Machine learning algorithm for leaf disease detection
Pravin R. Kshirsagar, D. B. V. Jagannadham, M. Belsam Jeba Ananth, Anand Mohan, Ganesh Kumar, Pankaj Bhambri
Abstract
Identification and classification of plant diseases is a major field of study, as most people in India depend on agriculture for their main source of income and food. This is one of the reasons why the identification of plant diseases plays a significant role in agriculture. It is useful to detect plant disease through any automated technique as it eliminates a significant amount of monitoring work in large crop farms and detects the symptoms of diseases at a very early stage, i.e. when they appear on plant leaves. The framework mainly involves different concepts related to image processing, such as image acquisition, image pre-processing, and extraction of features, database formation, and artificial neural network classification. This paper covers research on various methodologies for the use of neural networks to detect plant leaf diseases.