A Fast Template Matching Algorithm with Adaptive Skipping Using Inner-Subtemplates' Distances
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
A Method for Crack Detection on a Concrete Structure
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Image Processing Based on Percolation Model
IEICE - Transactions on Information and Systems
IEEE Transactions on Computers
A Class of Algorithms for Fast Digital Image Registration
IEEE Transactions on Computers
Detection of Cracks and Corrosion for Automated Vessels Visual Inspection
Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Achievements and challenges in recognizing and reconstructing civil infrastructure
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
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The detection of cracks on concrete surfaces is the most important step during the inspection of concrete structures. Conventional crack detection methods are performed by experienced human inspectors who sketch crack patterns manually; however, such detection methods are expensive and subjective. Therefore, automated crack detection techniques that utilize image processing have been proposed. Although most the image-based approaches focus on the accuracy of crack detection, the computation time is also important for practical applications because the size of digital images has increased up to 10 megapixels. We introduce an efficient and high-speed crack detection method that employs percolation-based image processing. We propose termination- and skip-added procedures to reduce the computation time. The percolation process is terminated by calculating the circularity during the processing. Moreover, percolation processing can be skipped in subsequent pixels according to the circularity of neighboring pixels. The experimental result shows that the proposed approach efficiently reduces the computation cost.