Classification of Leaf Disease Using Global and Local Features

Leaf disease of plants causes great loss in productivity crops. So proper take care is mandatory. Plants can be affected by various diseases. Early diagnosis leaf a good practice. Computer vision-based classification way diagnosing diseases early. detection lead to better treatment. Vision based technology identify quickly. Though deep learning trending and using vastly for recognition task, but it needs very large dataset also consumes much time. This paper introduced method classify Gist LBP (Local Binary Pattern) feature. These manual feature extraction process need less Combination gist features shows significant result used as global local describe an image well scene. robust illumination changes occlusions computationally simple. Various different are considered this study. from images extracted separately. Images pre-processed before extraction. Then both matrix combined concatenation method. Training testing done on Different machine model applied the vector. Result algorithms compared. SVM performs classifying plant's dataset.