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Proceedings Paper

A binary image enhancement and recognition approach in crack detection using exploring agents
Author(s): Wei Wei; Mingli Ding; Qi Wang
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Paper Abstract

This paper proposes a method using exploring agent for the noise elimination and crack recognition in binary images which originate from the objective gray level images. A mean filtering method is introduced to correct non-uniform background illumination and obtain the dynamic thresholds, which are used to convert the original 255 scales gray level image into binary images. The pavement crack figures in the binary image have been contaminated by randomly distributed noisy dots, and in most cases, the crack shape and orientation can't be represented by specific functions. The exploring agent method using sense-compute-act loop, presented in this paper, can be employed to determine the crack and eliminate the random noise. The exploring agent and the Least Square Fit (LSF) method separately have unique characteristics in recognizing the crack intersection and orientation, and automatically running along the crack. The traces of the exploring agent are the skeleton of the pavement crack, and the number of steps can be used to calculate the length of the crack. The sense, compute, and act ability of the exploring agent iterate to guarantee the effect in processing randomly distributed features of image during the actual processing.

Paper Details

Date Published: 8 February 2005
PDF: 10 pages
Proc. SPIE 5637, Electronic Imaging and Multimedia Technology IV, (8 February 2005); doi: 10.1117/12.570604
Show Author Affiliations
Wei Wei, Harbin Institute of Technology (China)
Mingli Ding, Harbin Institute of Technology (China)
Qi Wang, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 5637:
Electronic Imaging and Multimedia Technology IV
Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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