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Original scientific paper

https://doi.org/10.2498/cit.1001009

Affine Invariant Contour Descriptors Using Independent Component Analysis and Dyadic Wavelet Transform

Nisar Ahmed Memon
Syed Asif Mahmood Gilani
Asad Ali


Full text: english pdf 852 Kb

page 169-181

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Abstract

The paper presents a novel technique for affine invariant feature extraction with the view of object recognition based on parameterized contour. The proposed technique first normalizes an input image by removing the affine deformations using independent component analysis which also reduces the noise introduced during contour parameterization. Then four invariant functionals are constructed using the restored object contour, dyadic wavelet transform and conics in the context of wavelets. Experimental results are conducted using three different standard datasets to confirm the validity of the proposed technique. Beside this the error rates obtained in terms of invariant stability are significantly lower when compared to other wavelet based invariants. Also the proposed invariants exhibit higher feature disparity than the method of Fourier descriptors.

Keywords

Hrčak ID:

44591

URI

https://hrcak.srce.hr/44591

Publication date:

30.9.2008.

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