AN IDENTIFICATION OF CROP DISEASE USING IMAGE SEGMENTATIONAbstract
Agriculture forms a vital part of India’s economy. More than 50% of India’s population is dependent on agriculture for their livelihood. In India, many crops are cultivated, out of which wheat is one of the most important food grains that this country cultivates and exports. Thus it can be seen that wheat forms a major part of the Indian agricultural system and India’s economy. Hence, the maintenance of the steady production of the above-stated crop is very important. The main idea of this project is to provide a novel approach based on a deformable model is proposed to handle the segmentation of the system for detecting crop diseases. The existing system is based on the segmentation method simple linear iterative clustering to detect disease in plant leaves. It also shows visual attributes such as color, gradient, texture, and shape to describe the features of leaves. The proposed system will define the cropped image of a wheat plant through image processing and feature extraction algorithms. The RGB color space is converted so that the color information contained in the images can be used effectively to differentiate image and segmentation usage of the k-means algorithm has been suggested.
K. V. Kumar * and T. Jayasankar
Department of Electronics & Communication Engineering, Karpagam Institute of Technology, Coimbatore, Tamil Nadu, India
09 June 2018
22 August 2018
31 August 2018
01 March 2019