Novel initialization scheme for Fuzzy C-Means algorithm on color image segmentation

This paper presents a novel initialization scheme to determine the cluster number and obtain the initial cluster centers for Fuzzy C-Means (FCM) algorithm to segment any kind of color images, captured using different consumer electronic products or machine vision systems. The proposed initialization scheme, called Hierarchical Approach (HA), integrates the splitting and merging techniques to obtain the initialization condition for FCM algorithm. Initially, the splitting technique is applied to split the color image into multiple homogeneous regions. Then, the merging technique is employed to obtain the reasonable cluster number for any kind of input images. In addition, the initial cluster centers for FCM algorithm are also obtained. Experimental results demonstrate the proposed HA initialization scheme substantially outperforms other state-of-the-art initialization schemes by obtaining better initialization condition for FCM algorithm. (C) 2013 Elsevier B.V. All rights reserved.