Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 228-232.doi: 10.11896/j.issn.1002-137X.2017.11A.048

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Unsupervised Complex-scene Clothing Image Segmentation Algorithm Based on Color and Texture Features

GUO Xin-peng, HUANG Yuan-yuan and HU Zuo-jin   

  • Online:2018-12-01 Published:2018-12-01

Abstract: In this paper,an unsupervised segmentation algorithm especially used for clothing images in complex background was proposed.Based on priori knowledge,it combines color and texture features together.First,block truncation encoding thought is used to cut the traditional 3-dimentional color space into 6-dimentional space,so that fine color features can be obtained.Then,the texture feature based on the improved local binary pattern (LBP) algorithm was designed and used to describe the image together with the color feature.After that,according to the statistical appearance-law of the target region and background in the image,called priori knowledge,a kind of bisect method was proposed to do segmentation.Since the image is divided into several sub image blocks,such bisect segmentation will be accomplished more efficient.Experiments show that the algorithm can quickly and effectively extract clothing region from the complex scene without any artificial parameters.This segmentation will play an important role for image understanding and retrieval.()

Key words: Image segmentation,Block truncation code,Textural features,Heuristic knowledge

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