Crack Detection in Pavement Images Based on a Self- Adaptive Niche Algorithm

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 o...

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Bibliographic Details
Published inJournal of Applied Science and Engineering Vol. 25; no. 3; pp. 613 - 626
Main Authors Peng Bai, Linfeng Chen, Songrong Jiang, Yu Gong, Qishen Li
Format Journal Article
LanguageEnglish
Published 淡江大學 01.01.2022
Tamkang University Press
Subjects
crack detection
image processing
niche thought
pavement
pavement
image processing
crack detection
niche thought
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Summary: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.
ISSN:2708-9967
2708-9975
DOI:10.6180/jase.202206_25(3).0018