Automated blast disease detection from paddy plant leaf — A color slicing approach

Abstract

In the era of technology, the various industries are shifting from manual to automated solutions of various problems in the hand. Whereas these techniques has not only augmented the efficiency, they also have shortened the cost, time and labor hours required to get an assured excellence. Food Industry now a days is one of the foremost areas smearing these technology aspects. In agriculture the paddy crop of is one of the major crops casing large amount of fields and serving the food necessities. But while in field this crop has to face a lot of problems which include malnutrition and different diseases originated from environmental conditions and pests too. These problems in turn cause a large loss to the produce. An expert advice may be followed on from the agriculture professionals to get rid of such circumstances. But the remote sites has to face the location problems and hence get affected from such issues. So it will be a much better approach if they can be advised by the experts after checking the actual health status of their crop via some technological means without reaching at the place. The idea behind this paper is to develop such an algorithm which can work out for the problem of Blast Disease of paddy crops by just examining the image of plant leaf by the experts along with necessary advice/action. The back bone of the disease detection algorithm is Color Slicing Technique which perceives the diseased spots and damaged proportion of total leaf, making it easy to get advice if disease exists and eliminate it within time so as to avoid losses.