Abstract:
Identification of plant diseases is key to avoiding losses in agricultural yields and product quantities. Plant disease study means the study of disease patterns that can be visually seen on plants. The main objective of this research is to develop a prototype system to detect cabbage diseases which are Alternaria Leaf Spot Disease, Mosaic Virus Disease and Downy Fungus Disease. It is very difficult to monitor plant diseases manually because it requires a large amount of work, deep expertise in plant diseases, and also requires excessive processing time. This project focuses on image processing techniques used to improve image quality and K-NN techniques to classify cabbage diseases. Disease detection involves image acquisition, image pre-processing, segmentation and classification of disease. This paper discusses the methods used for the detection of plant diseases using cabbage leaf images as well as some segmentation and feature extraction algorithms used in the detection of cabbage diseases.
