Pavement crack disease detection system and method

Abstract

The invention provides a pavement crack disease detection method. The method comprises the following steps: laser generators emitting laser beams to lanes to form a series-connected bending marking line on the to-be-detected pavement; an image acquisition device, based on a preset collection period, acquiring a series-connected bending marking line image to obtain marking line images; carrying out high-pass filtering on the marking line images to obtain pulse elevation numerical images of the pavement crack disease; and processing the pulse elevation numerical images to obtain a result of the pavement crack disease. According to the pavement crack disease detection method, automatic and intelligent treatment of the pavement disease is realized, the problem that pseudo-cracks generated by water traces and oil traces, existing in an image photography method generally adopted at home and abroad, is solved, so that the automatic interpretation of complex grey-scale patterns is realized, relevant information of the pavement disease is directly obtained through processing, manual interpretation is not needed, and safety is guaranteed.

Description

technical field [0001] The invention relates to the field of pavement detection systems, in particular to a method and system for measuring cracks and pits in the pavement of roads or other similar structures. Background technique [0002] At present, in the field of pavement crack detection, the damage of crack damage mainly adopts manual direct observation and interpretation and the crack recognition method of crack two-dimensional image by computer. The main problem of using manual direct observation and interpretation is that real-time detection cannot be carried out, and normal driving safety is affected during the detection process, and the detection efficiency and detection accuracy need to be improved. [0003] The crack identification method based on the crack two-dimensional image is based on the difference between the illumination characteristics of cracks under certain lighting conditions and the road surface itself, but this is not the essential characteristic o...

AI Technical Summary

Problems solved by technology

The main problem of using manual direct observation and interpretation is that real-time detection cannot be carried out, which affects normal driving safety during the detection process, and the detection efficiency and detection accuracy need to be improved

[0003] The crack identification method based on the crack two-dimensional image is based on the difference between the illumination characteristics of cracks under certain lighting conditions and the road surface itself, but this is not the essential characteristic of cracks, because the principle of two-dimensional image sensing cannot be completely overcome , the interference factors such as lighting conditions, shadows, road oil, sundries and other interference factors in the acquisition process, the information obtained only through the crack two-dimensional image cannot extract the complete crack information, and cannot reflect the depth characteristics of the crack

[0004] Recently, a three-dimensional visualization measurement system using GNSS (Global Navigation Satellite System) has also been produced. This system collects data through connecting satellite systems and transmits it to dedicated equipment for reading and writing. It can achieve more accurate measurement results, but its price Expensive, not suitable for general large-scale use

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