Hevea Brasiliensis Leaf Disease Detection using MATLAB

Abstract

Indian economy relies on Agriculture which is the back bone of India. Indian Agricultural sector accounts for 18% of India’s GDP and employment to 50% of country workforce. Both quality and quantity of agricultural products are equally important. The conventional human naked eye quality inspection is not significant for large members of leaves as it is unpredictable and inconsistent. Disease identification is the key for decreasing and preventing plant illnesses. Health monitoring and contamination identification on plant is fundamental for feasible agriculture. It is hard to display the plant infections physically because it requires huge measure of labor, expertize inside the plant ailments, and furthermore require the over the pinnacle managing time. Thus the solution overcoming these kind of constraints is image processing. The process of image processing includes acquisition of photo, pre- processing of photo, segmentation of image, function extraction and class. To overcome digital image processing technoques has been implied. This paper proposed technique for evaluation and detection of plant leaf disorder using digital image processing. This paper proposes k clustering algorithm for the detection of the diseases. The major of the leaf diseases is mainly caused in hevea brasiliensis are Birds’ eye spot, collectotrichum leaf disease and collectotrium leaf disease. This way of detection have immense potential to classify the diseased leaf among healthy leaves.