A Method for Regional Segmentation and Semantic Categorization Based on Rough Set Theory
XIE Zhao, GAO Jun
Department of Computer and Information, Hefei University of Technology, Hefei 230009 Center for Biomimetic Sensing and Control Research, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031
Abstract A rough set theory based method for image understanding is proposed. The images are regarded as the information system and each pixel in them as an object in the system. The reduction process and extend models with lowerupper approximations and core attribute concepts in rough sets are considered. Then a segmentation algorithm and a rule reduction and inference method are proposed. The experimental results demonstrate the feasibility and the accuracy of proposed method by comparing it with Ncuts segmentation algorithms and statistical learning ways.
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2007, Vol. 20 
