Plant disease analysis using histogram matching based on Bhattacharya's distance calculation

Farmers in rural India have minimal access to agricultural experts, who can inspect crop images and render advice, Delayed expert responses to queries often reach farmers too late. Many of the farmers will be unaware of the non-native diseases, and they cannot go to experts always and take suggestions from them if they are in some rural areas. So the image processing techniques can be applied to detect the healthiness of the leaf by acquiring the image of it and applying algorithms to detect the disease. It requires less cost and helps in increased production. We design a system which tells the farmer about the type of the disease present or occurring to their plants. We are considering paddy plant for the experimental purpose, later which can be implemented for other crops also. The diseases we are focusing are leaf blast (disease one), leaf blight (disease two). First the leaves are classified into healthy and the diseased samples. We use Bhattacharya's similarity calculation method for finding similarity in histogram of test image or sample imageswith respect to clinically proved healthy image(standard image). During the training phase, we used 100 sample images of healthy, disease one, disease two leaves for obtaining standard values which represents respective types, based on which type of the test leaf is detected.