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Affine Invariant Representation with Generic Polar Radius Integral Transform

Affine Invariant Representation with Generic Polar Radius Integral Transform

Year:    2022

Author:    Chunyan Liu, Jianwei Yang, Chengxi Zhou

Journal of Information and Computing Science, Vol. 17 (2022), Iss. 1 : pp. 64–74

Abstract

In many computer vision tasks, the extraction of features invariant to affine transform plays an important role. To achieve better accuracy, region-based approaches usually need expensive computation. Whereas, contour-based methods need less computation, but their performance is strongly dependant on the boundary extraction. A method, generic polar radius integral transform (GPRIT), is proposed to combine region-based and contour-based method together for the extraction of affine invariant features. Polar radius integral transform and central projection transform are all special cases of the proposed GPRIT. With GPRIT, any object is converted into a closed curve for data reduction. Consequently, stationary wavelet transform is conducted to construct affine invariants. Several experiments have been presented to evaluate performance of the proposed GPRIT.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2024-JICS-22363

Journal of Information and Computing Science, Vol. 17 (2022), Iss. 1 : pp. 64–74

Published online:    2022-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    11

Keywords:    generic polar radius integral transform (GPRIT) invariant affine transform feature extraction.

Author Details

Chunyan Liu

Jianwei Yang

Chengxi Zhou