A novel method for classification using multi class-SVM classifier with multi features

Abstract

A proposed novel technique for classify using multi class SVM classifier with multi-features such as HOG (Histogram of Oriented Gradient), Color moment, Gabor and wavelet. Initially, the color feature is extracted from the segmented image using bounding box algorithm. Texture features are extracted using dominant HOG, Gabor and Wavelet then the feature selection methods are separately classified. Hence in this paper proposed a novel Multi class SVM technique is used in that initially classifies the different class from the database and get the accuracy of the image based upon the feature of the image. The fundamental performance metrics like accuracy, sensitivity and specificity are taken into comparison. The proposed method has higher accuracy when it is compared to the accuracy of other feature based SVM.