Leaf Health Monitoring and Disease Detection Using Image Processing

Recognizing the confirmation of leaf spot identification through image processing is also one of the most important factors in saving plants from several diseases. Leaf disturbance testing means an examination of the visible models that appear on a plant. Farmers need good crops to survive in the nation and we see how farmers deal with their crops many diseases that can cause and farmers will face many difficulties and it requires some external energy to be used over time. Therefore, the image is used in the area of leaf disease. Acknowledging contamination includes methods such as image acquisition, prior coping, image classification, feature removal and collection. In this paper we present a systematic diagnosis of leaf diseases using imaging techniques. The presented framework is a product response to systematic identification and calculation of higher rates of plant leaf disease. The handle frame consists of four basic improvements, first the shading of the RGB image for details, at which point, the image is split, and the key pieces. are separated, eventually more rates are registered. By further observation, diseases, thought to be present in the leaf of a plant are examined. fares are calculated based on the distance traveled. The fare is deducted from the rechargeable card.