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Proceedings Paper

Study on the application of MRF and fuzzy clustering as well as the D-S theory to image segmentation of the human brain
Author(s): Yihong Guan; Bin Guo; Rui Duan; Anding Mao
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Paper Abstract

A new image segmentation method based on Markov Random Field (MRF) and Two-Dimensional Histogram Method of Fuzzy Clustering as well as Dempster-Shafer (D-S) evidence theory is presented in this paper.The application of Markov Random Field to image restoration and segmentation can effectively remove noise and get more accurate segmentation results; And the application of Fuzzy Clustering Theory together with Two-Dimensional Histogram image segmentation methods can get more satisfactory segmentation results; However, these two ways leads to different classification results while classifying the controversial pixels in images, so we can use the Dempster-Shafer evidence theory to assign the controversial points to the plausibility interval, and then divide them. This paper will adopt the above three theories to propose a human brain image segmentation research method. Experimental result shows that the method solves the problem of the class attribution of the controversial points, and the segmentation result is more in line with human vision.

Paper Details

Date Published: 20 August 2010
PDF: 6 pages
Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78201J (20 August 2010); doi: 10.1117/12.866668
Show Author Affiliations
Yihong Guan, Kunming Univ. of Science and Technology (China)
Bin Guo, Kunming Univ. of Science and Technology (China)
Rui Duan, Kunming Univ. of Science and Technology (China)
Anding Mao, Kunming Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7820:
International Conference on Image Processing and Pattern Recognition in Industrial Engineering
Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du, Editor(s)

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