Fruit Classification using Statistical Features in SVM Classifier

Abstract

Automation of fruit classification is an interesting application of computer vision. The computer vision strategies used to classify a fruit based on intensity., color., shape and texture feature. This paper proposes a traditional technique which uses color and texture feature for fruit classification. Traditional fruit classification method depends on manual operation based on visual ability. The classification is done by Support Vector Machine (SVM) classifier based on statistical and co-occurence features derived from the wavelet transform. The classification accuracy for the proposed system is 95.3%.