Architecture Based Classification of Leaf Images

Plant classification and identification is an important and difficult task. In this paper, a systematic approach for extracting the leaf architecture characters from captured digital images is proposed. The input image is first pre-processed to be prepared for feature extraction. In the second stage, different architectural features are extracted and mapped to semantic botanical terms. Lastly, we propose a method for classifying leaf images based on these features. Compared with previous studies, the proposed method combines extracted features of an image with specific knowledge of leaf architecture in the domain of botany to provide a comprehensive framework for both computer engineers and botanist. Finally, based on the proposed method, experiments on the classification of the images from ImagerCLEF 2012 dataset has been performed and results are presented.