A method for automatic extraction of road surface defects in road laser point cloud

Abstract

The invention discloses a method for automatically extracting road surface diseases from road laser point clouds. Firstly, according to the original road point cloud data, a seed point containing road surface disease information is selected; and the complete road surface disease information is obtained by using the inverse distance weight interpolation of the circular neighborhood constraint. All the seed points; use histogram statistics to denoise the seed points, and then calculate the slope by rasterization and perform a median filter considering the disease feature constraints to eliminate the salt and pepper noise; then linear normalize to generate road surface disease feature images, using the moving window Binarize the image using the method; then perform morphological denoising on the distribution characteristics of the disease neighborhood; finally cluster and grow the road surface disease, generate editable road surface disease vector element results, and complete the automatic extraction of road surface diseases. The invention adopts the method of combining laser point cloud and image processing, creates a new method of using laser point cloud to completely extract road surface diseases, and provides reliable data support for road maintenance management.

Description

technical field [0001] The invention belongs to the technical field of laser point cloud data processing, and in particular relates to a method for automatically extracting road surface diseases from road laser point clouds. Background technique [0002] Road traffic plays an important role in the national economy and people's life, which greatly promotes the development of the national economy. With the increase of road service life and the impact of extreme conditions such as rain and snow, high temperature, and overloading, most road surfaces have various degrees of disease, such as potholes, cracks, mesh cracks, subsidence, rutting, and looseness, etc. , thus affecting the normal use of the road and bringing great traffic safety hazards. Pavement maintenance has become more and more important, and pavement disease detection is an important early stage of maintenance work. Timely and accurate pavement disease detection can save maintenance costs and provide guarantee fo...

AI Technical Summary

Problems solved by technology

[0003] In my country, manual or semi-mechanized methods are still used in the detection of road surface conditions. Not only is the efficiency low, only sampling inspection is possible, but also the road needs to be closed, which has a great impact on normal road traffic.

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