Weighted Neighborhood Pixels Segmentation Method for Automated Detection of Cracks on Pavement Surface Images-Reference-Cited by-同舟云学术

Weighted Neighborhood Pixels Segmentation Method for Automated Detection of Cracks on Pavement Surface Images

Published:2016-03 Issue:2 Volume:30 Page:04015021
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Sun Lu¹,Kamaliardakani Mojtaba²,Zhang Yongming³

Affiliation:

1. Professor, School of Transportation, Southeast Univ., Nanjing, Jiangsu 210096, China; Professor and Chairman, Dept. of Civil Engineering, Catholic Univ. of America, Washington, DC 20064; and Adjunct Professor, School of Architecture and Civil Engineering, Xiameng Univ., Xiameng, China (corresponding author).

2. Ph.D. Candidate, School of Transportation, Southeast Univ., Nanjing, Jiangsu 210096, China.

3. Postdoctoral Researcher, School of Transportation, Southeast Univ., Nanjing, Jiangsu 210096, China; and Tianjin Bureau of Highway Quality and Safety Inspection, Nankai District, Tianjin 300384, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0000488

Reference41 articles.

1. AASHTO. (2005). “Standard practice for quantifying cracks in asphalt pavement surface.” PP 44-01 Washington DC.

2. Automatic Road Pavement Assessment with Image Processing: Review and Comparison

3. Chen B. Cao W. and He Y. (2012). “Fractal dimension applied in highway surface crack detection.” Proc. 4th Int. Conf. on Digital Image Processing (ICDIP 2012) International Society for Optics and Photonics Bellingham WA.

4. Novel Approach to Pavement Cracking Detection Based on Fuzzy Set Theory

5. Novel System for Automatic Pavement Distress Detection

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