Paper Title :A Comparative Study Of Supervised Image Classification Algorithms For Satellite Images

Author :Kanika Kalra, Anil Kumar Goswami, Rhythm Gupta

Article Citation :Kanika Kalra ,Anil Kumar Goswami ,Rhythm Gupta , (2013 ) " A Comparative Study Of Supervised Image Classification Algorithms For Satellite Images " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 10-16, Volume-1,Issue-10

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

Type : Research paper

Published : Volume-1,Issue-10

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