Automated system for detecting jute plant disease using image processing and machine learning integrated with mobile application

Abstract

In our research, we have implemented an automated system for disease detection of jute plants using image analysis and machine learning. We have also integrated this system with a mobile application for Android phones to serve the farmers where they get benefitted by identifying the diseases correctly and taking measures accordingly. At first, an image of the defected jute plant has been taken with the camera of the mobile phone. The farmers then just have to send the image to our server by selecting the options provided on the application. The image has been analyzed in the server where the plant’s affected parts will be segmented using hue-based segmentation method, features for the texture analysis has been extracted using color co-occurrence methodology and comparing with our pre-defined database the disease is identified and classified using SVM classifier. At the final step, the classification result along with the necessary control measurement has been sent back to the user through the application on the phone.