Identification of Sugarcane Leaf Scorch Diseases using K-means Clustering Segmentation and K-NN based Classification

Abstract

Sugarcane is the most important plant in Indian agriculture as well as in economy also. In this world, India is a second largest production of sugarcane. Sugar is the by-product of sugarcane and it participates in our day today life in all the essential food items. Farmers are much interested to gain profit when they harvest from their land. Normally the plants may affect by the natural deficiency like water, sunlight and soil. Most of the plants leaves are affected by fungal diseases caused by viruses. Same way the sugarcane also affected by the bacterial diseases and it will leads the farmer to spend more time to identify the diseases and it increase cost to prevent from the diseases. The samples of sugarcane leaf scorch taken for the experiment. This leaf scorch caused by the bacterium which is popularly known as Xylella Fastidiosa. This paper emphasizes to detect and classify the sugarcane leaf scorch diseases automatically by using image processing techniques they are acquisition, filtering, segmentation and feature extraction. The accuracy of this experiment is given 95%.