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International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 3 Issue 2, 2014.
Abstract: Human has a duty to preserve the nature, preserving the plant is one of the examples. This research emphasis on ornamental plant that has functionality not only as ornament plant but also as a medicinal plant. Purpose of this research is to find the best of the particular feature extraction components from several wavelet transformations. It consists of Daubechies, Dyadic, and Dual-tree complex wavelet transformation. Dyadic and Dual-tree complex wavelet transformations have shift invariant property. While Daubechies is a standard wavelet transform that widely used for many applications. This comparison is utilizing leaf image datasets from ornamental plants. From the experiments, obtained that best classification performance attained by Dual-tree complex wavelet transformation with 96.66% of overall performance result.
Kohei Arai , Indra Nugraha Abdullah and Hiroshi Okumura, “Comparative Study of Feature Extraction Components from Several Wavelet Transformations for Ornamental Plants” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 3(2), 2014. http://dx.doi.org/10.14569/IJARAI.2014.030202
@article{2014,
title = {Comparative Study of Feature Extraction Components from Several Wavelet Transformations for Ornamental Plants},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2014.030202},
url = {http://dx.doi.org/10.14569/IJARAI.2014.030202},
year = {2014},
publisher = {The Science and Information Organization},
volume = {3},
number = {2},
author = {Kohei Arai and Indra Nugraha Abdullah and Hiroshi Okumura}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.