Robust recognition of planar shapes under affine transforms using principal component analysis

Tzimiropoulos, G. and Mitianoudis, N. and Stathaki, T. (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 content URL: http://dx.doi.org/10.1109/LSP.2007.896434

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Item Type:Article
Item Status:Live Archive

Abstract

A scheme, based on principal component analysis (PCA), is proposed that can be used for the recognition of 2-D 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 nonuniform sampling of the object contour introduced by the affine transformation. Then, a PCA-based 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, a novel invariant function is constructed. The performance of the proposed framework is compared with a standard wavelet-based approach with promising results. © 2007 IEEE.

Keywords:Boundary conditions, Functions, Principal component analysis, Robust control, Wavelet transforms, Affine transformation, Robust recognition, Shape recognition, Image recognition
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
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ID Code:8740
Deposited On:26 Jul 2013 09:17

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