文章基本信息

标题：Segmentation and Classification using Heuristic HRSPSO
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作者：H.S. Behera
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2011
卷号：1
期号：3
页码：66-69
出版社：International Journal of Soft Computing & Engineering
摘要：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.
关键词：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).