Pavement crack detection based on texture feature

Xiuhua Zhang; Yanjun Chen; Hanyu Hong

doi:10.1117/12.903045

8 December 2011 Pavement crack detection based on texture feature

Xiuhua Zhang, Yanjun Chen, Hanyu Hong

Proceedings Volume 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis; 80030C (2011) https://doi.org/10.1117/12.903045
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

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.

Citation Download Citation

Xiuhua Zhang, Yanjun Chen, and Hanyu Hong "Pavement crack detection based on texture feature", Proc. SPIE 8003, MIPPR 2011: Automatic Target Recognition and Image Analysis, 80030C (8 December 2011); https://doi.org/10.1117/12.903045

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