Multi-scale image segmentation algorithm based on support vector machine approximation criteria

Authors:
Liejun Wang;Zhenhong Jia
Affiliations:
College of Information Science and Engineering, Xinjiang University, Urumqi, China;College of Information Science and Engineering, Xinjiang University, Urumqi, China
Venue:
Concurrency and Computation: Practice & Experience
Year:
2012

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Abstract

A new multi-scale image segmentation algorithm based on support vector machine (SVM) approximation criteria has been discussed in this paper. Most current multi-scale image segmentation algorithms are based on the restricted empirical risk minimization, and the approximation of multi-scale image segmentation was poor. As the SVM theory was one based on the structural risk minimization, the best approximation results could be reached. So, it was combined with multi-scale image segmentation algorithms, and one-image multi-resolution analysis approximation algorithms based on the SVM theory were presented in this paper, which could obtain more accurate multi-scale image segmentation. By numerical results, the algorithm was further verified that more accurate image segmentation results were unfolded. Copyright © 2011 John Wiley & Sons, Ltd.