Analysis of Segmented Features For Identification of Tomato Plant Leaf Diseases At Early Stage

Abstract

Since the advancement in the recent technology, the works in agricultural area have introduced harmless techniques to detect diseases in the plant. Techniques to enhance precision agriculture which might be primarily based on the photographs of plants or datasets are used to locate exceptional diseases in the plants. This is accomplished as to lessen the financial losses in agricultural department. The use of right facts is an essential difficulty of every wise system. Several diseases that affect tomato plants and their characteristics are the main part of this study. In this paper, we analyses and presented the result of various sorts of tomato leaf diseases. More focus has been given on the statistical features of the tomato leaves affected by critical diseases like: early blight, mosaic virus, target spot etc. Furthermore, we have shown some samples of our collected datasets which contains different diseases appear on the leaf. Based on these physical characteristics and extracted features of the tomato leaves, an early disease detection system can be designed.