Leaf Classification Using Shape, Color, and Texture Features

Autor:	Kadir, Abdul, Nugroho, Lukito Edi, Susanto, Adhi, Santosa, Paulus Insap
Rok vydání:	2013
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Computers and Society
Druh dokumentu:	Working Paper
Popis:	Several methods to identify plants have been proposed by several researchers. Commonly, the methods did not capture color information, because color was not recognized as an important aspect to the identification. In this research, shape and vein, color, and texture features were incorporated to classify a leaf. In this case, a neural network called Probabilistic Neural network (PNN) was used as a classifier. The experimental result shows that the method for classification gives average accuracy of 93.75% when it was tested on Flavia dataset, that contains 32 kinds of plant leaves. It means that the method gives better performance compared to the original work. Comment: 6 pages, International Journal of Computer Trends and Technology- July to Aug Issue 2011
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1401.4447 Zobrazit plný text záznamu View this record from Arxiv