DocumentCode :
2748111
Title :
Automated pavement distress detection using advanced image processing techniques
Author :
Sun, Y. ; Salari, E. ; Chou, E.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Toledo, Toledo, OH, USA
fYear :
2009
fDate :
7-9 June 2009
Firstpage :
373
Lastpage :
377
Abstract :
In this paper, a novel, fast and self-adaptive image processing method is proposed for the extraction and connection of break points of cracks in pavement images. The algorithm first finds the initial point of a crack and then determines the crack´s classification into transverse, longitudinal and alligator types. Different search algorithms are used for different types of cracks. Then the algorithm traces along the crack pixels to find the break point and then connect the identified crack point to the nearest break point in the particular search area. The nearest point then becomes the new initial point and the algorithm continues the process until reaching the end of the crack. The experimental results show that this connection algorithm is very effective in maximizing the accuracy of crack identification.
Keywords :
feature extraction; image classification; image resolution; object detection; road building; advanced image processing techniques; automated pavement distress detection; break points connection; break points extraction; crack classification; crack identification; crack pixels; Civil engineering; Filtering; Image processing; Image segmentation; Inspection; Remuneration; Robustness; Statistics; Sun; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electro/Information Technology, 2009. eit '09. IEEE International Conference on
Conference_Location :
Windsor, ON
Print_ISBN :
978-1-4244-3354-4
Electronic_ISBN :
978-1-4244-3355-1
Type :
conf
DOI :
10.1109/EIT.2009.5189645
Filename :
5189645
Link To Document :
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