Fruit Disease Detection Using Color,Texture and ANN

Now-a-days as there is prohibitive demand for agricultural industry, effective growth and improved yield of fruit is necessary and important. But manual monitoring will not give satisfactory result all the times and they always need satisfactory advice from expert. So it requires proposing an efficient smart farming technique which will help for better yield and growth with less human efforts. 

Traditional system uses thousands of words which lead to boundary of language. Whereas system that we have come up with, uses image processing techniques for implementation as image is easy way for conveying. In the proposed work, OpenCV library is applied for implementation. K-means clustering method is applied for image segmentation, the images are catalogue and mapped to their respective disease categories on basis of four feature vectors colour, morphology, texture and structure of hole on the fruit. Artificial Neural Network (ANN) concept is used for pattern matching and classification of diseases.

keywords: OpenCV, K-means clustering, SURF, Artificial Neural Network.