Level set segmentation using image second order statistics

Bo Ma*, Yuwei Wu, Pei Li

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

This paper proposes a novel level set based image segmentation method by use of image second statistics and logarithmic Euclidean metric. Different from previous tensor based image segmentation approaches, the proposed method adopts covariance feature as region-level descriptor rather than pixel-level one. On the basis of feature image, we utilize second order statistics of image feature, i.e., covariance matrix, to model image region representation, which is of low dimension, invariant to uniform illumination change, insensitive to noise, and more importantly provide a natural mechanism of incorporating different types of image features by modeling their correlations. We model image segmentation problem as one finding the optimal segmentation that maximizes the covariance distance between foreground region and background region. Typically, covariance matrices do not lie on Euclidean space. Our solution to this is to exploit logarithmic Euclidean distance as a metric to compute the similarity between two matrices. The experimental results show that covariance matrix as region descriptor do form an effective representation for image segmentation problems, and the proposed image energy can be used to segment images and extract object boundaries reliably and accurately.

源语言英语
主期刊名MIPPR 2011
主期刊副标题Automatic Target Recognition and Image Analysis
DOI
出版状态已出版 - 2011
活动MIPPR 2011: Automatic Target Recognition and Image Analysis - Guilin, 中国
期限: 4 11月 20116 11月 2011

出版系列

姓名Proceedings of SPIE - The International Society for Optical Engineering
8003
ISSN(印刷版)0277-786X

会议

会议MIPPR 2011: Automatic Target Recognition and Image Analysis
国家/地区中国
Guilin
时期4/11/116/11/11

指纹

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引用此

Ma, B., Wu, Y., & Li, P. (2011). Level set segmentation using image second order statistics. 在 MIPPR 2011: Automatic Target Recognition and Image Analysis 文章 80030Z (Proceedings of SPIE - The International Society for Optical Engineering; 卷 8003). https://doi.org/10.1117/12.902005