1. School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China;
2. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu Sichuan 610031, China
De-noising Algorithm for Pavement Crack Images Based on Bi-layer Connectivity Checking
PENG Bo1, FU Yu1, JIANG Yang-sheng2
1. School of Traffic and Transportation, Chongqing Jiaotong University, Chongqing 400074, China;
2. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu Sichuan 610031, China
摘要A de-noising algorithm was designed on the basis of connectivity checking of pixel and crack block levels to remove isolated noises in pavement crack images and to retain the fine features of crack edges. This algorithm comprises three main parts, namely, (1) Pixel connectivity checking to eliminate pixels with poor connexity, (2) A de-noising algorithm to remove insular target regions, and (3) An 8×8 cracking block de-noising algorithm. The algorithm procedures and parameter selection issues were presented. Performance tests on the proposed algorithm and two commonly used methods (median filtering and the algorithm based on long line and black pixel percentage) were conducted using Visual Studio 2008 and OpenCV. Results indicated that the proposed algorithm could effectively remove isolated noises and maintain the continuity of cracking edges with higher precision(85.06%) and recall (85.80%) and better F1 scores (0.74% to 19.19% and 0.20% to 12.06%) in comparison with the other two methods.
Abstract：A de-noising algorithm was designed on the basis of connectivity checking of pixel and crack block levels to remove isolated noises in pavement crack images and to retain the fine features of crack edges. This algorithm comprises three main parts, namely, (1) Pixel connectivity checking to eliminate pixels with poor connexity, (2) A de-noising algorithm to remove insular target regions, and (3) An 8×8 cracking block de-noising algorithm. The algorithm procedures and parameter selection issues were presented. Performance tests on the proposed algorithm and two commonly used methods (median filtering and the algorithm based on long line and black pixel percentage) were conducted using Visual Studio 2008 and OpenCV. Results indicated that the proposed algorithm could effectively remove isolated noises and maintain the continuity of cracking edges with higher precision(85.06%) and recall (85.80%) and better F1 scores (0.74% to 19.19% and 0.20% to 12.06%) in comparison with the other two methods.
基金资助:Supported by the National Natural Science Foundation of China (No.51108391); the Science and Technology Innovation Project of Chongqing (No. cstc2015shms-ztzx0127; No. cstc2015shms-ztzx0177); the Scientific Research Foundation of Chongqing Jiaotong University (No.15JDKJC-A002)
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PENG Bo, FU Yu, JIANG Yang-sheng. De-noising Algorithm for Pavement Crack Images Based on Bi-layer Connectivity Checking. Journal of Highway and Transportation Research and Development, 2016, 10(3): 18-25.
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2016, Vol. 10 
