Detection of Plant Leaf Disease using Color Co-Occurrence and Segmentation Methods in CNN
Every year the plant diseases are becoming a challenge to plant growth and crop production various places of the world. Plant diseases can affect plants by interfering with several developments such as the absorbance and translocation of water and nutrients, photosynthesis, flower and fruit product improvement, plant growth and development and cell division and enlargement. Crop diseases or abnormalities are a prominent risk to nutrition safety, however their individual impervious stays troublesome in numerous parts of the world because of non-existence of the important foundation. Emergence of accurate techniques in the field of leaf-based image classification has shown impressive results. Our proposed model includes various phases of implementation namely dataset creation, feature extraction, training the classifier and classification. It's not moderate for them to go to agribusiness office and discover what the infection may be. Our principle objective is to distinguish the illness introduce in a plant by watching its morphology by picture handling and machine learning using convolutional approaches.