Fusion of rough set theoretic approximations and FCM for color image segmentation

Author

Mohabey, Akash ; Ray, A.K.

Author_Institution

Dept. of Electron. & Electr. Commun. Eng., Indian Inst. of Technol., Kharagpur, India

Volume

2

fYear

2000

fDate

2000

Firstpage

1529

Abstract

A new technique applying the fusion of rough set theoretic approximations and fuzzy C-means algorithm for color image segmentation is presented. The aim of the technique is to segment natural images with regions having gradual variations in color value. The technique extracts color information regarding the number of segments and the segments center values from the image itself through rough set theoretic approximations and presents it as input to FCM block for the soft evaluation of the segments. The performance of the algorithm has been evaluated on various natural and simulated images

Keywords

feature extraction; fuzzy logic; fuzzy set theory; image colour analysis; image segmentation; rough set theory; FCM block; color image segmentation; color information extraction; color value; fuzzy C-means algorithm; gradual variations; natural images; rough set theoretic approximations; simulated images; soft evaluation; Clustering algorithms; Data mining; Data visualization; Fuzzy sets; Humans; Image color analysis; Image processing; Image segmentation; Partitioning algorithms; Set theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 2000 IEEE International Conference on

Conference_Location

Nashville, TN

ISSN

1062-922X

Print_ISBN

0-7803-6583-6

Type

conf

DOI

10.1109/ICSMC.2000.886073

Filename

886073