标题:Image Segmentation based on Contextual Label Tree for Retrieval
作者:Yuan, Guoqiang; Liu, Heshan
通讯作者:Yuan, GQ
作者机构:[Yuan, Guoqiang; Liu, Heshan] Shandong Univ, Dept Mech Engn, Jinan 250061, Shandong, Peoples R China.
会议名称:International Conference on Advances in Computer Science and Engineering
会议日期:JUL 20-21, 2010
来源:NANOTECHNOLOGY AND COMPUTER ENGINEERING
出版年:2010
卷:121-122
页码:563-568
DOI:10.4028/www.scientific.net/AMR.121-122.563
关键词:Texture; Image Segmentation; Wavelet Coefficient; Contextual Label Tree
摘要:Image segmentation is an important constituent portion in image processing and retrieval. Based on the traditional Wavelet-domain Hidden Markov Tree (HMT) Multi-scale Segmentation method, this paper presents a Contextual Label Tree (CLT) method according to the dependency information between image blocks belong to different scales, including the relation from the father node, the neighbor nodes and the neighbor nodes of the father. This method calculates the maximal similarity using context vectors that exit on every tree node and realizes image segmentation from coarse-scale to fine-scale. Experiments show that this method is satisfied with its segmentation performance.
收录类别:CPCI-S;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650732222&doi=10.4028%2fwww.scientific.net%2fAMR.121-122.563&partnerID=40&md5=a6a3be9752958eb77adb5fe98c92a456
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