ABSTRACT

This paper addresses the problem of war scene classification. Scene classification underlies many problems in visual perception such as object recognition and environment navigation. Scene classification, the classification of images into semantic categories (e.g. opencountry, mountains, highways and streets) is a challenging and important task nowadays. In this paper we are trying to classify the war scene category from the natural scene category. For this purpose two set of image categories were taken i.e., opencountry & war tank. By using Haar and Daubechies(db4) wavelets the features are extracted from the images. The extracted features are trained and tested with the help of feed forward back propagation algorithm using Artificial neural Networks. The complete work is experimented in Matlab 7.6.0 using real world dataset.