JELE_V3_N2_RP2 S. Praveena S.P. Singh I.V. Muralikrishna Journal on Electronics Engineering 2249 – 0760 3 2 7 15 Segmentation, Classification ,Feature Extraction, Naive Bayes Classifier, Moving KFCM This paper presents an improvised Moving kernel based fuzzy C-means(MKFCM) for land-cover mapping of trees, shade, building and road. It starts with the single step preprocessing procedure in which first the input image is passed through a median filter to reduce the noise and get a better image fit for segmentation. The pre-processed image is segmented using the Moving KFCM algorithm and classified using Bayesian classifier with kernel Distribution type. KFCM with moving property is used to improve the object segmentation in satellite images. Simulation results show that classification accuracy for different regions using Moving KFCM is better than moving k means using Naive Bayes classifier with four different kernels. December 2012 - February 2013 Copyright © 2013 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=2117