Detection of Plant Leaf Disease Using Image Processing and Deep Learning Technique—A Review

Agriculture employs 50% of liveware of the nation. The agricultural yield gets affected by fruit and plant leaf diseases. It is necessary to take vital steps against the deterioration of yield. Image processing techniques provide essential apparatus to look after these diseases in plants. Mostly designed systems work in four steps. Once a picture is captured of doubtful fruit or leaf, this is called image acquisition. The picture is sent to the system, and it goes under pre-processing, segmentation, feature extraction, and classification. The acquired image is processed to fit in the system by setting its resolution. Clusters are made as it becomes easy for the system to extract color features, boundary features, and histograms, etc. The final step classifies the input data into pre-defined categories of different diseases. This paper is a hub of some acceptable techniques and highlights the success ratio of variant methods used for disease detection.