Shape based leaf recognition

Humans carry out object recognition as a very primitive task. However, knowing all the detailed information regarding an object is mostly not possible. Therefore, object recognition and linking the object to associated data is a popular research area. In this study, we have measured leaf recognition performances of different feature and data sets using image processing techniques. We have studied the effects of general shape features, Fourier descriptors and MDM-A feature sets for the solution of this problem. We have also measured performance evaluation by fusing these features. Eventually, we have observed a compatible performance with similar studies.