Wang Li
Aviation Automation College, Civil Aviation University of China
Zeng Pei-Pei
Aviation Automation College, Civil Aviation University of China
ABSTRACT
Circuit board infrared image segmentation is an important procedure in the application of circuit board fault detection with infrared thermal imaging technology. A CNO-HMRF-EM algorithm combined with the advantage of HMRF, EM and CNO is designed to deal with the insufficiency of the traditional clustering methods in the circuit board infrared image segmentation. To get the best clustering segmentation results, HMRF-EM algorithm is used as the first step to estimate the tag of each image point so that each point of image can be clustered according to the tag estimation result. Then the HMRF-EM algorithms optimal clustering number is determined in the use of CNO algorithm. The simulation results prove that, comparing with the methods of C-Mean clustering and OTSU clustering, bigger GS value as well as the better results of the clustering segmentation can be acquired in the use of CNO-HMRF-EM algorithm.
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How to cite this article
Wang Li and Zeng Pei-Pei, 2013. Infrared Image Segmentation using Hidden Markov Random Fields and Expectation-maximization Algorithm. Information Technology Journal, 12: 8494-8499.
DOI: 10.3923/itj.2013.8494.8499
URL: https://scialert.net/abstract/?doi=itj.2013.8494.8499
DOI: 10.3923/itj.2013.8494.8499
URL: https://scialert.net/abstract/?doi=itj.2013.8494.8499
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