Water conservancy project measurement method and system

Abstract

The invention relates to the technical field of engineering measurement, in particular to a hydraulic engineering measurement method and system, and the method comprises the following steps: based on a target hydraulic engineering river channel environment, in a differentiated weather state, capturing a river channel image, marking environment condition parameters in a river channel image collection process, and obtaining a reference image database; according to the method, the current image is adjusted and optimized through construction and comparison of the reference image library, the color balance and the contrast ratio of the image are improved, the image is clearer, the subsequent boundary recognition effect is enhanced, image correction and integration are carried out through image stacking and pixel point comparison and analysis on boundary data processing, and the boundary recognition efficiency is improved. According to the method, the image analysis continuity and accuracy are improved, the river channel width is calculated, the river channel length is calculated under the condition that the river channel width is considered, more accurate river channel size data are provided, and a scientific basis is provided for planning and construction of a water conservancy project.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering surveying, and particularly relates to a water conservancy project surveying method and system. Background Art

[0002] The technical field of engineering surveying involves using a variety of surveying tools and techniques to determine the location, boundaries, shape, and topography of land. Techniques in the field of engineering surveying include total station surveying, GPS technology, unmanned aerial vehicle mapping, and laser scanning. The purpose of engineering surveying is to ensure the accurate construction of infrastructure projects such as roads, bridges, buildings, and dams. Through precise measurements, the correct implementation of engineering designs can be ensured, errors during the construction process can be reduced, and the safety and durability of engineering structures can be ensured.

[0003] Among them, the water conservancy project surveying method is mainly used for various surveying tasks in the construction and maintenance of water conservancy projects. The surveying method ensures the accurate layout and construction of water conservancy facilities such as dams, rivers, reservoirs, and irrigation systems. By precisely measuring the hydrogeological environment, the water conservancy project surveying method supports the optimized design and efficient management of water conservancy facilities. Its uses include topographic mapping before construction, monitoring and adjustment during construction, and deformation monitoring and environmental impact assessment after construction, ensuring that the safety, stability, and environmental protection of water conservancy projects meet the planning requirements.

[0004] Traditional surveying methods use a variety of surveying tools such as total stations and GPS, and conduct surveys manually. This method requires manual surveying in the field environment. Not only is the labor intensity relatively large, but also in a complex and dangerous water environment, the surveying process is risky, it is difficult to achieve a good surveying effect, and manual surveying takes a lot of time, making it difficult to meet the high-efficiency and precise surveying requirements of water conservancy projects, unable to provide sufficient support for water conservancy projects, resulting in errors in engineering design and maintenance, and affecting the safety and sustainability of the project. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies existing in the prior art, and to propose a water conservancy project surveying method and system.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions: A water conservancy project surveying method, comprising the following steps:

[0007] S1: Based on the river channel environment of the target water conservancy project, capture river channel images under different weather conditions, and mark the environmental condition parameters during the acquisition process of the river channel images to obtain a reference image database;

[0008] S2: Based on the reference image database, adjust the color value and brightness value of each pixel point of the current river channel image according to the color temperature, contrast, and deviation between the current river channel image and the reference image to obtain a calibrated image;

[0009] S3: Based on the calibrated image, through image analysis, identify the boundary between water and non-water in the image, mark the river channel boundary in the image, and obtain the image boundary recognition result;

[0010] S4: Based on the image boundary recognition result, through image stacking and pixel point comparison analysis, perform rotation, scaling, and stretching correction on multiple river channel images, splice and integrate multiple river channel images, and construct the boundary image of the entire river channel to obtain the boundary data integration result;

[0011] S5: Based on the boundary data integration result, calculate the river channel width parameters of the differential nodes in the image data, and calculate the length of the river channel target area by connecting the midpoints of the river channel widths to obtain the river channel size data measurement result;

[0012] S6: Based on the river channel size data measurement result, by analyzing the river channel size data over a period of time, identify the width and position changes of the differential river channel nodes, and identify the target project node positions according to the target width of the water conservancy project and the length of the river channel nodes to obtain the water conservancy project target position recognition result.

[0013] As a further solution of the present invention, the reference image database includes the illumination intensity level of the image, the weather type label, and the image capture time. The calibrated image includes the color temperature adjustment range, the contrast enhancement degree, and the brightness adjustment ratio. The image boundary recognition result includes the water body edge pixel coordinate set and the segmentation line between the river channel and the non-water area. The boundary data integration result includes the image splicing seam position, the continuity verification information of the river channel boundary line, and the image rotation and scaling parameters. The river channel size data measurement result includes the maximum width, minimum width, average width of the river channel, and the measurement data of the river channel target area length. The water conservancy project target position recognition result includes the coordinate positions of the key nodes and the width change sensitive areas.

[0014] As a further solution of the present invention, based on the target water conservancy project river channel environment, under different weather conditions, capture river channel images and mark the environmental condition parameters during the acquisition process of the river channel images. The steps to obtain the reference image database are specifically as follows:

[0015] S101: Based on the target water conservancy project river channel environment, deploy acquisition equipment, adjust the equipment parameters according to the real-time weather conditions, including the exposure time and the sensitivity, and acquire river channel images to obtain the original image set;

[0016] S102: Based on the original image set, annotate each image, record the lighting conditions and weather status during shooting, including the sunshine intensity and rainfall, and mark the time and location of the image shooting to obtain the environmental condition annotated image;

[0017] S103: Annotate the images based on the environmental conditions, classify and sort the images, group them according to the lighting and weather conditions, and index the images to obtain a benchmark image database.

[0018] As a further solution of the present invention, based on the benchmark image database, according to the color temperature, contrast, and deviation between the current river channel image and the benchmark image, the steps of adjusting the color value and brightness value of each pixel point of the current river channel image to obtain a calibrated image are specifically as follows:

[0019] S201: Based on the benchmark image database, compare the currently captured river channel image with the images stored in the benchmark image library, and screen out the benchmark images that match the lighting and weather conditions of the current image from the benchmark image database to obtain a benchmark image matching result;

[0020] S202: Based on the benchmark image matching result, analyze the differences in color temperature, contrast, and brightness between the current river channel image and the benchmark image, adjust the parameters of the current river channel image, balance the image color and contrast, and obtain color correction parameters;

[0021] S203: Based on the color correction parameters, adjust the color value and brightness of each pixel point of the current river channel image, optimize the light and dark effect of the image, and obtain a calibrated image.

[0022] As a further solution of the present invention, based on the calibrated image, through image analysis, identify the boundary between water and non-water in the image, mark the river channel boundary in the image, and the steps of obtaining an image boundary recognition result are specifically as follows:

[0023] S301: Based on the calibrated image, use color separation technology to distinguish the water and non-water parts in the image, and optimize the recognition effect of the differentiated area by adjusting the color threshold to obtain water separation data;

[0024] S302: Based on the water separation data, use edge detection technology to identify the boundary of the river channel, and adjust the edge detection threshold to optimize the accuracy of boundary recognition to obtain a boundary marked image;

[0025] S303: Based on the boundary marked image, segment the river channel part from the background, and isolate the river channel part from the background to obtain an image boundary recognition result.

[0026] As a further solution of the present invention, based on the image boundary recognition result, through image stacking and pixel point comparison analysis, perform rotation, scaling, and stretching correction on multiple river channel images, splice and integrate multiple river channel images, and construct the boundary image of the entire river channel to obtain the steps of the boundary data integration result are specifically as follows:

[0027] S401: Based on the image boundary recognition result, perform rotation correction and scaling adjustment on each image to align the images in the same ratio and direction, and adjust the images to a preset standard size and angle to obtain aligned and corrected images;

[0028] S402: Based on the aligned and corrected images, by comparing the pixels in the seam regions of each image, adjust the pixel points at the seams to optimize the visual tomography and perform seamless stitching between the images to obtain seamless stitched images;

[0029] S403: Based on the seamless stitched images, perform beautification processing on the entire river channel image, correct the errors and irregular edges existing after image stitching, and optimize the coherence of the images to obtain the boundary data integration result.

[0030] As a further solution of the present invention, the steps of calculating the river channel width parameter of the differential nodes in the image data based on the boundary data integration result and calculating the length of the target area of the river channel by connecting the midpoints of the river channel widths to obtain the measurement result of the river channel size data are specifically as follows:

[0031] S501: Based on the boundary data integration result, perform scale analysis on the images of each river channel node, calculate the width of each node through the calibrated scale in the image, and record the central coordinates of each width point to obtain the node width and central coordinate data;

[0032] S502: Based on the node width and central coordinate data, calculate the length of the river channel in the target area by analyzing the distance between the central coordinates of adjacent nodes to obtain the river channel length data;

[0033] S503: Based on the river channel length data and the node width and central coordinate data, mark the river channel width data and the river channel length data on the picture and mark the corresponding measurement time to obtain the measurement result of the river channel size data.

[0034] As a further solution of the present invention, the formula for calculating the length of the river channel in the target area is:

[0035]

[0036] where x i and y i respectively represent the horizontal and vertical coordinates of the i-th node, x i+1 and y i+1 respectively represent the horizontal and vertical coordinates of the (i + 1)-th node, w i represents the width of the i-th node, W represents the average width of the river channel, n represents the total number of nodes, and L represents the length of the river channel in the target area.

[0037] As a further solution of the present invention, based on the measurement results of the river channel dimension data, by analyzing the river channel dimension data over a period of time, identifying the width and position changes of the differential river channel nodes, and according to the target width and the river channel node length of the water conservancy project, the steps of identifying the target project node position to obtain the water conservancy project target position identification result are specifically as follows:

[0038] S601: Based on the measurement results of the river channel dimension data, by analyzing the width and position data of the river channel at differential time points, comparing the change trends of the data, identifying the width and position changes of the river channel, and obtaining the river channel width and position change data;

[0039] S602: Based on the river channel width and position change data, analyzing the change trend of the river channel length, evaluating the change rate of the river channel length, and obtaining the river channel length change trend data;

[0040] S603: Based on the river channel length change trend data and the river channel width and position change data, evaluating the compliance degree of the target width and the node length of the water conservancy project, selecting the node position according to the engineering design requirements, and obtaining the water conservancy project target position identification result.

[0041] A water conservancy project measurement system, the water conservancy project measurement system is used to execute the above water conservancy project measurement method, and the system includes:

[0042] The reference image capture module captures river channel images under differential weather conditions based on the river channel environment of the target water conservancy project, marks the environmental condition parameters during the acquisition process of the river channel images, and obtains a reference image database;

[0043] The image correction and processing module adjusts the color value and brightness value of each pixel point of the current river channel image based on the reference image database according to the color temperature, contrast and deviation between the current river channel image and the reference image, optimizes the image contrast and color balance, and obtains a calibrated image;

[0044] The river channel boundary recognition module marks the river channel boundary in the image based on the calibrated image, and splices and integrates multiple river channel images through image stacking and pixel point comparison analysis to obtain a boundary data integration result;

[0045] The river channel length analysis module calculates the river channel width parameters of the differential nodes in the image data based on the boundary data integration result, and calculates the length of the river channel target area by connecting the midpoints of the river channel widths to obtain the measurement result of the river channel dimension data;

[0046] Based on the measurement results of the river channel dimension data, the engineering target position recognition module identifies the width and position changes of the differential river channel nodes by analyzing the river channel dimension data over a period of time, and identifies the target engineering node positions according to the target width of the water conservancy project and the length of the river channel nodes, so as to obtain the recognition result of the water conservancy project target position.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0048] In the present invention, through the construction and comparison of the reference image library, the current image is adjusted and optimized, the color balance and contrast of the image are improved, the image is made clearer, and the subsequent boundary recognition effect is enhanced. In the processing of the boundary data, through the stacking of images and the comparative analysis of pixel points, the image is corrected and integrated, the coherence and accuracy of the image analysis are improved, the river channel width is calculated, and the river channel length is calculated considering the river channel width, providing more accurate river channel dimension data and providing a scientific basis for the planning and construction of water conservancy projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic flow chart of the method of the present invention;

[0050] Figure 2 It is a detailed flow chart of S1 of the present invention;

[0051] Figure 3 It is a detailed flow chart of S2 of the present invention;

[0052] Figure 4 It is a detailed flow chart of S3 of the present invention;

[0053] Figure 5 It is a detailed flow chart of S4 of the present invention;

[0054] Figure 6 It is a detailed flow chart of S5 of the present invention;

[0055] Figure 7 It is a detailed flow chart of S6 of the present invention;

[0056] Figure 8 It is a system flow chart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0058] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0059] Please refer to Figure 1 , the present invention provides a technical solution: a water conservancy project measurement method, including the following steps:

[0060] S1: Based on the target water conservancy project river channel environment, capture river channel images under different weather conditions, mark the environmental condition parameters during the acquisition process of the river channel images, including marking the lighting conditions and weather conditions, and perform data sorting to obtain a reference image database;

[0061] S2: Based on the reference image database, compare the currently captured river channel image with the images stored in the reference image library, identify the reference images with matching lighting conditions and weather conditions, and adjust the color values and brightness values of each pixel point of the current river channel image according to the color temperature, contrast, and deviation between the current river channel image and the reference image to optimize the image contrast and color balance, and obtain a calibrated image;

[0062] S3: Based on the calibrated image, through image analysis, identify the boundary between water and non-water in the image, mark the river channel boundary in the image, mark the river channel boundary line, and separate the river channel part from the background image to obtain an image boundary recognition result;

[0063] S4: Based on the image boundary recognition result, through image stacking and pixel point comparison analysis, perform rotation, scaling, and stretching correction on multiple river channel images, splice and integrate multiple river channel images to construct the boundary image of the entire river channel, and obtain a boundary data integration result;

[0064] S5: Based on the boundary data integration result, calculate the river channel width parameters of different nodes in the image data through the image ratio, and calculate the length of the river channel target area by connecting the midpoints of the river channel widths to obtain the measurement result of the river channel size data;

[0065] S6: Based on the measurement results of the river channel dimension data, by analyzing the river channel dimension data over a period of time, identify the width and position changes of the differential river channel nodes, and analyze the length change of the target area of the river channel. According to the target width of the water conservancy project and the length of the river channel nodes, identify the positions of the target project nodes to obtain the recognition result of the target position of the water conservancy project.

[0066] The reference image database includes the light intensity level of the image, the weather type label, and the image capture time. The calibrated image includes the color temperature adjustment range, the contrast enhancement degree, and the brightness adjustment ratio. The image boundary recognition result includes the set of water body edge pixel coordinates and the segmentation line between the river channel and the non-water body area. The boundary data integration result includes the image stitching seam position, the continuity verification information of the river channel boundary line, and the image rotation and scaling parameters. The measurement result of the river channel dimension data includes the maximum width, minimum width, average width of the river channel, and the measurement data of the length of the target area of the river channel. The recognition result of the target position of the water conservancy project includes the coordinate positions of the key nodes and the width change sensitive area.

[0067] Please refer to Figure 2 , for the steps of capturing river channel images under different weather conditions based on the river channel environment of the target water conservancy project, annotating the environmental condition parameters during the acquisition process of the river channel images, including annotating the lighting conditions and weather states, and performing data collation to obtain the reference image database, specifically as follows:

[0068] S101: Based on the river channel environment of the target water conservancy project, deploy acquisition equipment, adjust the equipment parameters according to the real-time weather conditions, including the exposure time and the sensitivity, and acquire river channel images to obtain the original image set;

[0069] Based on the river channel environment of the target water conservancy project, adjust the parameters of the acquisition equipment according to the real-time weather conditions, such as the exposure time and the sensitivity, to adapt to different lighting and weather conditions, so as to ensure the image quality. For example, according to the increase in cloud density or approaching rain, the processor adjusts the exposure time and the sensitivity in real time. During the adjustment process, the equipment also records the adjusted parameter values and the reasons for adjustment. Each acquired image and its related set parameters are stored in the local memory card to obtain the original image set.

[0070] S102: Based on the original image set, annotate each image, record the lighting conditions and weather states during shooting, including the sunshine intensity and rainfall, and mark the time and location of image shooting to obtain the environmentally condition-annotated images;

[0071] Based on the original image set, each image is annotated, and the shooting time and location are extracted from the metadata of each image. At the same time, the weather conditions and light intensity recorded during the shooting are extracted, including sunlight intensity and rainfall. The information is recorded in the database together with the images. The annotation information of each image also includes the lighting conditions during shooting, and environmental condition annotated images are generated.

[0072] S103: Based on the environmental condition annotated images, the images are classified and sorted, grouped according to lighting and weather conditions, and indexes are established for the images to obtain a reference image database.

[0073] Based on the environmental condition annotated images, according to the lighting and weather condition information in the image tags, the images are grouped and sorted. For example, all images on sunny or cloudy days are grouped separately. Each group of images is further subdivided into different light intensity or rainfall levels to provide a more detailed classification. An index is established for each image, including the unique identifier of the image and the associated environmental parameter tags. In this way, a systematic reference image database is created, which is convenient for future rapid retrieval and comparative analysis, and supports the management and decision-making of water conservancy projects to obtain a reference image database.

[0074] Please refer to Figure 3 , based on the reference image database, compare the currently captured river channel image with the images stored in the reference image library, identify the reference images with matching lighting conditions and weather states, and adjust the color values and brightness values of each pixel point of the current river channel image according to the color temperature, contrast and deviation between the current river channel image and the reference images, optimize the image contrast and color balance. The specific steps to obtain the calibrated image are as follows:

[0075] S201: Based on the reference image database, compare the currently captured river channel image with the images stored in the reference image library, and screen out the reference images that match the lighting and weather states of the current image from the reference image database to obtain the reference image matching result;

[0076] Based on the reference image database, first use image processing software to extract key information from the currently captured river channel image, including light intensity, weather conditions and image shooting time. Compare it with the metadata in the reference image database, and screen out the reference images that match the lighting and weather states of the current image. The selected matching results will be used for subsequent image quality analysis and correction to obtain the reference image matching result.

[0077] S202: Based on the reference image matching result, analyze the differences in color temperature, contrast and brightness between the current river channel image and the reference images, adjust the parameters of the current river channel image, balance the image color and contrast, and obtain the color correction parameters;

[0078] Based on the benchmark image matching results, use image processing software to analyze the specific differences between the current river channel image and the selected benchmark image in terms of color temperature, contrast, and brightness. The analysis process includes calculating the color histograms of the two groups of images and the statistical distribution of brightness values, and determining the color correction parameters that need to be adjusted, such as brightness increase or decrease, contrast adjustment, and color temperature change. The determination of the adjustment parameters is based on the goal of ensuring the optimization of image quality, and the color correction parameters are obtained.

[0079] S203: Based on the color correction parameters, adjust the color values and brightness of each pixel point in the current river channel image to optimize the light and dark effects of the image and obtain the calibrated image.

[0080] Based on the color correction parameters, perform detailed adjustments to the color values and brightness of each pixel point in the current river channel image. The process is executed by image processing software. The software adjusts the image data pixel by pixel according to the color correction parameters determined in the previous step, including adjusting the color balance and brightness contrast of each RGB channel, ensuring that the color of each pixel point is more realistic and conforms to the natural observation effect. The adjusted image is compared with the benchmark image again to verify the effect of color correction. After confirming that no further adjustment is required, the calibrated image is obtained.

[0081] Please refer to Figure 4 , based on the calibrated image, through image analysis, identify the boundary between water and non-water bodies in the image, mark the river channel boundary in the image, mark the river channel boundary line, and separate the river channel part from the background image. The specific steps for obtaining the image boundary recognition result are as follows:

[0082] S301: Based on the calibrated image, use color separation technology to distinguish the water and non-water parts in the image, and optimize the recognition effect of the differentiated area by adjusting the color threshold to obtain water separation data;

[0083] Based on the calibrated image, apply color separation technology to process the calibrated image, analyze the color spectrum in the image, and determine the typical range of water body colors. By setting the color threshold, which is determined through multiple experiments and can effectively distinguish the water body from the surrounding environment. During the process of adjusting the color threshold, the adjustment effect is previewed in real time to ensure that the boundary between the water body and the non-water body part is clearly visible, and the water separation data is obtained.

[0084] S302: Based on the water separation data, use edge detection technology to identify the boundary of the river channel, and adjust the edge detection threshold to optimize the accuracy of boundary recognition to obtain the boundary marked image;

[0085] Based on the water body separation data, edge detection technology is used to analyze the data after water body separation to identify the specific boundaries of the river channel. The edge positions are determined by analyzing the gradient of color changes in the image. Gradient calculation is applied to the separated water body area, and the threshold for edge detection is set according to the gradient intensity. This threshold adjustment is based on experimental data and the expected boundary clarity. The threshold is adjusted through multiple iterations until the boundary line conforms to the actual shape of the river channel, obtaining a boundary marked image that shows the demarcation line between the river channel and the non-water body part.

[0086] S303: Based on the boundary marked image, the river channel part is segmented from the background, and the river channel part is isolated from the background to obtain the image boundary recognition result;

[0087] Based on the boundary marked image, image segmentation technology is adopted to analyze the marked boundary line, and then the image data is divided into the river channel part and the non-river channel part. The segmentation operation is performed relying on accurate boundary line information to ensure that each part of the river channel image is correctly identified and separated. The river channel part is segmented from the background, and the river channel part is isolated from the background to obtain the image boundary recognition result.

[0088] Please refer to Figure 5 , based on the image boundary recognition result, through image stacking and pixel point comparison analysis, multiple river channel images are rotated, scaled and stretched for correction, and multiple river channel images are spliced and integrated to construct the boundary image of the entire river channel. The steps to obtain the boundary data integration result are specifically as follows:

[0089] S401: Based on the image boundary recognition result, each image is rotated and corrected and scaled, and the images are aligned in the same ratio and direction, and the images are adjusted to the preset standard size and angle to obtain the aligned and corrected image;

[0090] Based on the image boundary recognition result, image processing software is used for rotation correction and scaling adjustment to achieve the unified alignment of the images. Through the direction and ratio of each image, the center and boundary coordinates of the image are calculated, and the rotation angle and scaling ratio to be performed are determined. According to the calculation results, each image is automatically adjusted to rotate to the predetermined angle and scale to the standard size to ensure that all images maintain the same direction and size after alignment. After the adjustment is completed, the images are re-encoded and saved to obtain the aligned and corrected image.

[0091] S402: Based on the aligned and corrected image, by comparing the pixels in the seam area of each image, the pixel points at the seam are adjusted to optimize the visual tomogram and perform seamless splicing between the images to obtain the seamless spliced image;

[0092] Based on the aligned and corrected images, by comparing the pixel points in the seam area of each image, the differences in color and brightness are identified, and the visual tomography is optimized by adjusting the pixel points at the seam. The software is used to adjust and smooth the seam area, including color gradient adjustment and pixel fusion techniques. These adjustments ensure that the images are visually seamless, and there is no visual difference in the optimized seam area of the images, making the entire stitching process more accurate and natural, and obtaining a seamlessly stitched image.

[0093] S403: Based on the seamlessly stitched image, beautify the entire river channel image, correct the errors and irregular edges existing after image stitching, and optimize the coherence of the image to obtain the boundary data integration result.

[0094] Based on the seamlessly stitched image, beautify the entire river channel image, including correcting any errors and irregular edges that may occur after stitching. Analyze the stitched image through software, pay attention to the incoherence at the stitching line and the image boundary, make local corrections through image editing tools, and adjust the pixels to eliminate any visual defects at the visually incoherent places, including color correction and edge smoothing, to ensure the overall beauty and coherence of the image and obtain the boundary data integration result.

[0095] Please refer to Figure 6 , the steps for calculating the river channel width parameters of the differential nodes in the image data based on the boundary data integration result through the image scale and calculating the length of the river channel target area by connecting the midpoints of the river channel widths to obtain the river channel size data measurement result are as follows:

[0096] S501: Based on the boundary data integration result, perform scale analysis on the images of each river channel node. Through the calibrated scale in the image, calculate the width of each node and record the central coordinates of each width point to obtain the node width and central coordinate data;

[0097] Based on the boundary data integration result, identify each river channel node through image analysis software and perform scale analysis, identify and apply the scale in the image. The scale is obtained according to the previously set standard or through on-site measurement to ensure the accuracy of width calculation. Through software tools, automatically measure the pixel values of the river channel width in the image and convert them into actual widths. At the same time, the software records the central coordinates of each measurement point, and these coordinates reflect the exact position of each node in the river channel, generating the node width and central coordinate data.

[0098] S502: Based on the node width and central coordinate data, calculate the river channel length of the target area by analyzing the distance between the central coordinates of adjacent nodes to obtain the river channel length data;

[0099] The formula for calculating the river channel length of the target area is:

[0100]

[0101] Among them, x i and y i represent the horizontal and vertical coordinates of the i-th node respectively, and x i+1 and y i+1 represent the horizontal and vertical coordinates of the (i + 1)-th node respectively. w i represents the width of the i-th node, W represents the average width of the river channel, n represents the total number of nodes, and L represents the length of the river channel in the target area.

[0102] Formula:

[0103]

[0104] Detailed Explanation of Parameters and Acquisition Methods:

[0105] x i and y i and x i+1 and y i+1 represent the horizontal and vertical coordinates of the river channel nodes. The coordinate data is obtained by calculating the midpoint of the river channel width in the previous step.

[0106] w i represents the width of the i-th node and is obtained through image analysis in the previous step.

[0107] W represents the average width of the river channel and is the average value of all measured node widths w i .

[0108] n represents the total number of nodes, which is determined according to the project requirements and the specific length of the river channel. Usually, the node interval and total number are determined during the on-site investigation stage.

[0109] Calculation Example

[0110] Suppose the coordinates and widths of four nodes are as follows:

[0111] Node 1: (x1, y1) = (0, 0), w1 = 50 meters.

[0112] Node 2: (x2, y2) = (100, 0), w2 = 70 meters.

[0113] Node 3: (x3, y3) = (100, 100), w3 = 65 meters.

[0114] Node 4: (x4, y4) = (0, 100), w4 = 50 meters.

[0115] Calculation of the average width W:

[0116]

[0117] Calculate the distances between adjacent nodes and accumulate them:

[0118] From node 1 to node 2:

[0119]

[0120] From node 2 to node 3:

[0121]

[0122] From node 3 to node 4:

[0123]

[0124] Total length L:

[0125] L = d 1,2 + d 2,3 + d 3,4

[0126] = 85 + 119 + 111

[0127] = 315 meters

[0128] Calculations show that, considering the influence of node width, the estimated length of the entire river channel is 315 meters. This method adjusts the calculation of the distance between nodes by considering the variation in the width of the river channel, providing a more realistic estimate of the river channel length.

[0129] S503: Based on the river channel length data, node width, and central coordinate data, mark the river channel width data and river channel length data on the picture, and mark the corresponding measurement time to obtain the measurement result of the river channel dimension data.

[0130] Based on the river channel length data, node width, and central coordinate data, data marking is performed on the image. Through an image editing tool, each width point and corresponding length position of the river channel are clearly marked on the image. In addition, the measurement time is also recorded on the image, providing a time reference for each measurement point. The information is automatically added to the corresponding position by image processing software to ensure that each data point is accurately represented, obtaining the measurement result of the river channel dimension data.

[0131] Please refer to Figure 7 , based on the measurement result of the river channel dimension data, by analyzing the river channel dimension data over a period of time, identifying the changes in the width and position of the differential river channel nodes, and analyzing the change in the length of the target area of the river channel, and according to the target width of the water conservancy project and the length of the river channel nodes, identifying the position of the target project nodes to obtain the steps of the identification result of the target position of the water conservancy project are specifically as follows:

[0132] S601: Based on the measurement results of the river channel dimension data, by analyzing the width and position data of the river channel at different time points, comparing the change trends of the data, identifying the changes in the width and position of the river channel, the change data of the river channel width and position is obtained;

[0133] Based on the measurement results of the river channel dimension data, using data analysis software to compare the width and position data of the river channel recorded at different time points, extracting the width and position records of multiple time points from the database, through statistical analysis methods such as time series analysis, calculating the change trends of the width and position, and the analysis includes identifying the standard deviation, average change rate and trend line of the data to ensure that the physical changes of the river channel at different times can be accurately identified, and the change data of the river channel width and position is obtained.

[0134] S602: Based on the change data of the river channel width and position, analyzing the change trend of the river channel length, evaluating the change rate of the river channel length, and obtaining the change trend data of the river channel length;

[0135] Based on the change data of the river channel width and position, analyzing the change trend of the overall length of the river channel, the analysis focuses on measuring and calculating the total length of the river channel at different time points and evaluating its change rate. By performing trend line analysis on the regular measurement data of the river channel length, it can be identified whether the river channel has been shortened or lengthened due to natural erosion, sedimentation or human intervention, and the change trend data of the river channel length is obtained, providing a quantitative way to observe the evolution of the physical characteristics of the river channel and providing support for formulating corresponding water resource management and protection strategies.

[0136] S603: Based on the change trend data of the river channel length and the change data of the river channel width and position, evaluating the compliance degree of the target width and node length of the hydraulic project, and selecting the node position according to the engineering design requirements to obtain the recognition result of the target position of the hydraulic project.

[0137] Based on the change trend data of the river channel length and the change data of the river channel width and position, evaluating the matching degree between the design target and the actual situation of the hydraulic project, by comparing the actual dimension data of the river channel with the engineering design requirements, identifying the best node position that meets the design requirements, ensuring that the selected node position maximally meets the functional and safety requirements of the project, and generating the recognition result of the target position of the hydraulic project.

[0138] Please refer to Figure 8 , a hydraulic project measurement system, which is used to execute the above-mentioned hydraulic project measurement method, and the system includes:

[0139] The reference image capture module captures the river channel images under different weather conditions based on the river channel environment of the target hydraulic project, and marks the environmental condition parameters during the acquisition process of the river channel images to obtain the reference image database;

[0140] The image correction processing module, based on the reference image database, adjusts the color value and brightness value of each pixel point in the current river channel image according to the color temperature, contrast, and deviation between the current river channel image and the reference image, optimizes the image contrast and color balance, and obtains the calibrated image;

[0141] The river channel boundary recognition module, based on the calibrated image, marks the river channel boundary in the image, and through image stacking and pixel point comparison analysis, splices and integrates multiple river channel images to obtain the boundary data integration result;

[0142] The river channel length analysis module, based on the boundary data integration result, calculates the river channel width parameter of the differential nodes in the image data, and by connecting the midpoints of the river channel widths, calculates the length of the river channel target area to obtain the river channel size data measurement result;

[0143] The engineering target position recognition module, based on the river channel size data measurement result, by analyzing the river channel size data over a period of time, identifies the width and position changes of the differential river channel nodes, and according to the target width of the water conservancy project and the length of the river channel nodes, identifies the target engineering node position to obtain the water conservancy project target position recognition result.

[0144] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for surveying water conservancy projects, characterized in that, It includes the following steps: S1: Based on the river channel environment of the target water conservancy project, capture river channel images under different weather conditions, annotate the environmental condition parameters during the acquisition process of the river channel images, and obtain a reference image database; S2: Based on the reference image database, adjust the color value and brightness value of each pixel point of the current river channel image according to the color temperature, contrast and deviation between the current river channel image and the reference image, and obtain a calibrated image; S3: Based on the calibrated image, identify the boundary between water and non-water in the image through image analysis, and mark the river channel boundary in the image to obtain an image boundary recognition result; S4: Based on the image boundary recognition result, perform rotation, scaling and stretching correction on multiple river channel images through image stacking and pixel point comparison analysis, splice and integrate multiple river channel images, and construct the boundary image of the entire river channel to obtain a boundary data integration result; S5: Based on the boundary data integration result, calculate the river channel width parameters of different nodes in the image data, and calculate the length of the river channel target area by connecting the midpoints of the river channel widths to obtain a river channel size data measurement result; S6: Based on the river channel size data measurement result, identify the width and position changes of different river channel nodes by analyzing the river channel size data over a period of time, and identify the target project node positions according to the target width of the water conservancy project and the length of the river channel nodes to obtain a water conservancy project target position recognition result.

2. The method for surveying water conservancy projects according to claim 1, characterized in that The reference image database includes the light intensity level of the image, weather type label and image capture time, the calibrated image includes the color temperature adjustment range, contrast enhancement degree and brightness adjustment ratio, the image boundary recognition result includes the water body edge pixel coordinate set and the segmentation line between the river channel and the non-water area, the boundary data integration result includes the image splicing seam position, the continuity verification information of the river channel boundary line and the image rotation and scaling parameters, the river channel size data measurement result includes the maximum width, minimum width, average width of the river channel and the measurement data of the river channel target area length, and the water conservancy project target position recognition result includes the coordinate positions of key nodes and the width change sensitive area.

3. The method for surveying water conservancy projects according to claim 1, characterized in that, The steps of capturing river channel images under different weather conditions based on the river channel environment of the target water conservancy project, annotating the environmental condition parameters during the acquisition process of the river channel images, and obtaining a reference image database are specifically as follows: S101: Based on the river channel environment of the target water conservancy project, deploy acquisition equipment, adjust the equipment parameters according to the real-time weather conditions, including exposure time and sensitivity, collect river channel images, and obtain an original image set; S102: Based on the original image set, annotate each image, record the lighting conditions and weather conditions during shooting, including sunshine intensity and rainfall, and mark the time and location of image shooting to obtain an environmental condition annotated image; S103: Based on the environmental condition annotated image, classify and organize the images, group them according to lighting and weather conditions, and establish an index for the images to obtain a reference image database.

4. The method for surveying water conservancy projects according to claim 1, characterized in that, Based on the reference image database, the steps of adjusting the color value and brightness value of each pixel point of the current river channel image according to the color temperature, contrast, and deviation between the current river channel image and the reference image to obtain the calibrated image are as follows: S201: Based on the reference image database, compare the currently captured river channel image with the images stored in the reference image library, and screen out the reference images that match the current image's lighting and weather conditions from the reference image database to obtain the reference image matching result; S202: Based on the reference image matching result, analyze the differences in color temperature, contrast, and brightness between the current river channel image and the reference image, adjust the parameters of the current river channel image, balance the image color and contrast, and obtain the color correction parameters; S203: Based on the color correction parameters, adjust the color value and brightness of each pixel point of the current river channel image, optimize the light and dark effect of the image, and obtain the calibrated image.

5. The water conservancy project survey method according to claim 1, wherein Based on the calibrated image, the steps of identifying the water body and non-water body boundaries in the image through image analysis and marking the river channel boundaries in the image to obtain the image boundary recognition result are as follows: S301: Based on the calibrated image, use color separation technology to distinguish the water body and non-water body parts in the image, and optimize the recognition effect of the differentiated area by adjusting the color threshold to obtain the water body separation data; S302: Based on the water body separation data, use edge detection technology to identify the boundaries of the river channel, and adjust the edge detection threshold to optimize the accuracy of boundary recognition to obtain the boundary marked image; S303: Based on the boundary marked image, segment the river channel part from the background, isolate the river channel part from the background, and obtain the image boundary recognition result.

6. The water conservancy project survey method according to claim 1, characterized in that Based on the image boundary recognition result, the steps of performing rotation, scaling, and stretching correction on multiple river channel images through image stacking and pixel point comparison analysis, splicing and integrating multiple river channel images, and constructing the boundary image of the entire river channel to obtain the boundary data integration result are as follows: S401: Based on the image boundary recognition result, perform rotation correction and scaling adjustment on each image, align the images in the same proportion and direction, and adjust the images to the preset standard size and angle to obtain the aligned and corrected images; S402: Based on the aligned and corrected images, compare the pixels in the seam areas of each image, adjust the pixel points at the seams, optimize the visual fault, and perform seamless splicing between the images to obtain the seamless spliced image; S403: Based on the seamless spliced image, perform beautification processing on the entire river channel image, correct the errors and irregular edges existing after image splicing, and optimize the coherence of the image to obtain the boundary data integration result.

7. The method for measuring water conservancy projects according to claim 1, wherein Based on the boundary data integration result, calculate the river channel width parameters of the differentiated nodes in the image data, and calculate the length of the river channel target area by connecting the midpoints of the river channel widths to obtain the measurement result of the river channel size data: S501: Based on the integrated boundary data result, perform scale analysis on the image of each river channel node. Through the calibrated scale in the image, calculate the width of each node, and record the central coordinates of each width point to obtain the node width and central coordinate data; S502: Based on the node width and central coordinate data, calculate the length of the river channel in the target area by analyzing the distance between the central coordinates of adjacent nodes to obtain the river channel length data; S503: Based on the river channel length data and the node width and central coordinate data, mark the river channel width data and the river channel length data on the picture, and mark the corresponding measurement time to obtain the measurement result of the river channel size data.

8. The method for measuring hydraulic engineering according to claim 7, characterized in that, The formula for calculating the length of the river channel in the target area is: where x i and y i represent the horizontal and vertical coordinates of the i-th node respectively, x i+1 and y i+1 represent the horizontal and vertical coordinates of the (i + 1)-th node respectively, w i represents the width of the i-th node, W represents the average width of the river channel, n represents the total number of nodes, and L represents the length of the river channel in the target area.

9. The method for surveying water conservancy projects according to claim 1, characterized in that Based on the measurement result of the river channel size data, by analyzing the river channel size data over a period of time, identify the width and position changes of the differential river channel nodes, and based on the target width of the water conservancy project and the length of the river channel nodes, identify the position of the target project nodes to obtain the steps of the water conservancy project target position identification result are specifically as follows: S601: Based on the measurement result of the river channel size data, by analyzing the width and position data of the river channel recorded at different time points, compare the change trends of the data, and identify the width and position changes of the river channel to obtain the river channel width and position change data; S602: Based on the river channel width and position change data, analyze the change trend of the river channel length, and evaluate the change rate of the river channel length to obtain the river channel length change trend data; S603: Based on the river channel length change trend data and the river channel width and position change data, evaluate the compliance degree of the target width of the water conservancy project and the node length, and select the node position according to the engineering design requirements to obtain the water conservancy project target position identification result.

10. A water conservancy project survey system, characterized in that, According to the water conservancy project measurement method described in any one of claims 1-9, the system includes: The reference image capture module captures river channel images under different weather conditions based on the river channel environment of the target water conservancy project, and marks the environmental condition parameters during the acquisition process of the river channel images to obtain a reference image database; The image correction and processing module adjusts the color value and brightness value of each pixel point of the current river channel image based on the reference image database according to the color temperature, contrast and deviation between the current river channel image and the reference image, and optimizes the image contrast and color balance to obtain a calibrated image; The river channel boundary recognition module marks the river channel boundary in the image based on the calibrated image, and splices and integrates multiple river channel images through image stacking and pixel point comparison analysis to obtain the integrated boundary data result; The river channel length analysis module calculates the river channel width parameters of the differential nodes in the image data based on the integrated boundary data result, and calculates the length of the target area of the river channel by connecting the midpoints of the river channel widths to obtain the measurement result of the river channel size data; The engineering target position recognition module, based on the measurement result of the river channel size data, by analyzing the river channel size data over a period of time, identifies the width and position changes of the differential river channel nodes, and based on the target width of the water conservancy project and the length of the river channel nodes, identifies the position of the target engineering nodes to obtain the water conservancy project target position recognition result.

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