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
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