usamaislam/leafdiag

LeafDiag is an Android mobile application, which can automatically identify the plants diseases based on its leaf appearance with some computer vision and machine learning techniques.

LeafDiag

This my undergraduate final year project. LeafDiag is an Android mobile application which can automatically identify the plants diseases based on its leaf appearance with some computer vision and machine learning techniques. The target group of the user is those who request a free and quick diagnosis on common leaf disease at any time of the day. EM and Otsu algorithms were used for segmentation. Color histogram and Tamura’s texture feature were extracted. ANN, SVM and Random Forest learning models were built respectively. Experiments and evaluations on different segmentations, feature extractions and classification methods were done to find the most effective approach. The higest average accuracy is 96.4%. Another desktop version was also developed. The application was mainly built with Java and Matlab. It was rewarded as a first class project. The source code can be access here. The report can be accessed here.