The Comparative Research on Image Segmentation Algorithms

As the premise of feature extraction and pattern recognition, image segmentation is one of the fundamental approaches of digital image processing. This paper enumerates and reviews main image segmentation algorithms, then presents basic evaluation methods for them, finally discusses the prospect of image segmentation. Some valuable characteristics of image segmentation come out after a large number of comparative experiments.

[1]  Fu Yang,et al.  Comprehensive method detecting the status of the transformer based on the artificial intelligence , 2004, 2004 International Conference on Power System Technology, 2004. PowerCon 2004..

[2]  Ronen Basri,et al.  Fast multiscale image segmentation , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[3]  A. D. Brink Thresholding of digital images using two-dimensional entropies , 1992, Pattern Recognit..

[4]  Wang Da-zhen,et al.  Threshold Segmentation for Hand Vein Image , 2005 .

[5]  Zhou Xian-cheng Image Segmentation Based on Modified Particle Swarm Optimization and Fuzzy C-Means Clustering , 2009, 2009 Second International Conference on Intelligent Computation Technology and Automation.

[6]  Y. W. Lin,et al.  Digital image processing applications , 1989 .

[7]  Jerry D. Gibson,et al.  Handbook of Image and Video Processing , 2000 .

[8]  Cláudio Rosito Jung Multiscale image segmentation using wavelets and watersheds , 2003, 16th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2003).

[9]  Josef Kittler,et al.  On threshold selection using clustering criteria , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[10]  Lawrence O. Hall,et al.  Fast fuzzy clustering of infrared images , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[11]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.