文章基本信息

标题：Leaf Classification Using Shape, Color, and Texture Features
本地全文：下载
作者：Abdul Kadir ; Lukito Edi Nugroho ; Adhi Susanto 等
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2011
卷号：1
期号：3-2
出版社：Seventh Sense Research Group
摘要：— 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.
关键词：Color features; Foliage plants; Lacunarity; Leaf classification; PFT; PNN; Texture features