scope of the project for plant disease detection.

On-device Image Processing Approachesġ.10.3 Fig 6 Proposed Convolutional Networkġ.20 4.3 IMAGE PREPROCESSING AND ENHANCEMENTġ.20.1 Fig 10 Image Processing Original Imageġ.23. Disease detection involves the steps like image acquisition, image pre-processing, image segmentation, feature extraction and classification Using CNN (Convolutional Neural Net) of Machine Learning to Detect and Diagnose also It Provide Graphical User Interface which is not web based System which class Disease type and Recommendation System for Each Diseaseġ.7.1 Deep learning for Image-Based Plant detectionġ.7.2 Detection and Classification of leaf disease using Artificial Neural Networkġ.7.3 Plant disease detection using CNN and GANġ.7.4 Convolutional Neural Network based Inception v3 Model for Plant Classificationġ.8 Plant Disease Detection using CNN Model and Image Processingġ.8.1 F. Hence, Leaf image processing is used for the detection of plant diseases. It requires tremendous amount of work, expertize in the plant diseases, and also require the excessive processing time. It is very difficult to monitor the plant diseases manually. Health monitoring and disease detection on plant is very critical for sustainable agriculture. The studies of the plant diseases mean the studies of visually observable patterns seen on the plant. In this we are using image processing techniques to classify diseases & quickly diagnosis can be carried out as per disease. In this paper, we are providing software solution to automatically detect and classify plant leaf diseases. Perception of human eye is not so much stronger so as to observe minute variation in the infected part of leaf.

Diseases in crops mostly on the leaves effects on the reduction of both quality and quantity of agricultural products. Almost 70% people depend on it & shares major part of the GDP. Plant Scope uses algorithms to integrate and analyze the captured images and data to provide a detailed report on the health accurately and faster to detect. Identification of the plant diseases is the key to preventing the losses in the yield and quantity of the agricultural product.

Scope of the project for plant disease detection.