A unifying approach to moment-based shape orientation and symmetry classification

Tzimiropoulos, Georgios, Mitianoudis, Nikolaos and Stathaki, Tania (2009) A unifying approach to moment-based shape orientation and symmetry classification. IEEE Transactions on Image Processing, 18 (1). pp. 125-139. ISSN 1057-7149

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In this paper, the problem of moment-based shape orientation and symmetry classification is jointly considered. A generalization and modification of current state-of-the-art geometric moment-based functions is introduced. The properties of these functions are investigated thoroughly using Fourier series analysis and several observations and closed-form solutions are derived. We demonstrate the connection between the results presented in this work and symmetry detection principles suggested from previous complex moment-based formulations. The proposed analysis offers a unifying framework for shape orientation/symmetry detection. In the context of symmetry classification and matching, the second part of this work presents a frequency domain method, aiming at computing a robust moment-based feature set based on a true polar Fourier representation of image complex gradients and a novel periodicity detection scheme using subspace analysis. The proposed approach removes the requirement for accurate shape centroid estimation, which is the main limitation of moment-based methods, operating in the image spatial domain. The proposed framework demonstrated improved performance, compared to state-of-the-art methods.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/1014037
Additional Information: © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1109/TIP.2008.2007050
Depositing User: Tzimiropoulos, Yorgos
Date Deposited: 01 Feb 2016 11:03
Last Modified: 04 May 2020 20:26
URI: https://eprints.nottingham.ac.uk/id/eprint/31407

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