TEXTURE BASED LAND COVER CLASSIFICATION ALGORITHM USING GABOR WAVELET AND ANFIS CLASSIFIER

ICTACT Journal on Image and Video Processing ( Volume: 6 , Issue: 4 )

Abstract

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Texture features play a predominant role in land cover classification of remotely sensed images. In this study, for extracting texture features from data intensive remotely sensed image, Gabor wavelet has been used. Gabor wavelet transform filters frequency components of an image through decomposition and produces useful features. For classification of fuzzy land cover patterns in the remotely sensed image, Adaptive Neuro Fuzzy Inference System (ANFIS) has been used. The strength of ANFIS classifier is that it combines the merits of fuzzy logic and neural network. Hence in this article, land cover classification of remotely sensed image has been performed using Gabor wavelet and ANFIS classifier. The classification accuracy of the classified image obtained is found to be 92.8%.

Authors

S. Jenicka1, A. Suruliandi2
Einstein College of Engineering, India1, Manonmaniam Sundaranar University, India2

Keywords

ANFIS, Gabor Filters, Texture Analysis, Land Cover Classification, Big Data

Published By
ICTACT
Published In
ICTACT Journal on Image and Video Processing
( Volume: 6 , Issue: 4 )
Date of Publication
May 2016
Pages
1273-1279

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