Leaf Classification Using Shape, Color, and Texture Features

نویسندگان

  • Abdul Kadir
  • Lukito Edi Nugroho
  • Adhi Susanto
  • Paulus Insap Santosa
چکیده

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. Keywords—Color features, Foliage plants, Lacunarity, Leaf classification, PFT, PNN, Texture features.

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عنوان ژورنال:
  • CoRR

دوره abs/1401.4447  شماره 

صفحات  -

تاریخ انتشار 2011