Leaf Classification Using Shape, Color, and Texture Features

International Journal of Computer Trends and Technology (IJCTT)          
© July to Aug Issue 2011 by IJCTT Journal
Volume-1 Issue-3                           
Year of Publication : 2011
Authors : Abdul Kadir, Lukito Edi Nugroho, Adhi Susanto, Paulus Insap Santosa.


Abdul Kadir, Lukito Edi Nugroho, Adhi Susanto, Paulus Insap Santosa.. "Leaf Classification Using Shape, Color, and Texture Features"International Journal of Computer Trends and Technology (IJCTT),V1(3):306-311 July to Aug Issue 2011 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract: — 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.


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KeywordsColor features, Foliage plants, Lacunarity, Leaf classification, PFT, PNN, Texture features.