A Review of Grape Plant Disease Detection

Abstract

Productivity of plant decreases due to infections caused by variety of diseases. The diseases not only restrict the growth of plant but also reduce quality and quantity of plant. Different technique is adopted for detecting and diagnosis the diseases but the better way is by using Image Processing. Initially the infected region is found then different features are extracted such as color, texture and shape. Finally classification technique is used for detecting the diseases. Different feature extraction technique is there for extracting the color, texture and edge features such as color space, color histogram, grey level cooccurrence matrix (CCM), Gabor filter, Canny and Sobel edge detector. There are also different classification techniques such as Support Vector Machine (SVM), Artificial Neural Network (ANN) Back propagation (BP) Network, Probabilistic Neural Network (PNN), Radial Basis Function (RBF) Neural Network. This paper reviews various image processing and classification techniques to detect and further eliminate plant diseases which has tremendous significance on the productivity of agriculture.