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Two-dimensional shape recognition with Cosine Transform-Based Synthesized Affine Invariant Function

Two dimensional shape recognition needs to remove the effect of geometric transformations from the contour pattern. This is usually obtained by transforming the contour pattern into an affine invariant form. In this paper, the cosine transform is used to decompose the contour pattern of the object shape into a set of synthesized feature signals (SFS). Then the SFSs are used to evaluate the cosine transform based synthesized affine invariant function (CSAIF) for the shape recognition. The information loss of representing the contour pattern with the CSAIF is minimized by simply neglecting the translation component. This assures high accuracy in recognizing the object shape by discriminating its CSAIF from others. Experiments examine the performance and robustness of the CSAIF based shape recognition and the results are compared with that of using the Fourier affine invariant function.