Mountain crack detection method based on image local reinforcement

Abstract

The invention discloses a mountain crack detection method, comprising: analyzing collected images through an image sliding window, and determining the contrast ratio of each pixel point in the images; in dependence on contrast ratios, constructing and analyzing a contrast graph, determining the optimal segmentation threshold of the contrast graph, determining an area to be enhanced in dependence on the threshold, and performing image reinforcement processing on the area to be enhanced; analyzing processed images, and determining a gray scale characteristic graph and a variance characteristic graph; calculating optimal segmentation thresholds of the gray scale characteristic graph and the variance characteristic graph, and the binary images of contrast characteristics and variance characteristics, and performing AND operation on the two binary images to determine the binary image of racks; transforming the binary of racks to determine a refined frame, and performing area extension processing on the frame to obtain all crack latent areas on the frame; and traversing frame pixels to obtain crack length information, and calculating a crack area in dependence on the number of area pixels.

Description

technical field [0001] The invention relates to the technical field of digital image processing, in particular to a mountain crack detection method based on local image enhancement. Background technique [0002] With the continuous deterioration of the natural environment and more and more man-made engineering constructions, the number of landslides is increasing every year, and the intensity and frequency are increasing every year. The annual loss caused by landslides in China exceeds 400 million US dollars. Landslides have caused huge property losses and casualties, and it is very necessary to establish an early warning system. [0003] Landslide early warning systems are currently monitored by monitoring instruments. The traditional methods for landslide monitoring are as follows: conventional geodesy; hydrostatic leveling, gravity measurement; groundwater level monitoring; electrical measurement , Underground drilling tilt, etc. Although these methods have played a pos...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the problems in related technologies, the present invention proposes a mountain crack detection method based on local image enhancement, which solves the problem of difficult identification of mountain cracks, and has the advantage of non-contact measurement compared with traditional instrument monitoring methods, and is suitable for real-time monitoring in the field surroundings

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