Journal of Systems Engineering and Electronics ›› 2014, Vol. 25 ›› Issue (2): 298-306.doi: 10.1109/JSEE.2014.00034

• SOFTWARE ALGORITHM AND SIMULATION • Previous Articles     Next Articles

Image segmentation algorithm based on high-dimension fuzzy character and restrained clustering network

Baoping Wang, Yang Fang*, and Chao Sun   

  1. Science and Technology on UAV Laboratory, Northwestern Polytechnical University, Xi’an 710065, China
  • Online:2014-04-22 Published:2010-01-03


An image segmentation algorithm of the restrained fuzzy Kohonen clustering network (RFKCN) based on highdimension fuzzy character is proposed. The algorithm includes two steps. The first step is the fuzzification of pixels in which two redundant images are built by fuzzy mean value and fuzzy median value. The second step is to construct a three-dimensional (3-D) feature vector of redundant images and their original images and cluster the feature vector through RFKCN, to realize image segmentation. The proposed algorithm fully takes into account not only gray distribution information of pixels, but also relevant information and fuzzy information among neighboring pixels in constructing 3-D character space. Based on the combination of competitiveness, redundancy and complementary of the information, the proposed algorithm improves the accuracy of clustering. Theoretical analyses and experimental results demonstrate that the proposed algorithm has a good segmentation performance.