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An Evolutionary Dynamic Clustering based Colour Image Segmentation
Amiya Halder, Nilvra Pathak
Pages - 549 - 556     |    Revised - 31-01-2011     |    Published - 08-02-2011
Volume - 4   Issue - 6    |    Publication Date - January / February  Table of Contents
Segmentation, Clustering, Genetic Algorithm, Clustering Metric, Validity Index
We have presented a novel Dynamic Colour Image Segmentation (DCIS) System for colour image. In this paper, we have proposed an efficient colour image segmentation algorithm based on evolutionary approach i.e. dynamic GA based clustering (GADCIS). The proposed technique automatically determines the optimum number of clusters for colour images. The optimal number of clusters is obtained by using cluster validity criterion with the help of Gaussian distribution. The advantage of this method is that no a priori knowledge is required to segment the color image. The proposed algorithm is evaluated on well known natural images and its performance is compared to other clustering techniques. Experimental results show the performance of the proposed algorithm producing comparable segmentation results.
CITED BY (16)  
1 Singh, V., Gupta, S., & Saini, S. (2015, March). A methodological survey of image segmentation using soft computing techniques. In Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in (pp. 419-422). IEEE.
2 Halder, A., & Hassan, S. S. (2015, February). Self-organizing feature map and linear discriminant analysis based image segmentation. In Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE), 2015 International Conference on (pp. 394-399). IEEE.
3 Singh, V., & Misra, A. K. (2015, March). Cardiac image segmentation using Simulated Genetic algorithm. In Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in (pp. 1024-1027). IEEE.
4 Ding, Y., Feng, Q., Wang, T., & Fu, X. (2014). A modular neural network architecture with concept. Neurocomputing, 125, 3-6.
5 Amelio, A., & Pizzuti, C. (2014). An evolutionary approach for image segmentation. Evolutionary computation, 22(4), 525-557.
6 Halder, A., Dalmiya, S., & Sadhu, T. (2014). Color Image Segmentation Using Semi-supervised Self-organization Feature Map. In Advances in Signal Processing and Intelligent Recognition Systems (pp. 591-598). Springer International Publishing.
7 Dengxiao Zheng, & Jiao Licheng. (2014). Autoimmune cloning clustering image segmentation algorithm Manifold distance of University of Electronic Science and Technology, 43 (5), 742-747.
8 Febrihani, l. (2014). Segmentasi citra menggunakan level set untuk active contour berbasis parallel gpu cuda(doctoral dissertation, uajy).
9 Agarwal, M., & Singh, V. (2013). A Methodological Survey and Proposed Algorithm on Image Segmentation using Genetic Algorithm. International Journal of Computer Applications, 67(16).
10 Jaiswal, A., Kurda, L., & Singh, V. (2013). Reboost Image Segmentation using Genetic Algorithm. International Journal of Computer Applications, 69(19).
11 Singh, V., & Garg, P. Adaptive Image Segmentation Using a Genetic Algorithm.
12 Halder, A., & Dasgupta, A. (2012, September). Image segmentation using rough set based k-means algorithm. In Proceedings of the CUBE International Information Technology Conference (pp. 53-58). ACM.
13 Halder, A., & Dasgupta, A. (2012). Color image segmentation using rough set based K-means algorithm. International Journal of Computer Applications, 57(12).
14 Halder, A., & Pramanik, S. (2012). An unsupervised dynamic image segmentation using fuzzy hopfield neural network based genetic algorithm. arXiv preprint arXiv:1205.6572.
15 Amelio, A., & Pizzuti, C. (2012). An evolutionary and graph-based method for image segmentation. In Parallel Problem Solving from Nature-PPSN XII (pp. 143-152). Springer Berlin Heidelberg.
16 Halder, A., Pramanik, S., & Kar, A. (2011). Dynamic image segmentation using fuzzy C-means based genetic algorithm. International Journal of Computer Applications, 28(6), 15-20.
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Associate Professor Amiya Halder
- India
Mr. Nilvra Pathak
- India