Feature Extraction and Disease Prediction from Paddy Crops Using Data Mining Techniques

Abstract

In the Indian economy, the agriculture sector has a very important role. So, identification and early stage detection of diseases of the infected plants in a timely manner are a challenge in the field of data mining. Researchers are always trying to develop an efficient automated disease classification system to identify crop diseases. This paper presents the development of an automated system that will analyze the diseased infected paddy plant images and will provide guidance to the farmers. The main goal of the development of rice disease classification system is that it identifies and classifies the rice diseases automatically. The work is divided mainly in two parts, namely rice disease detection and classification of rice diseases. In disease detection task, at first, features responsible for diseases are extracted from the diseased portion of the rice images using various feature extraction techniques, and then important and relevant features are selected from the extracted features using the proposed method. The proposed method gives a remarkable result which can help in the agricultural field.