Leaf classification methods based on SVM and SIFT

Abstract

In this research, Support Vector Machine (SVM) and Scale-Invariant Feature Transform (SIFT) are used to identify plants. For each leaf image, the algorithm localizes the keypoints and assigns orientations for each keypoint. Then it matches the sample leaves with the comparison leaves to find out whether they belong to the same category. After conducting edge detection and feature extraction, the experimental result shows that the method for classification gives average accuracy of approximately 99 % when it is tested on 12 descriptive features. © 2013 Springer-Verlag.