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14 December 2015 Pavement crack detection combining non-negative feature with fast LoG in complex scene
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Proceedings Volume 9812, MIPPR 2015: Automatic Target Recognition and Navigation; 98120L (2015) https://doi.org/10.1117/12.2205292
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
Pavement crack detection is affected by much interference in the realistic situation, such as the shadow, road sign, oil stain, salt and pepper noise etc. Due to these unfavorable factors, the exist crack detection methods are difficult to distinguish the crack from background correctly. How to extract crack information effectively is the key problem to the road crack detection system. To solve this problem, a novel method for pavement crack detection based on combining non-negative feature with fast LoG is proposed. The two key novelties and benefits of this new approach are that 1) using image pixel gray value compensation to acquisit uniform image, and 2) combining non-negative feature with fast LoG to extract crack information. The image preprocessing results demonstrate that the method is indeed able to homogenize the crack image with more accurately compared to existing methods. A large number of experimental results demonstrate the proposed approach can detect the crack regions more correctly compared with traditional methods.
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Wanli Wang, Xiuhua Zhang, and Hanyu Hong "Pavement crack detection combining non-negative feature with fast LoG in complex scene", Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 98120L (14 December 2015); https://doi.org/10.1117/12.2205292
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