Fuzzy genetic clustering for pixel classification of satellite images

Author

Pakhira, Malay K. ; Bandyopadhyay, Sanghamitra ; Maulik, Ujjwal

Author_Institution

Kalyani Govt. Engg. Coll., India

Volume

2

fYear

2003

fDate

15-17 Oct. 2003

Firstpage

872

Abstract

We evaluate the performance of two fuzzy cluster validity indices, including a recently developed index, PBMF. The effectiveness of variable string length genetic algorithm (VGA) is used in conjunction with the fuzzy indices to determine the number of clusters present in a data set as well as the proper fuzzy cluster configuration. The utility of the fuzzy partitioning is tested on a number of artificial and real life data sets. The results of the fuzzy VGA algorithm are compared with those obtained by the well known FCM (fuzzy C-means) algorithm which is applicable only when the number of clusters is known a priori. The performance of the two fuzzy cluster validity indices is also tested for the pixel classification of a remotely sensed image of the race-course ground of Kolkata.

Keywords

fuzzy systems; genetic algorithms; image classification; pattern clustering; remote sensing; Kolkata race-course ground; fuzzy C-means algorithm; fuzzy cluster validity indices; fuzzy genetic clustering; pixel classification; remotely sensed image; satellite images; Clustering algorithms; Educational institutions; Fuzzy sets; Genetic algorithms; Life testing; Multidimensional systems; Partitioning algorithms; Pattern classification; Pixel; Satellites;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 2003. Conference on Convergent Technologies for the Asia-Pacific Region

Print_ISBN

0-7803-8162-9

Type

conf

DOI

10.1109/TENCON.2003.1273304

Filename

1273304