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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Nearest Feature Line Discriminant Analysis in DFRCT Domain for Image Feature Extraction
verfasst von : Lijun Yan, Cong Wang, Jeng-Shyang Pan
Erschienen in: Computational Collective Intelligence. Technologies and Applications
Verlag: Springer Berlin Heidelberg
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A novel subspace learning algorithm based on nearest feature line in time-frequency domain is proposed in this paper. The proposed algorithm combines neighborhood discriminant nearest feature line analysis and fractional cosine transform to extract the local discriminant features of the samples. A new discriminant power criterion based on nearest feature line is also presented in this paper. Some experiments are implemented to evaluate the proposed algorithm and the experimental results demonstrate the efficiency of the proposed algorithm.