An approach of tomato leaf disease detection based on SVM classifier

Abstract

Disease Identification and management is a challenging task. Diseases of plants are commonly seen on the leaves of the plant. Precise Identification of the disease by visually observing them is difficult because of the complexity of the patterns on the leaf. So the demand for identifying the diseases using computers has raised more in recent years. This work employs a machine learning technique to identify the diseases of a tomato plant and suggest appropriate control measures to handle the disease. The system is designed using python software programmed into raspberry pi modules. After the image is uploaded for the disease identification, images are pre-processed using histogram equalization, filtering, color transformation and segmentation then the images are taken to the classification using SVM classifier and the appropriate disease identified is displayed on the screen along with the corresponding control measures to be taken