matched feature points and the homography matrix for each area, and if the target slope has changed in the corresponding area, generating an alarm message indicating that the target slope has changed in the corresponding area.

[0148] In this way, the technical solution provided in this application can divide the initial image into multiple regions, match each region with the corresponding region in the current image, obtain the number of successfully matched feature points and the homography matrix, and determine whether each region has changed in the current image based on the number of successfully matched feature points and the homography matrix, thus realizing non-contact monitoring of slopes, which not only reduces the risk of secondary disasters but also improves the sensitivity of monitoring.

[0149] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 4 As shown, the electronic device 400 includes a processor 410, a memory 420, and a bus 430.

[0150] The memory 420 stores machine-readable instructions executable by the processor 410. When the electronic device 400 is running, the processor 410 communicates with the memory 420 via the bus 430. When the machine-readable instructions are executed by the processor 410, they can perform the operations described above. Figure 1 as well as Figure 2 The steps of the slope monitoring method in the illustrated embodiment can be found in the method embodiment for specific implementation details, which will not be repeated here.

[0151] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described actions. Figure 1 as well as Figure 2 The steps of the slope monitoring method in the illustrated embodiment can be found in the method embodiment for specific implementation details, which will not be repeated here.

[0152] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0153] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0154] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0155] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0156] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0157] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The scope of protection of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for monitoring slopes, characterized in that, The monitoring method includes: An initial image of the target slope monitoring area is acquired, and multiple regions are identified in the initial image based on the surface features of the target slope monitoring area; the regions include a reference region and multiple control regions. Acquire the current image of the target slope monitoring area, and extract the feature points of the current image and the feature points of the initial image; For each region, based on the feature points of the current image and the feature points of the initial image, feature point matching is performed between each feature point in that region of the current image and the feature points in that region of the initial image to obtain the number of successfully matched feature points and the homography matrix. Based on the number of successfully matched feature points corresponding to each region and the homography matrix, it is determined whether the target slope has changed in the corresponding region. If the target slope has changed in the corresponding region, an alarm message indicating that the target slope has changed in the corresponding region is generated. The step of determining whether the target slope has changed within a corresponding region based on the number of successfully matched feature points and the homography matrix for each region, and generating an alarm message indicating that the target slope has changed within the corresponding region if it has changed, includes: Based on the number of successfully matched feature points corresponding to each region and the homography matrix, if the region is a reference region, then the number of successfully matched feature points in the reference region is determined as the first number of matched points, and the homography matrix corresponding to the reference region is determined as the first homography matrix; If the region is a control region, the number of successfully matched feature points in the control region is determined as the second number of matching points, and the homography matrix corresponding to the control region is determined as the second homography matrix; Based on the number of the first matching points corresponding to the reference area, if the number of the first matching points is less than a first preset threshold, it is determined that the reference area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the reference area. Based on the number of the second matching points corresponding to each control area, for each control area, if the number of the second matching points corresponding to the control area is less than the second preset threshold, it is determined that the control area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the control area. If the number of the first matching points is not less than the first preset threshold, then based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each control region, it is determined whether each control region has been displaced and deformed in the current image. If displacement occurs, an alarm message is generated indicating that the target slope has been displaced in the corresponding control region. If deformation occurs, an alarm message is generated indicating that the target slope has been deformed in the corresponding control region. The step of determining whether each reference region has been displaced and deformed in the current image based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each reference region if the number of the first matching points is not less than the first preset threshold includes: If the number of the first matching points is not less than the first preset threshold, then the first homography matrix corresponding to the reference region is decomposed to obtain the first rotation angle and the first translation vector corresponding to the reference region. For each control region, if the number of the second matching points corresponding to the control region is not less than the second preset threshold, the second homography matrix corresponding to the control region is decomposed to obtain the second rotation angle and the second translation vector corresponding to the control region. Based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the control region, it is determined whether the control region has been displaced in the current image; Based on the first rotation angle corresponding to the reference area and the second rotation angle corresponding to the control area, it is determined whether the control area is deformed in the current image.

2. The monitoring method according to claim 1, characterized in that, The step of matching each feature point in the current image with the feature points in the same region of the initial image based on the feature points of the current image and the feature points of the initial image, to obtain the number of successfully matched feature points and the homography matrix, includes: Based on the feature points of the current image, determine the current feature points of the current image in this region from the feature points of the current image; Based on the feature points of the initial image, the initial feature points of the initial image in this region are determined from the feature points of the initial image; For each current feature point in the region, feature point matching is performed with the initial feature points in the region to obtain the initial feature points that match each current feature point and the matching degree. For each current feature point, if the matching degree of the current feature point is greater than the preset matching degree, then the current feature point is determined as a successfully matched feature point. Based on the successfully matched feature points within the region, the number of successfully matched feature points and the homography matrix in the region are obtained.

3. The monitoring method according to claim 1, characterized in that, The step of determining whether the reference region has been displaced in the current image based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the reference region includes: Based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the control region, the distance between the second translation vector corresponding to the control region and the first translation vector corresponding to the reference region is determined as the translation distance; Determine whether the translation distance is greater than a third preset threshold; If the value is not greater than the third preset threshold, it is determined that the control area has not been displaced in the current image; If the displacement is greater than the third preset threshold, it is determined that the control area has shifted in the current image.

4. The monitoring method according to claim 1, characterized in that, The step of determining whether the reference region is deformed in the current image based on the first rotation angle corresponding to the reference region and the second rotation angle corresponding to the reference region includes: Based on the first rotation angle corresponding to the reference area and the second rotation angle corresponding to the control area, the difference between the second rotation angle corresponding to the control area and the first rotation angle corresponding to the reference area is determined as the rotation difference. Determine whether the rotation difference is greater than a fourth preset threshold; If the value is not greater than the fourth preset threshold, then it is determined that the control area has not been deformed in the current image; If the value is greater than the fourth preset threshold, then it is determined that the control area has been deformed in the current image.

5. A slope monitoring device, characterized in that, The monitoring device includes: The acquisition module is used to acquire an initial image of the target slope monitoring area and, based on the surface features of the target slope monitoring area, determine multiple regions in the initial image; the regions include a reference region and multiple control regions; The extraction module is used to acquire the current image of the target slope monitoring area and extract the feature points of the current image and the feature points of the initial image; The matching module is used to perform feature point matching for each region, based on the feature points of the current image and the feature points of the initial image, to match each feature point in the current region with the feature points in the initial image, and to obtain the number of successfully matched feature points and the homography matrix. The determination module is used to determine whether the target slope has changed in the corresponding region based on the number of successfully matched feature points corresponding to each region and the homography matrix. If the target slope has changed in the corresponding region, an alarm message indicating that the target slope has changed in the corresponding region is generated. When the determining module determines whether the target slope has changed within a corresponding region based on the number of successfully matched feature points and the homography matrix for each region, and generates an alarm message indicating that the target slope has changed within the corresponding region if it has changed, the determining module is specifically used for: Based on the number of successfully matched feature points corresponding to each region and the homography matrix, if the region is a reference region, then the number of successfully matched feature points in the reference region is determined as the first number of matched points, and the homography matrix corresponding to the reference region is determined as the first homography matrix; If the region is a control region, the number of successfully matched feature points in the control region is determined as the second number of matching points, and the homography matrix corresponding to the control region is determined as the second homography matrix; Based on the number of the first matching points corresponding to the reference area, if the number of the first matching points is less than a first preset threshold, it is determined that the reference area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the reference area. Based on the number of the second matching points corresponding to each control area, for each control area, if the number of the second matching points corresponding to the control area is less than the second preset threshold, it is determined that the control area has changed in the current image, and an alarm message is generated indicating that the target slope has changed in the control area. If the number of the first matching points is not less than the first preset threshold, then based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each control region, it is determined whether each control region has been displaced and deformed in the current image. If displacement occurs, an alarm message is generated indicating that the target slope has been displaced in the corresponding control region. If deformation occurs, an alarm message is generated indicating that the target slope has been deformed in the corresponding control region. When the determining module is used to determine whether each reference region has undergone displacement and deformation in the current image based on the first homography matrix corresponding to the reference region and the second homography matrix corresponding to each reference region if the number of the first matching points is not less than a first preset threshold, the determining module is specifically used for: If the number of the first matching points is not less than the first preset threshold, then the first homography matrix corresponding to the reference region is decomposed to obtain the first rotation angle and the first translation vector corresponding to the reference region. For each control region, if the number of the second matching points corresponding to the control region is not less than the second preset threshold, the second homography matrix corresponding to the control region is decomposed to obtain the second rotation angle and the second translation vector corresponding to the control region. Based on the first translation vector corresponding to the reference region and the second translation vector corresponding to the control region, it is determined whether the control region has been displaced in the current image; Based on the first rotation angle corresponding to the reference area and the second rotation angle corresponding to the control area, it is determined whether the control area is deformed in the current image.

6. The monitoring device according to claim 5, characterized in that, The matching module is specifically used for: Based on the feature points of the current image, determine the current feature points of the current image in this region from the feature points of the current image; Based on the feature points of the initial image, the initial feature points of the initial image in this region are determined from the feature points of the initial image; For each current feature point in the region, feature point matching is performed with the initial feature points in the region to obtain the initial feature points that match each current feature point and the matching degree. For each current feature point, if the matching degree of the current feature point is greater than the preset matching degree, then the current feature point is determined as a successfully matched feature point. Based on the successfully matched feature points within the region, the number of successfully matched feature points and the homography matrix in the region are obtained.

7. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. The machine-readable instructions are executed by the processor to perform the steps of the slope monitoring method as described in any one of claims 1 to 4.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the slope monitoring method as described in any one of claims 1 to 4.

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