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Massively Parallel Computing Techniques Might Improve Highway Maintenance
January-March 1998 (vol. 6 no. 1)
pp. 58-67
Manual methods of measuring defects in roads show poor repeatability and reproducibility. Cracking is a principle indicator of defect progression in road pavements, and the authors' overall objective is to develop a practical automatic, repeatable, and reproducible method of determining the extent of cracking. Their research aims at using a distributed array of processors to achieve practical speeds for processing digitized images of road surfaces to detect cracks. The algorithms described here provide for two processes. The first converts a gray-scale image into a binary image that represents most of the cracks and eliminates most of the noise from the surface texture. This initial screening process might suffice for the bulk of a road having few cracks. The second process combines the crack fragments in the binary image into continuous cracks and gives the highway engineer an appropriate output. The article includes results in which individual images were judged to contain cracks or not contain cracks by eight independent observers and by processing on the DAP to the end of the initial screening process. The authors have found that single images can be processed to the initial screening stage in the 40-millisecond limit for real-time processing provided by the British TV standard.
Yong Gen Huang, Howard Tillotson, Martin Snaith, "Massively Parallel Computing Techniques Might Improve Highway Maintenance," IEEE Concurrency, vol. 6, no. 1, pp. 58-67, Jan.-March 1998, doi:10.1109/4434.656780
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