research-article

Affine invariant shape matching using radon transform and dynamic time warping distance

Authors:

Makoto Hasegawa,

Salvatore TabboneAuthors Info & Claims

SAC '12: Proceedings of the 27th Annual ACM Symposium on Applied Computing

Pages 777 - 781

https://doi.org/10.1145/2245276.2245426

Published: 26 March 2012 Publication History

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Abstract

An affine invariant shape matching method using the Radon transform and the dynamic time warping distance is proposed. Our descriptor based on the Radon transform is robust to shapes rotation, uniform scaling, and translation. For non-uniform scaling and shearing, our descriptor has a non-linear sparse and dense distortion relative to the angle coordinates. Therefore, we apply the dynamic time warping to be robust to these transformations. Our performances are better for any affine transformations than the conventional other methods.

References

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S. Tabbone, O. R. Terrades, and S. Barrat. Histogram of Radon transform. a useful descriptor for shape retrieval. In ICPR, pages 1--4. IEEE, 2008.

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S. Tabbone, L. Wendling, and J.-P. Salmon. A new shape descriptor defined on the Random transform. CVIU, 102(1): 42--51, 2006.

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Cited By

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Hammouda GSellami DHammouda A(2018)Pattern recognition based on compound complex shape-invariant Radon transformThe Visual Computer10.1007/s00371-018-1604-9Online publication date: 27-Oct-2018
https://doi.org/10.1007/s00371-018-1604-9
Pilar BShekar B(2016)An integrated approach of radon transform and blockwise binary pattern for shape representation and classification2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)10.1109/ICACCI.2016.7732341(1976-1982)Online publication date: Sep-2016
https://doi.org/10.1109/ICACCI.2016.7732341

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An affine invariant shape matching method using the histogram of Radon transform (HRT) and the dynamic time warping (DTW) distance is proposed. Our descriptor based on the Radon transform is robust to shape rotation, uniform scaling, and translation. ...
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Published In

SAC '12: Proceedings of the 27th Annual ACM Symposium on Applied Computing

March 2012

2179 pages

ISBN:9781450308571

DOI:10.1145/2245276

Conference Chairs:
Sascha Ossowski
University Rey Juan Carlos, Spain
,
Paola Lecca
The Microsoft Research - University of Trento COSBI, Italy

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 26 March 2012

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SAC 2012: ACM Symposium on Applied Computing

March 26 - 30, 2012

Trento, Italy

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SAC '12 Paper Acceptance Rate 270 of 1,056 submissions, 26%;

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Hammouda GSellami DHammouda A(2018)Pattern recognition based on compound complex shape-invariant Radon transformThe Visual Computer10.1007/s00371-018-1604-9Online publication date: 27-Oct-2018
https://doi.org/10.1007/s00371-018-1604-9
Pilar BShekar B(2016)An integrated approach of radon transform and blockwise binary pattern for shape representation and classification2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)10.1109/ICACCI.2016.7732341(1976-1982)Online publication date: Sep-2016
https://doi.org/10.1109/ICACCI.2016.7732341

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Affine Invariant Shape Matching using Histogram of Radon Transform and Angle Correlation Matrix

Histogram of Radon transform with angle correlation matrix for distortion invariant shape descriptor

Amplitude-only log Radon transform for geometric invariant shape descriptor

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