Crack Detection in Pavement Images Based on a Self- Adaptive Niche Algorithm
Year: 2021
Type: article
Abstract: This study focuses on optical image pavement damage detection instead of artificial detection in pavement maintenance. Based on the characteristics of cracks and combined with the niche theory, it proposes a dynamic adaptive curve extraction algorithm. First, we construct the matrix space, map the original pavement image data to the target space, process the data in target space using the multi-trough algorithm, then connect the extreme gray value points between two adjacent scanning rows with lines, compare the average gray value of the line with the average gray value of this area, and judge the possibility of cracks according to curve extension characteristics. The method considers oil, water stain, irregular concave spot, and other kinds of image noise on the pavement surface. It has good adaptability, and experimental results show that the algorithm is effective.
Authors: Peng Bai, Linfeng Chen, Songrong Jiang, Yu Gong, Qishen Li
Institution: Civil Aviation University of China
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3208938786