ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

PLANT LEAF DISEASE DETECTION FOR TOMATO

Abstract

Abstract: Pest detection systems have lately become more sophisticated in order to boost yieldproductivity and quality. Disease identification is critical for increasing crop yield, however somediseases are difficult to detect early on by farmers, and the crop suffers as a result. As a result, pestdetection is critical in order to prevent plant deterioration and increase product quality. Using imageprocessing algorithms such as the K-means algorithm, a pest identification system will be developed. Itwill classify the leaf image based on criteria such as colour, texture, and their combinations to trainthree support vector machine classifier models. The dataset will be a trained dataset made up ofthousands of photos gathered from various villages and farms. The algorithm will use a trained datasetto determine which leaves are healthy and which are unhealthy. It will provide various photographs ofthe diseased leaf as well as the healthy leaf. The system will be simpler to use because it only requiresan image of a plant as input and returns results such as healthy and unhealthy plants. As a result,farmers may readily use the system to increase crop quality.Keywords: plant disease, image processing, android, etc

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