A Survey on Leaf Disease Detection Techniques

Abstract

Abstract: Plants get affected by various diseases, different pathogens, fungus, bacteria, and viruses that affect the plants. Some affect leaves, stems, fruits, flowers, and other parts of the plant. Diseases in plants are one of their kinds in nature. There are a few diseases that can be fought by the plant immune system but there are a few diseases that need to be focused and a little care has to be taken to find the particular disease at an early stage and take an immediate measure. This helps the agriculturists to save time and increase productivity over a relative period of time. To encounter such types of problems automatically, computer science provides various technologies to detect diseases which include machine learning and deep learning algorithms which resolve the problem. The leaves are just as important as other parts of the plant. Mainly the leaf diseases are most common among many plants than the other diseases caused on different parts. Because in general, the leaf is the sensitive part of the plant, the changes in it which can be observed by the naked eye whenever there is a change in the weather, soil, fertilizer, etc. Plant diseases make farmers suffer, which may be any disease related to any part of the plant. Plant diseases are just abnormal effects that disturb the normal functioning of plant life. Thus plants are the most important factors to create ecological balance in the environment. This paper focuses on different diseases caused to leaves. This is a survey paper that represents the disease detection in various leaves, algorithms, and techniques used.

Index Terms: Leaf diseases, Deep Convolution Neural Network, GoogleNet, AlexNet, Image Subdivision.