Detection and classification of areca nut diseases

India is well known for its agricultural products cultivation. Areca nut, also known as Betel nut, is considered to be one of the primary crops. The raw areca nut set consist of both healthy and unhealthy areca nuts. For farmers, it would be tedious procedure to classify which areca nuts are healthy and unhealthy. The proposed system classifies healthy and unhealthy nuts using image processing by taking raw (with husk) areca nut images as input. The process of classification includes background subtraction to remove the shadow effects found in the images collected. Otsu method is used to find the infected regions. Decision tree is being used to classify the images by considering the texture features that are derived from the image using GLCM texture feature extraction method. The proposed method is implemented in MATLAB and achieves 90 percent accuracy.