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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Herbal Leave Recognition System Based on Dirichlet Laplacian Eigenvalues

Author 1: Mahmoud Elgamal Author 2: Mahmoud Youness R. Alaidy
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 5, No. 5 · Published 2014

DOI: https://doi.org/10.14569/IJACSA.2014.050532

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Abstract

Identifying and recognition of herbal plant green leaves is essential in botanical study. In[8] Thai herb leaf image recognition system used for recognition of leaves with accuracy of 93.29%, in this paper, we propose a recognition system of leaves based on the eigenvalues of Dirichlet Laplacian that used to generate three different sets of features for shape analysis and classification in binary images[4]. First leaf images are preprocessed to remove unwanted background, converted to binary form; used to build the images database, finally Queries made on the system. The correct classification rates without noise is 100% and with noise is 90%.

Keywords

Eigenvalues Finite difference method Curve descriptor Binary image classification noise leave recognition.

How to Cite this Article

Elgamal, M., & Alaidy, M. Y. R. (2014). Herbal Leave Recognition System Based on Dirichlet Laplacian Eigenvalues. International Journal of Advanced Computer Science and Applications, 5(5). https://doi.org/10.14569/IJACSA.2014.050532

Elgamal, Mahmoud, and Mahmoud Youness R. Alaidy. "Herbal Leave Recognition System Based on Dirichlet Laplacian Eigenvalues." International Journal of Advanced Computer Science and Applications, vol. 5, no. 5, 2014, https://doi.org/10.14569/IJACSA.2014.050532.

@article{Elgamal2014,
  title     = {Herbal Leave Recognition System Based on Dirichlet Laplacian Eigenvalues},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {5},
  number    = {5},
  year      = {2014},
  publisher = {The Science and Information Organization},
  author    = {Mahmoud Elgamal and Mahmoud Youness R. Alaidy},
  doi       = {10.14569/IJACSA.2014.050532},
  url       = {https://doi.org/10.14569/IJACSA.2014.050532}
}

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