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

Authors:
Khang Siang Tan;Wei Hong Lim;Nor Ashidi Mat Isa
Affiliations:
Imaging and Intelligent Systems Research Team (ISRT), School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia;Imaging and Intelligent Systems Research Team (ISRT), School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia;Imaging and Intelligent Systems Research Team (ISRT), School of Electrical and Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, 14300 Nibong Tebal, Penang, Malaysia
Venue:
Applied Soft Computing
Year:
2013

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Abstract

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.