Segmentation and Classification using Heuristic HRSPSO
H. S. Behera
H.S. Behera, Faculty in Dept. of Computer Science and Engineering, Veer Surendra Sai University of Technology (VSSUT), Burla, Orissa, India.
Manuscript received on June 18, 2011. | Revised Manuscript received on June 28, 2011. | Manuscript published on July 05, 2011. | PP: 66-69 | Volume-1 Issue-3, July 2011. | Retrieval Number: C057061311
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, a Heuristic Hybrid Rough Set Particle Swarm optimization (HRSPSO) Algorithm is proposed for partitioning a digital image into different segments that is more meaningful and easier to analyze segmentation and Classification. The heuristic HRSPSO algorithm has been implemented with a novel method in MATLAB platform considering 50 iterations and 20 particles. The experimental study and performance evaluation show that Heuristic HRSPSO optimization Algorithm is observed to be having optimal solution with smallest DB (Davies-Bouldin) index and it converges after fifteenth iterations.
Keywords: Image Processing, Clustering, Image Segmentation, Classification, Davies-Bouldin index, Rough Set, Particle Swarm Optimization, Hybrid Rough Set Theory, Image Pixel Classification, Fuzzy C- Means (FCM).