Detecting jute plant disease using image processing and machine learning

Abstract

Detecting stem diseases of plants by image analysis are still in an inchoate state in the research field. This research has been conducted on detecting the stem diseases of jute plants which is one of the most important cash crops in some of the Asian countries. An automated system based on an Android application has been implemented to take pictures of the disease affected stems of jute plants and send them to the dedicated server for assaying. On the server side, the affected portion from the image will be segmented using customized thresholding formula based on hue-based segmentation. The consequential feature values will be extracted from the segmented portion for texture analysis using color co-occurrence methodology. The extracted values will be compared with the sample values stored in the pre-defined database which will lead the disease to be identified and classified using Multi-SVM classifier. At the final step, the classification result along with the necessary control measures will be sent back to the farmer within three seconds through the application on their phone.