Comparative Study of Feature Extraction Components from Several Wavelet Transformations for Ornamental Plants
نویسندگان
چکیده
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 Dualtree 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. Keywords—wavelet transformation; shift invariant; rotation invariant; feature extraction; leaf identification.
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