Analysis of Infection in Plant Leaf and Implication of Suitable Pesticides based on Image Processing

Abstract

Agriculture plays a vital role in livelihood. Agriculture is the only way to feed ever growing populations. Several researchers are going on energetically in plant disease detection. Plant infection can affect the leaf which leads to huge loss in cultivation of crop and economical value of market. Mainly, in between the stages of sowing and harvesting. Plant infection are caused by various pests like virus, fungus and bacteria which causes infection to plants and results in loss of quantity and amount of production. Also, plant diseases increase due to pollution and other environmental changes. The plants should be supervised from its germinal stage of their life-cycle to evade such diseases. To monitor such type of infection manually is extremely difficult and also time consuming. It is necessary to devise a method to speed up this identification process. This technique is imperative, so it is decided to automate the disease detection system. Hence, image processing is used for the recognition of plant infection. Here, matching and segmentation algorithms are used for identifying the diseases. Classification algorithm is used for classifies the disease. Machine learning techniques are used for improving the diagnosis of plant infection. Identification of pesticides for those affected diseases is also suggested.