Pavement crack detecting method based on active contour model

Abstract

The invention provides a method for enhancing a pavement image, and relates to a pavement crack detecting method based on an active contour model. The pavement crack detecting method based on the active contour model comprises the following steps of: enhancing the contrast of a pavement crack image; carrying out accurate detection of a pavement crack area on the image with an enhanced contrast; and classifying pavement cracks based on an accurate detection result. According to the technical scheme provided by the invention, various crack images obtained in the high-speed operation process in a natural scene can be automatically identified. With the adoption of the method provided by the invention, the high-accuracy positioning of a crack suspicious area is realized, and the robustness identification is carried out on an area with a positioning error by using various sample classification methods.

Description

Technical field [0001] The invention relates to an automatic detection technology, in particular to a method for enhancing road image and a road crack detection method based on an active contour model. Background technique [0002] Cracks are the most common disease on highway pavements, which are extremely harmful to highways. Especially in winter and spring, due to the infiltration of rain and snow from time to time, under the action of the traffic load, the road surface disease that is already in a cracked state becomes more serious. Failure to discover pavement diseases in time has brought a lot of trouble to road maintenance, increased maintenance costs, and, to a certain extent, also delayed road maintenance. The traditional method of pavement crack detection is to use manual on-site visual measurement and investigation. This method has subjective interpretation errors and low efficiency, which greatly affects the timeliness, scientificity and accuracy of information on t...

AI Technical Summary

Problems solved by technology

[0014] The reasons for the low accuracy of existing methods for locating suspicious areas of cracks are as follows: (1) The cracks are complicated, such as water damage such as potholes, looseness, etc., and fluid deformation caused by vehicle withdrawal and pushing, resulting in shape, area and depth. Various cracks

(2) Since the imaging device itself is shooting in the process of high-speed operation in natural scenes, factors such as noise and shadows formed by light will interfere with the detection of suspicious areas

[0015] In other words, the existing crack detection methods (whether digital image processing-based methods or "semi-automatic detection methods") require human participation in the identification process, rather than automatic detection in the true sense

The reason is that there is a contradiction in the current crack detection method, that is, the existing method has low positioning accuracy for the suspicious area of ​​the crack, and at the same time, the crack classification requires high positioning accuracy for the suspicious area

Images