Three-dimensional Spatial Coordinate Location Method for Coal Rock Geological Images

Abstract

The present invention relates to the technical field of geological logging, and specifically to a three-dimensional space coordinate positioning method for coal-rock geological images, including: installing two cameras with fixed relative position information in parallel on a turntable, obtaining the camera parameters of the cameras, respectively taking overlapping geological images from both sides by the two cameras, and performing distortion correction on the geological images and resolving angular orientation elements according to the relative position information; performing gray processing on the geological images taken by the two cameras, extracting a preset number of homologous image points in the gray-processed geological images and collecting their pixel coordinates; constructing a collinearity equation set for each camera by using the space resection method according to the camera parameters and pixel coordinates, and calculating the interior orientation elements, exterior orientation elements, and distortion residuals. The present invention only needs to extract a set of data for calculation, reduces the amount of calculation, and overcomes the errors caused by the inability to use cameras with strictly collinear optical axis centers, improving the accuracy and efficiency of photogrammetry.

Description

Technical Field

[0001] The present invention relates to the technical field of geological logging, and specifically relates to a three-dimensional space coordinate positioning method for coal-rock geological images. Background Art

[0002] Coal-rock mining is to extract coal buried underground or on the ground. During the process of mining coal underground, a space of a certain size will be formed underground for material transportation, commuting, exploration, etc. Since different geological conditions will be shown on the inner wall of the space, during the mining process, it is necessary to take pictures of the formed coal-rock geological space and conduct logging to record geological information in a timely and accurate manner. Before taking pictures of the coal-rock geological space, it is necessary to calibrate the camera to calculate the distortion parameters of the camera, and calculate the three-dimensional geometric position of the object located in the three-dimensional space according to the image. The mutual relationship between the three-dimensional geometric position and its corresponding image point in the image is determined by the camera imaging principle. Therefore, relative positioning needs to be performed on the taken images.

[0003] Currently, for camera calibration, usually a stereo calibration frame is arranged indoors alone, and a plurality of object-space control points distributed in a preset spatial orientation are arranged on the stereo calibration frame to complete the control field setting. Then, images of the object-space control points with multiple known relative coordinates are taken to perform the calculation of the three-dimensional coordinate calibration of the camera. However, due to the limitation of the coal-rock geological space, the layout of the stereo calibration frame is very difficult to apply; and the number of selected object-space control points is large, and the amount of calculation is large, resulting in a long running time of the subsequent aerial triangulation algorithm. Summary of the Invention

[0004] The present invention aims to provide a three-dimensional space coordinate positioning method for coal-rock geological images to solve the problem of large amount of calculation during the calculation of three-dimensional space coordinate calibration.

[0005] The three-dimensional space coordinate positioning method for coal-rock geological images in this solution includes the following steps:

[0006] Step 1, install two cameras with fixed relative position information parallel on a turntable, obtain the camera parameters of the cameras, respectively take overlapping geological images from both sides by the two cameras, perform distortion correction on the geological images according to the camera parameters, and perform angular azimuth element calculation according to the relative position information;

[0007] Step 2, perform gray processing on the geological images taken by the two cameras, extract a preset number of homologous image points in the gray-processed geological images by using a preset algorithm, and collect the pixel coordinates of the homologous image points;

[0008] Step 3: For each camera, establish a collinearity equation system using the space resection method based on the camera parameters and pixel coordinates, and calculate the interior orientation elements, exterior orientation elements, and distortion residuals.

[0009] The beneficial effects of this solution are as follows:

[0010] By using two cameras with known relative positions, the running time of the subsequent aerotriangulation algorithm for calculating relative positions is shortened; and after gray processing the geological images, corresponding image points are extracted. Compared with the original color geological images, instead of separately extracting the three-channel pixel matrices for the three primary colors, this solution only needs to extract a set of pixel matrix data for calculation, reducing the amount of calculation, and can overcome the errors caused by the inability to use two cameras with strictly collinear optical axis centers, improving the accuracy of photogrammetry. In addition, after shooting the geological images, the interior orientation elements are calculated again, which is equivalent to recalibrating the two cameras separately, preventing errors caused by bumps during the transportation of the cameras.

[0011] Further, in Step 2, count the corresponding image points extracted to obtain a count value, and compare the count value with a preset quantity in real time. When the count value is equal to the preset quantity, stop extracting the corresponding image points. When the extraction of the corresponding image points on the coal wall image is completed and the count value is less than the preset quantity, re-extract the corresponding image points.

[0012] The beneficial effect is that during the process of extracting corresponding image points using the algorithm, the number of extracted corresponding image points is not extremely stable. When the extraction process of the corresponding image points is completed, the number of extracted corresponding image points may be larger or smaller than the preset quantity. Therefore, count the extracted corresponding image points and judge the count value in real time to avoid having too many or too few corresponding image points.

[0013] Further, in Step 2, before extracting the corresponding image points, first evenly divide the gray-processed geological image into multiple extraction grids, and extract the corresponding image points in each extraction grid according to the pixel positions on the coal wall image with several thresholds as the criteria, and the sum of the thresholds is equal to the preset quantity.

[0014] The beneficial effect is that dividing the geological image into multiple extraction grids and extracting different numbers of corresponding image points in each extraction grid improves the uniformity of extracting corresponding image points on the geological image.

[0015] Further, in Step 2, count the corresponding image points extracted in each extraction grid to obtain a single value, compare the single value with the threshold. When the single value is less than the threshold after the extraction of the corresponding image points in any extraction grid is completed, stop extracting the corresponding image points.

[0016] The beneficial effects are as follows: By counting the homologous image points for each extraction cell and determining whether a single value is equal to the threshold, if the single value is less than the threshold, the extraction of homologous image points is stopped, preventing the delay caused by continued extraction and ensuring that the total number of extracted homologous image points does not meet the requirements at the end, and ensuring the uniform extraction of homologous image points on the coal wall image.

[0017] Further, in the second step, when the single value is less than the threshold after the extraction of homologous image points in any extraction cell is completed, record the position information of the extraction cell on the geological image, and use this position information as the initial position for the extraction of homologous image points when re-extracting homologous image points.

[0018] The beneficial effects are as follows: By recording the position information of the extraction cell where the single value of the extracted homologous image points is less than the threshold and using this position information as the initial position for the extraction of homologous image points, if the homologous image points reaching the threshold still cannot be extracted, the extraction can be stopped quickly and in a timely manner, avoiding wasting time.

[0019] Further, when it is determined again that the single value is less than the threshold, determine whether the multiple recorded position information is located within the same extraction cell. If it is determined that multiple position information is located within the same extraction cell, then determine whether there is a single value within the extraction cell that is greater than the threshold. If so, re-divide the extraction cell with a reduced size and then re-extract the homologous image points.

[0020] The beneficial effects are as follows: When the homologous image points reaching the threshold cannot be extracted multiple times at the same position information, determine whether there are a large number of homologous image points extracted within the extraction cell, indicating that the division of the extraction cell is unreasonable. If so, re-divide the extraction cell to improve the accuracy and uniformity of the extraction of homologous image points.

[0021] Further, in the second step, before extracting the homologous image points, first obtain the spacing value of the cameras, obtain the overlap degree of the coal wall images captured by the cameras according to the spacing value, and then determine the thresholds in the preset quantity order from the left and right sides of the captured coal wall images according to the overlap degree, and extract the homologous image points for each extraction cell according to the thresholds.

[0022] The beneficial effects are as follows: Due to different coal and rock geological environments, the spacing value between the two cameras during installation is different, and the shooting ranges of the cameras themselves are different, so the overlap degrees of the coal wall images captured by the two cameras are also different, and the distribution of homologous image points on the two coal wall images is different. Therefore, the homologous image points are extracted according to the overlap degree with different quantity order thresholds, improving the uniformity of the extraction of homologous image points on the coal wall image. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flowchart of the first embodiment of the three-dimensional space coordinate positioning method for this coal and rock geological image. DETAILED DESCRIPTION

[0024] The following is a further detailed description through specific embodiments.

[0025] Embodiment 1

[0026] A three-dimensional space coordinate positioning method for coal-rock geological images includes the following steps, as Figure 1 shown:

[0027] Step 1: Install two cameras with fixed relative position information in parallel on a turntable. The relative position information is the change amounts in three directions, the rotation azimuth angle, and the inclination angle of the two cameras in the geodetic coordinate system. The central axes of the two cameras are parallel to each other and the shooting directions of the cameras are the same. The turntable is a transverse plate, and universal joints are installed at both ends of the transverse plate. The cameras are installed on the universal joints. Obtain the camera parameters of the cameras. The camera parameters include the focal length and the internal orientation elements after camera calibration, etc. The two cameras respectively shoot overlapping geological images from both sides. Perform distortion correction on the geological images according to the camera parameters, and perform angular orientation element calculation according to the relative position information. For example, if the camera tilts or moves a certain angle or a certain distance, the position information at the corresponding points on the geological image will tilt or move.

[0028] Step 2: Perform gray-scale processing on the geological images shot by the two cameras. Evenly divide the gray-scale processed geological images into multiple extraction grids. Extract corresponding image points in each extraction grid according to the pixel positions on the coal wall image with several thresholds as the criteria. That is, the number of corresponding image points extracted in the extraction grids at different positions is different, and the sum of the thresholds is equal to the preset number; Use a preset algorithm to extract a preset number of corresponding image points in the gray-scale processed geological image. The preset algorithm is the SURF algorithm; Count the extracted corresponding image points to obtain a count value, and compare the count value with the preset number in real time. When the count value is equal to the preset number, stop extracting the corresponding image points. When the extraction of the corresponding image points on the coal wall image is completed and the count value is less than the preset number, re-extract the corresponding image points, and collect the pixel coordinates of the corresponding image points on the geological image.

[0029] Step 3: According to the camera parameters and the pixel coordinates, use the space resection method to construct a collinear equation system for each camera, and calculate the internal orientation elements, the external orientation elements, and the distortion residuals. The principle of constructing the collinear equation system and calculating the corresponding internal orientation elements, external orientation elements, and distortion residuals is the prior art and will not be elaborated here.

[0030] For two cameras with known positions, there is no need to calculate the relative position through subsequent aerotriangulation algorithms, reducing the running time of the aerotriangulation algorithms. And after gray processing the geological images, corresponding image points are extracted. Compared with the original color geological images, instead of extracting three sets of data for the three primary colors respectively, only one set of data needs to be extracted for calculation, and using the SURF algorithm greatly reduces the amount of calculation and the running time of subsequent algorithms. It can also overcome the errors caused by cameras whose two optical axis centers are not strictly collinear, improving the accuracy of photogrammetry. In addition, after shooting the geological images, the interior orientation elements are calculated again, which is equivalent to calibrating the two cameras separately again to prevent errors caused by bumps during the transportation of the cameras. By dividing the extraction grid and extracting corresponding image points within each extraction grid, the stability of corresponding image point extraction is improved.

[0031] Embodiment 2

[0032] The difference from Embodiment 1 is that in Step 2, the corresponding image points extracted within each extraction grid are counted to obtain a single value, and the single value is compared with a threshold. When the single value is less than the threshold after the corresponding image points in any extraction grid are extracted, the extraction of corresponding image points is stopped. At the same time, the position information of this extraction grid on the geological image is recorded. This position information is pixel position information, and when re-extracting corresponding image points, the corresponding image points are extracted starting from this position information as the initial position; when it is determined again that the single value is less than the threshold, it is judged whether the multiple recorded position information is located within the same extraction grid. If it is judged that multiple position information is located within the same extraction grid, then it is further judged whether there is a single value within the extraction grid that is greater than the threshold. If so, the extraction grid is re-divided with a reduced size, and then the corresponding image points are re-extracted.

[0033] By stopping the extraction and recording the position information when it is judged that the single value of the corresponding image points extracted within a certain extraction grid is small, and performing the corresponding image point extraction starting from the position information as the initial position during re-extraction. If there are no corresponding image points within this extraction grid, the extraction can be stopped immediately, avoiding the time delay caused by re-extracting when the number of corresponding image points on the coal wall image is incorrect after extraction. In addition, the multiple recorded position information is judged. When the multiple recorded position information is located within the same extraction grid, it is judged whether there is a single value within the extraction grid that is greater than the threshold. If so, the extraction grid is re-divided for re-extraction to ensure the uniformity of corresponding image point extraction.

[0034] Embodiment 3

[0035] The difference from the second embodiment is that in step two, before extracting the corresponding image points with the same name, the distance value between the cameras is first obtained, and the overlapping degree of the coal wall images captured by the cameras is obtained according to the distance value. The distance value and the overlapping degree are pre-set in a one-to-one correspondence. Then, according to the overlapping degree, thresholds in the preset quantity order are respectively determined from the left and right sides of the captured coal wall images. For each extraction grid, the corresponding image points with the same name are extracted according to the thresholds. The overlapping degree can be expressed as a percentage. For example, when the overlapping degree is 80% and 20 corresponding image points with the same name are to be extracted, the threshold of the left 1 / 5 of the left coal wall image is 0. For the coal wall image of the left camera in the overlapping area, the thresholds in the preset quantity order are 1, 2, 2, 1. The coal wall image of the right camera can be adaptively set. Then, for the coal wall image of the left camera divided into extraction grids of 4*4 specifications, the thresholds of the corresponding image points with the same name extracted successively in each column of extraction grids from left to right are: the first column is 0, 0, 0, 0, the second column is 1, 1, 1, 1, the third column is 2, 2, 2, 2, and the fourth column is 1, 1, 1, 1. For the coal wall image of the right camera divided into extraction grids of 4*4 specifications, the thresholds of the corresponding image points with the same name extracted successively in each column of extraction grids from right to left are: 0, 0, 0, 0, the second column is 1, 1, 1, 1, the third column is 2, 2, 2, 2, and the fourth column is 1, 1, 1, 1.

[0036] Due to different coal and rock geological environments, the distance value between the two cameras during installation is different, and the shooting ranges of the cameras themselves are different. Therefore, the overlapping degrees of the coal wall images captured by the two cameras are different, and the distribution of the corresponding image points with the same name on the two coal wall images is different. Therefore, by extracting the corresponding image points with the same name according to the thresholds in different quantity orders according to the overlapping degree, the uniformity of the extraction of the corresponding image points with the same name on the coal wall image is improved.

[0037] The above are only the embodiments of the present invention. Common knowledge such as the specific structures and characteristics in the solutions is not described in detail here. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the implementation effect of the present invention and the practicality of the patent. The protection scope required by this application should be subject to the content of its claims, and the specific implementation manners described in the specification can be used to explain the content of the claims.

Claims

1. A three-dimensional space coordinate positioning method for coal-rock geological images, characterized in that It includes the following steps: Step 1: Install two cameras with fixed relative position information parallelly on the turntable, obtain the camera parameters of the cameras, have the two cameras respectively capture overlapping geological images from both sides, perform distortion correction on the geological images according to the camera parameters, and perform angular orientation element calculation according to the relative position information; Step 2: Perform gray processing on the geological images captured by the two cameras, use a preset algorithm to extract a preset number of homologous image points in the gray-processed geological images, and collect the pixel coordinates of the homologous image points; Before extracting the homologous image points, first evenly divide the gray-processed geological image into multiple extraction grids, extract homologous image points in each extraction grid according to the pixel positions on the coal wall image with several thresholds as the criteria, the sum of the thresholds is equal to the preset number, count the homologous image points extracted in each extraction grid to obtain a single value, compare the single value with the threshold, and when the single value is less than the threshold after the extraction of homologous image points in any extraction grid is completed, stop extracting homologous image points; When the single value is less than the threshold after the extraction of homologous image points in any extraction grid is completed, record the position information of this extraction grid on the geological image, and use this position information as the initial position to extract homologous image points when re-extracting homologous image points. When it is determined again that the single value is less than the threshold, determine whether the multiple recorded position information is located in the same extraction grid. If it is determined that multiple position information is located in the same extraction grid, then further determine whether there is a single value in the extraction grid that is greater than the threshold. If so, re-divide the extraction grid with a reduced size and then re-extract homologous image points; Step 3: According to the camera parameters and pixel coordinates, use the method of space resection to construct a collinear equation system for each camera, and calculate the interior orientation elements, exterior orientation elements, and distortion residuals.

2. The three-dimensional spatial coordinate positioning method for coal-rock geological images according to claim 1, characterized in that: In the above Step 2, count the extracted homologous image points to obtain a count value, and compare the count value with the preset number in real time. When the count value is equal to the preset number, stop extracting homologous image points. When the extraction of homologous image points on the coal wall image is completed and the count value is less than the preset number, re-extract homologous image points.

3. The three-dimensional space coordinate positioning method of the coal-rock geological image according to claim 1, characterized in that: In Step 2, before extracting homologous image points, first obtain the spacing value of the cameras, obtain the overlap degree of the coal wall images captured by the cameras according to the spacing value, and then determine the thresholds in the preset number order from the left and right sides of the captured coal wall images according to the overlap degree, and extract homologous image points in each extraction grid according to the thresholds.

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