Comparative Study of Feature Extraction Components from Several Wavelet Transformations for Ornamental Plants
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2014, Vol 3, Issue 2
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.
Authors and Affiliations
Kohei Arai, Indra Abdullah, Hiroshi Okumura
Keywords
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- EP ID EP121136
- DOI 10.14569/IJARAI.2014.030202
- Views 108
- Downloads 0
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