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Proceedings Paper

Pavement crack detection based on texture feature
Author(s): Xiuhua Zhang; Yanjun Chen; Hanyu Hong
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Paper Abstract

A novel automatic pavement crack detection approach based on texture feature is proposed. The bidirectional multi-level median filter is applied in pretreatment process to eliminate noise while maintain the details of crack edge. Improved center-symmetric local binary pattern (ICS-LBP) texture feature, local correlation texture feature and relative standard deviation texture feature are combined to detect the pavement cracks. Trained-decision strategy is applied to allocate each weight of features and texture features are extracted to train the weights. Experimental results show that the proposed algorithm provides better detection result in comparison with various crack extraction algorithms, and can detect the pavement crack quickly and effectively.

Paper Details

Date Published: 8 December 2011
PDF: 6 pages
Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 80030C (8 December 2011); doi: 10.1117/12.903045
Show Author Affiliations
Xiuhua Zhang, Wuhan Institute of Technology (China)
Yanjun Chen, Wuhan Institute of Technology (China)
Hanyu Hong, Wuhan Institute of Technology (China)

Published in SPIE Proceedings Vol. 8003:
MIPPR 2011: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Nong Sang, Editor(s)

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