An adaptive criterion for cluster number estimation and the optimal algorithm for image segmentation.
- Author:
Gang YAN
1
;
Wu-fan CHEN
Author Information
1. Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou 510515, China. yangang@fimmu.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Cluster Analysis;
Image Enhancement;
methods;
Image Interpretation, Computer-Assisted;
methods;
Markov Chains;
Models, Statistical;
Pattern Recognition, Automated;
methods
- From:
Journal of Southern Medical University
2006;26(7):959-962
- CountryChina
- Language:Chinese
-
Abstract:
In the algorithms for image segmentation, the number of clusters (NOC), which impacts on the segmentation results, should be first solved, and its correct estimation both theoretically and in application is of much importance. The authors propose an adaptive total energy criterion (ATEC) based on Markov random fields (MRF). The correct NOC of different images can be obtained by minimizing the ATEC and the parameters in the criterion are estimated by expectation maximization algorithm and maximum pseudo-likelihood method. The experiments show that the NOC can be automatically detected by adjusting the parameters, and the segmentation with the estimated NOC can be obtained by the maximum a posteriori at the same time.
