Identification of Groundnut Bud Necrosis Virus on Tomato Fruits using Machine Learning based Segmentation Algorithm

Abstract

Disease classification in plants is significant to prevent the failures in the amount as well as the production
of agricultural manufactured goods. The difficulties in the farming sector are pointed out by using different
Machine Learning and Image Processing Methods. This paper mostly focuses on tomato plant Groundnut
Bud Necrosis Virus disease diagnosis using an image as inputs. Different input images give-ups varied
superiority of a result and so choosing a classification technique is a significant task. In general, the raw
fruit images need pre-processing to distinguish the segmentation functions. These pre-processing functions
consist of de-noising and intensity normalization. The preprocessed image is given as input to disease
classification using different segmentation algorithms. In this work Support Vector Machine based
segmentation algorithm is proposed. Further, the severity is calculated for further processing