Fruit Disease Classification and Identification using Image Processing

Abstract

Fruit Industry is the largest industry of India. Due to lack of maintenance, inappropriate manual inspection the fruit Disease causes huge losses in yield, quality and quantity. Manual inspection is tedious and time consuming process. An image processing approach is proposed for apple fruit disease identification and categorization using different color, texture and shape feature combination. The basic steps of the proposed approach are image segmentation, extraction of features (color, texture and shape), feature combination and finally apple disease identified and classified using multi-class support vector machine into diseased or normal class. Our proposed technique experimentally verified and validated. The accuracy of the proposed approach is achieved up to 96%.