Comparative Study of the EM Color Image Segmentation in Multiple Color Spaces

摘要：

The task of image segmentation in imaging science is to solve the problem of partitioning an image into smaller disjoint homogeneous regions that share similar attributes. The novel technique of the expectation-maximization (EM) algorithm with adaptively selecting dominant components in color spaces is studied as a means of improving the EMbased segmentation of color images. And simultaneously, the final segmentation is completed by a simple labeling scheme. Then the comparative study of the refined EM algorithm is done in multiple color spaces. The experimental results illustrate that the improved EM algorithm has good segmentation results with fine adaptability in RGB, CIE XYZ, and YIQ (NTSC) color spaces where the results of test image changes little. Nevertheless, these color spaces, i.e. YCbCr, HSV, CIE L*a*b*, and hlh2h3, produce poor segmentation on the reliability and accuracy of a set of test images by performance analysis with evaluation indicators.

关键词： expectation-maximization algorithm Image segmentation color space color perception

作者: Yongqin Zhang Fenglan Sun Yongjun Xiao

作者单位: School of Information Engineering,North China University of Water Resources and Electric Power,Zheng Department of Control Science and Engineering,Huazhong University of Science and Technology,Wuhan,43 School of Physics and Electronic Information Engineering,Xiaogan University,Xiaogan 432000,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 188-191

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）