基于区域限制的EM和图割的非监督彩色图像分割方法

doi:10.3969/j.issn.0372-2112.2016.06.013

电子学报 ›› 2016, Vol. 44 ›› Issue (6): 1349-1354.DOI: 10.3969/j.issn.0372-2112.2016.06.013

基于区域限制的EM和图割的非监督彩色图像分割方法

李磊, 董卓莉, 张德贤, 费选

河南工业大学信息科学与工程学院, 河南郑州 450001

收稿日期:2014-10-22 修回日期:2015-04-08 出版日期:2016-06-25
- 作者简介:
- 李磊男,1979年出生,河南杞县人,博士,讲师,主要研究方向:图像处理、计算机视觉与机器学习.E-mail:llhaut@163.com;董卓莉 女,1980年出生,河南洛宁人,讲师,主要研究方向:图像处理、计算机视觉与机器学习.E-mail:dong_lily2002@haut.edu.cn
- 基金资助:
- 河南省教育厅自然科学项目 (No.13A520177,No.15A520057); 河南省科技厅自然科学项目 (No.132102210494); 高层次人才基金 (No.21476062,No.31401918)

An Unsupervised Color Image Segmentation Method Based on Region-constrained EM and Graph cuts

LI Lei, DONG Zhuo-li, ZHANG De-xian, FEI Xuan

College of Information Science and Engineering, Henan University of Technology, Zhengzhou, Henan 450001, China

Received:2014-10-22 Revised:2015-04-08 Online:2016-06-25 Published:2016-06-25
- Supported by:
- Natural Science Project of Education Department of Henan Province (No.13A520177, No.15A520057); Natural Science Program of Science and Technology Department of Henan Province (No.132102210494); High-level Talents Fund (No.21476062, No.31401918)

摘要/Abstract

摘要：

提出一种基于区域限制的EM(Expectation Maximization)和图割的非监督彩色图像分割方法,以解决自动确定分割类数问题.首先,生成图像的超像素,提取图像的CIE Lab颜色特征和多尺度四元数Gabor滤波特征;为了高效自动地确定分割类数,同时避免因直接使用超像素造成的奇异值问题,对每一个超像素采样并使用采样像素表示超像素;然后采用高斯混合模型对采样像素集合进行建模,使用加入区域限制的分量EM自动获取模型组件数及参数,最后使用图割结合高斯混合模型对图像进行优化,获取最终分割结果.实验结果表明,该方法在分割效率和分割质量上均得到较大提升.

关键词: 彩色图像分割, 区域限制, 超像素, 分量EM, 图割

Abstract:

A new unsupervised color segmentation method based on region-constrained EM (Expectation Maximization) and graph cuts is proposed, which can automatically determine the number of segments for a color image.The proposed method first obtains the superpixels of the image and extracts CIE Lab color feature and multi-scale quaternion Gabor filter feature.In order to automatically and efficiently determine the number of segments for the image and avoid the problem caused by using superpixels directly, a window is used to sample each superpixel to obtain a pixel subset which represents the superpixel.Then the feature space of the sampled pixel subsets is modeled with Gaussian mixture model, and the model parameters (including the number of components) are obtained by a region-constraint component-wise EM algorithm.Finally, the segmentation result can be obtained by α-expansion with the learned model parameters.Experimental results demonstrate the good performance of the proposed method.

Key words: color image segmentation, region constraint, superpixel, component-wise EM, graph cuts

中图分类号:

TP391.41

李磊, 董卓莉, 张德贤, 等. 基于区域限制的EM和图割的非监督彩色图像分割方法[J]. 电子学报, 2016, 44(6): 1349-1354.

LI Lei, DONG Zhuo-li, ZHANG De-xian, et al. An Unsupervised Color Image Segmentation Method Based on Region-constrained EM and Graph cuts[J]. Acta Electronica Sinica, 2016, 44(6): 1349-1354.

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基于区域限制的EM和图割的非监督彩色图像分割方法

An Unsupervised Color Image Segmentation Method Based on Region-constrained EM and Graph cuts

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