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Granular computing, rough entropy and object extraction
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DOI：10.1016/j.patrec.2005.05.007.png)
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Abstract
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The problem of image object extraction in the framework of rough sets and granular computing is addressed. A measure called rough entropy of image is defined based on the concept of image granules. Its maximization results in minimization of roughness in both object and background regions; thereby determining the threshold of partitioning. Methods of selecting the appropriate granule size and efficient computation of rough entropy are described. (c) 2005 Elsevier B.V. All rights reserved.
Keywords:
rough sets
entropy
image segmentation
set approximation
granules
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