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Fusion of A-IFS Histon and FCM for Color Image Segmentation


Affiliations
1 Dept. of ECE, Pondicherry Engg. College, Pillaichavady, Puducherry-605014, India
2 EEE Dept., Pondicherry Engg. College, Pillaichavady, Puducherry-605014, India
     

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The proposed paper presents a new approach to color image segmentation by fusing Fuzzy C-Means (FCM) and Atanassov's Intuitionistic Fuzzy Set (A-IFS) Histon. The method proposed here does not require prior knowledge about the no. of clusters. The proposed method also calculates the threshold value automatically for segmentation. This method calculates membership values using conventional FCM and uses A-IFS Histon for calculating the no. of clusters and employs roughness index for segmentation. In the homogeneous region, the roughness index is more and is close to unity value, whereas, in the boundary region, it is small. The qualitative and quantitative comparison of the proposed method yields better results against the recently developed A-IFS Histon technique.

Keywords

Atanassov's Intuitionistic Fuzzy Set, Clustering, Color Image Segmentation, FCM, Membership Values.
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  • Fusion of A-IFS Histon and FCM for Color Image Segmentation

Abstract Views: 218  |  PDF Views: 2

Authors

S. Batmavady
Dept. of ECE, Pondicherry Engg. College, Pillaichavady, Puducherry-605014, India
R. Senthil
Dept. of ECE, Pondicherry Engg. College, Pillaichavady, Puducherry-605014, India
K. Manivannan
EEE Dept., Pondicherry Engg. College, Pillaichavady, Puducherry-605014, India

Abstract


The proposed paper presents a new approach to color image segmentation by fusing Fuzzy C-Means (FCM) and Atanassov's Intuitionistic Fuzzy Set (A-IFS) Histon. The method proposed here does not require prior knowledge about the no. of clusters. The proposed method also calculates the threshold value automatically for segmentation. This method calculates membership values using conventional FCM and uses A-IFS Histon for calculating the no. of clusters and employs roughness index for segmentation. In the homogeneous region, the roughness index is more and is close to unity value, whereas, in the boundary region, it is small. The qualitative and quantitative comparison of the proposed method yields better results against the recently developed A-IFS Histon technique.

Keywords


Atanassov's Intuitionistic Fuzzy Set, Clustering, Color Image Segmentation, FCM, Membership Values.