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论文类型：期刊论文

发表时间：2013-10-01

发表刊物：JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION

收录刊物：SCIE

卷号：24

期号：7

页面范围：1009-1019

ISSN号：1047-3203

关键字：Shape matching; Uniform fuzzy partition; Fuzzy histogram; Classical-histogram-based descriptor; Fuzzy-histogram-based descriptor; Fuzzy shape context; Inner-distance fuzzy shape context; Locally constrained matching

摘要：Shape representation and shape matching are significant topics in computer and human vision. In this paper, fuzzy histogram model with a uniform fuzzy partition is introduced instead of the classical histogram model, and two fuzzy-histogram-based descriptors are proposed: fuzzy shape context (FSC) and inner-distance fuzzy shape context (IDFSC). Compared with classical-histogram-based descriptors, FSC and IDFSC provide more accurate descriptions of samples distributions in log-polar space. Based on fuzzy-histogram-based descriptors, a novel shape matching framework named locally constrained matching (LCM) is proposed for computing the dissimilarity between shapes, and the rotation invariant problem of descriptors can be properly settled. Experimental results on a variety of shape databases show that shape retrieval and recognition results can be effectively achieved by using the proposed method. (C) 2013 Elsevier Inc. All rights reserved.