COTTON LEAF DISEASE IDENTIFICATION USING PATTERN RECOGNITION TECHNIQUES

Abstract

The large number of people depends on cotton crop. The recognition of cotton leaf disease are of the Major important as they have a cogent and momentous impact on quality and production of cotton. Cotton disease identification is an art and science.Now a day’s image processing technique is becoming a key technique for diagnosing the various features of the crop. The diseases can affect any part or area of the crop. This paper mainly focuses detection of various cotton crop diseases and to classify them. There are so many classification techniques such as k-Nearest Neighor classifier , k-means Classifier, Probabilistic Neural Network, Genetic Algorithm, Support Vector Machine, and Principal Component Analysis, Artificial neural network, Fuzzy logic. Selecting a classification method is always a difficult task because the quality of result can vary for different input data. A smart phone empowers farmer to keep updated with the on going conditions of his agricultural land using IOT at any time and any part of the world. IOT technology can reduce the cost and enhance the productivity of traditional farming.