Fast And Accurate System For Leaf Recognition - Mostafa, SI; Latif, YM Abd El; Reda, NM (International Journal of Computer Sciences and Engineering, 2020)
Leaf recognition is used in various applications in domains like agriculture, forest, biodiversity protection. Leaf recognition based on images is a challenging task for computer, due to the appearance and complex structure of leaves, high variability between classes, and small differences between leaves in the same class. This paper reviews a state-of-the- art application for building a fast automatic leaf recognition system. We propose a combination of shape, color, texture features and sparse representation extraction for different leaf recognition tasks. In this paper two features databases have been built using 32 classes with 1980 images for Flavia dataset. In recent trends the Graphics processing units (GPU) emerge with high parallel computing capabilities. In this paper we used the computation ability of modern GPU to execute the proposed leaf classification that achieves classification results of 99% and extreme parallelism recognition.