Plant Disease Detection and Solution using Image Classification

Crop cultivation plays a crucial role within the agricultural field.Presently, the loss of food is particularly because of infected crops, which reflexively reduces the assembly rate.Identifying plant diseases is not explored yet.The foremost challenge is to reduce the usage of pesticides within the agricultural field and to increase the quality and quantity of the assembly rate.Our paper is used to explore the disease prediction at an untimely action.We propose an enhanced algorithm to predict the infected area of the leaves.For segmenting Infected region and placing it to its relevant classes, colour based segmentation model is used.Experimental analyses were done on samples images in terms of sometime complexity and thus the world of infected region.Plant diseases are often detected by image processing technique.Disease detection has steps like image acquisition, pre-processing, segmentation, classification and feature extraction.Our project is used to detect the plant diseases and provide solutions to urge over the disease.It shows the affected a neighbourhood of the leaf in percentage.We planned to style our project with voice navigation system, so a private with lesser expertise in software should even be able to use it easily.