Automatic Data Clustering Using Parameter Adaptive Harmony Search Algorithm and Its Application to Image Segmentation

作     者：Kumar, Vijay Chhabra, Jitender Kumar Kumar, Dinesh 

作者机构：Thapar Univ Patiala Punjab India Natl Inst Technol Kurukshetra Haryana India Guru Jambheshwer Univ Sci & Technol Hisar Haryana India 

出 版 物：《JOURNAL OF INTELLIGENT SYSTEMS》 (J Intell Syst)

年 卷 期：2016年第25卷第4期

页      面：595-610页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Harmony search algorithm clustering variance meta-heuristics 

摘      要：In this paper, the problem of automatic data clustering is treated as the searching of optimal number of clusters so that the obtained partitions should be optimized. The automatic data clustering technique utilizes a recently developed parameter adaptive harmony search (PAHS) as an underlying optimization strategy. It uses real-coded variable length harmony vector, which is able to detect the number of clusters automatically. The newly developed concepts regarding threshold setting and cutoff are used to refine the optimization strategy. The assignment of data points to different cluster centers is done based on the newly developed weighted Euclidean distance instead of Euclidean distance. The developed approach is able to detect any type of cluster irrespective of their geometric shape. It is compared with four well-established clustering techniques. It is further applied for automatic segmentation of grayscale and color images, and its performance is compared with other existing techniques. For real-life datasets, statistical analysis is done. The technique shows its effectiveness and the usefulness.