The week's pick
Reseach Article
Automatic Road Distress Detection and Analysis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 101 - Number 10 |
| Year of Publication: 2014 |
| Authors: Akhila Daniel, Preeja V |
10.5120/17723-8018
|
Akhila Daniel, Preeja V . Automatic Road Distress Detection and Analysis. International Journal of Computer Applications. 101, 10 ( September 2014), 18-23. DOI=10.5120/17723-8018
Abstract
Pavement distresses (damages) are important information for evaluating the road condition and conducting the necessary road maintenance activities. Conventional human visual pavement distress detection method is time consuming, very expensive, labour-intensive and dangerous due to exposure to traffic. Numbers of methods have been introduced for road damage detection in the context of fine structure extraction. Due to the unceasing traffic increase, the automation of pavement surface distress monitoring is more and more required. Several techniques are developed for this purpose. But all those approaches access the road condition based on cracks on roads. Due to the various climatic factors, Indian roads suffer from some other types of distresses like potholes also. The goal of this paper is to introduce a novel technique to determine the road condition based on the cracks and potholes on road surfaces. Thus a fully integrated system is proposed for the automatic detection and characterization of distresses in road and flexible pavement surfaces and to detect its severity. The main tasks involved are Collection of images, Distress Detection and Classification using Supervised training approach, Assignment of crack's severity levels to analyze the road performance.
References
- H. Cheng and M. Miyojim(July. 1998),"Automatic pavement distress detection system," Inf. Sci. , vol. 108, no. 1–4, pp. 219–240.
- Peggy Subirats (1), Jean Dumoulin(1), Vincent Legeay(1) and Dominique Barba(2)(2006),"Automation of Pavement Crack Detection using the Continous Wavelet Transform " in IEEE International Conference on Image Processing, 2006
- S. Chambon, P. Subirats, and J. Dumoulin,(2009),"Introduction of a wavelet transform based on 2D matched filter in a Markov randomfield for fine structure extraction: Application on road crack detection,"in Proc. IST/SPIE Electron. Imag. Sci. Technol. , San Jose, CA. 72510A-1–72510A-12.
- Henrique Oliveira, Paulo Lobato Correia(2009) "Automatic road crack segmentation using entropy and image dynamic thresholding " in 17th European Signal Processing Conference.
- H. Oliveira and P. L. Correia, "Identifying and retrieving Distress images from road pavement surveys", Proc. 1st ICIP Workshop on Multimedia Information Retrieval: new trends and challenges, ICIP 2008, Las Vegas, USA, 2008.
- Tien Sy NGUYEN(1)(2), Manuel AVILA(1), BEGOT Stephane(1),"Automatic Detection and Classification of Defect on Road Pavement using Anisotropy Measure", in 17th European Signal Processing Conference (EUSIPCO 2009).
- C. Ma, W. Wang, C. Zhao, F. Di, and Z. Zhu, "Pavement cracks detection based on FDWT," in Proc. IEEE Int. Conf. CiSE, Wuhan, China, 2009, pp. 1–4.
- A. Ayenu-Prah and N. Attoh-Okine, "Evaluating pavement cracks with bidimensional empirical mode decomposition," EURASIP J. Adv. Signal Process. , vol. 2008, no. 1, pp. 861701-1–861701-7, 2008.
- P. Ekdahl, Routine Measurements of Pavement Surface Cracks, Ramböll RST, Malmo, Sweden. http://carbon. videolectures. net/2008/contrib/surf08_portoroz/ekdahl_rmopsc/surf08_ekdahl_rmopsc_ 01. pdf
- C. Ma, C. Zaho, and Y. Hou, "Pavement distress detection based on nonsubsampled contourlet transform," in Proc. IEEE Int. CSSE, Wuhan, China, 2008, pp. 28–31.
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