DOIONLINE

DOIONLINE NO - IJEEDC-IRAJ-DOIONLINE-250

Publish In
International Journal of Electrical, Electronics and Data Communication (IJEEDC)-IJEEDC
Journal Home
Volume Issue
Issue
Volume-1,Issue-10  ( Dec, 2013 )
Paper Title
A Comparative Study Of Supervised Image Classification Algorithms For Satellite Images
Author Name
Kanika Kalra, Anil Kumar Goswami, Rhythm Gupta
Affilition
Banasthali University
Pages
10-16
Abstract
Image classification is a complex information extraction technique. The objective of image classification is to identify the features occurring in an image and group similar features as clusters. The aim of this study is to compare some supervised image classification techniques .The techniques considered in this paper are Minimum Distance, k-Nearest Neighbour (KNN), Nearest Clustering Fuzzy C-Means (FCM) and Maximum Likelihood (ML) Classification algorithms. All the techniques are compared and analysed for best results and maximum accuracy
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