Robust recognition of planar shapes under affine transforms using principal component analysisTools Tzimiropoulos, Georgios, Mitianoudis, Nikolaos and Stathaki, Tania (2007) Robust recognition of planar shapes under affine transforms using principal component analysis. IEEE Signal Processing Letters, 14 (10). pp. 723-726. ISSN 1070-9908 Full text not available from this repository.
Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4303087&filter%3DAND%28p_IS_Number%3A4303057%29
AbstractA scheme, based on Principal Component Analysis (PCA), is proposed that can be used for the recognition of 2D planar shapes under affine transformations. A PCA step is first used to map the object boundary to its canonical form, reducing the problem of the non-uniform sampling of the object contour introduced by the affine transformation. Then, a PCAbased scheme is employed to train a set of basis functions on the signals extracted from the objects’ boundaries. The derived bases are used to analyze the boundary locally. Based on the theory of invariants and local boundary analysis, an novel invariant function is constructed. The performance of the proposed framework is compared with a standard wavelet-based approach with promising results.
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