|
|
|
| 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 |
|
|
|
|
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.
|
|
Received: 19 March 2015
|
| Fund: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) |
|
Corresponding Authors:
PENG Bo,E-mail address:pengbo351@126.com
E-mail: pengbo351@126.com
|
|
|
|
[1] WANG K C P. Design and Implementation of Automated Systems for Pavement Surface Distress Survey[J]. Journal of Infrastructure Systems, 2000, 6(1):24-32.
[2] WANG K C P, HOU Z Q, GONG W G. Automated Road Sign Inventory System Based on Stereo Vision and Tracking[J]. Computer-Aided Civil and Infrastructure Engineering, 2010, 25(6):468-477.
[3] SUN Bo-cheng, QIU Yan-jun. Pavement Crack Diseases Recognition Based on Image Processing Algorithm[J]. Journal of Highway and Transportation Research and Development, 2008, 25(2):64-68. (in Chinese)
[4] JITPRASITHSIRI S. Development of a New Digital Pavement Image Processing Algorithm for Unified Crack Index Computation[D]. Salt Lake City:University of Utah, 1997.
[5] ZHANG Juan, SHA Ai-min, SUN Chao-yun, et al. Pavement Crack Automatic Recognition Based on Phase-Grouping Method[J]. China Journal of Highway Transport, 2008, 21(2):39-42. (in Chinese)
[6] WANG Qian-qian, PENG Zhong, LIU Li. An Adaptive Method of Image Segmentation[J]. Transactions of Beijing Institute of Technology, 2003, 23(4):521-524.(in Chinese)
[7] CANNY J. A Computational Approach to Edge Detection[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence, 1986, 8(6):679-698.
[8] ZHOU J, HUANG P S, CHIANG F P. Wavelet-based Pavement Distress Detection and Evaluation[J]. Optical Engineering, 2006, 45(2):409-411.
[9] NEJAD F M, ZAKERI H. A Comparison of Multi-resolution Methods for Detection and Isolation of Pavement Distress[J]. Expert Systems with Applications, 2011(38):2857-2872.
[10] HUANG Y X, XU B G. Automatic Inspection of Pavement Cracking Distress[J]. Journal of Electronic Imaging, 2006, 15(1):185-188.
[11] GAVILÁN M, BALCONES D, MARCOS O, et al. Adaptive Road Crack Detection System by Pavement Classification[J]. Sensors, 2011(11):9628-9657.
[12] MA Chang-xia, ZHAO Chun-xia, DI Feng, et al. Road Crack Detection under Natural Environment[J]. Journal of Engineering Graphics, 2011, 32(4):20-26. (in Chinese)
[13] ZHAO Ke. Design and Research of Pavement Crack Identification System[D]. Xi'an:Chang'an University, 2009. (in Chinese)
[14] LI Gang, HE Yu-yao. A Novel Image Detection and Classification for Pavement Crack under Non-Uniform Illumination[J]. ACTA Photonica Sinica, 2010, 39(8):1405-1408. (in Chinese)
[15] LI L, CHAN P, RAO A, et al. Flexible Pavement Distress Evaluation Using Image Analysis[C]//Application of Advanced Technologies in Transportation Engineering. Minneapolis:ASCE, 1991, 473-477.
[16] CHENG H D, CHEN J R, GLAZIER C, et al. Novel Approach to Pavement Cracking Detection Based on Fuzzy Set Theory[J]. Journal of Computing in Civil Engineering, 1999(13):270-280.
[17] ZOU Q, CAO Y, LI Q Q, et al. CrackTree:Automatic Crack Detection from Pavement Images[J]. Pattern Recognition Letters, 2012, 33(3):227-238. |
| [1] |
LI Ning, MA Biao, LI Rui, SI Wei. Performance of Unbound Aggregate Materials under Single-stage and Multi-stage Loading Modes Based on Precision Unbounded Material Analyzer[J]. Journal of Highway and Transportation Research and Development, 2019, 13(2): 1-12. |
| [2] |
XU Hai-liang, REN He-huan, HE Zhao-cai, HE Lian. Time-domain Analysis of Deformation Characteristics of Asphalt Concrete Pavement Considering Vehicle-pavement Coupled Effect[J]. Journal of Highway and Transportation Research and Development, 2019, 13(2): 13-19. |
| [3] |
DU Jian-huan, AI Chang-fa, HUANG Chao, GUO Yu-jin, JIANG Yun-bing. Effect of Interfacial Water on the Fatigue Performance of Composite Asphalt Mixture Beams[J]. Journal of Highway and Transportation Research and Development, 2019, 13(1): 1-7. |
| [4] |
YAO Guo-qiang, YAN Zhi-xin, LONG Zhe, ZHAI Ju-yun. Simulation Experimental Study on Shear Stress Distribution of Rock Slope Anchoring Interface[J]. Journal of Highway and Transportation Research and Development, 2019, 13(1): 8-15. |
| [5] |
LIU Ze, HE Fan, HUANG Tian-qi, JIANG Mei-dong. Additional Earth Pressure of Retaining Wall Caused by Vehicle Load[J]. Journal of Highway and Transportation Research and Development, 2019, 13(1): 16-23. |
| [6] |
QIU Xin, XU Jing-xian, TAO Jue-qiang, YANG Qing. Asphalt Pavement Icing Condition Criterion and SVM-based Prediction Analysis[J]. Journal of Highway and Transportation Research and Development, 2018, 12(4): 1-9. |
|
|
|
|
2016, Vol. 10 
