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

Tzimiropoulos, Georgios; Mitianoudis, Nikolaos; Stathaki, Tania


Georgios Tzimiropoulos

Nikolaos Mitianoudis

Tania Stathaki


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.


Tzimiropoulos, G., Mitianoudis, N., & Stathaki, T. (2009). A unifying approach to moment-based shape orientation and symmetry classification. IEEE Transactions on Image Processing, 18(1),

Journal Article Type Article
Publication Date Jan 1, 2009
Deposit Date Feb 1, 2016
Publicly Available Date Feb 1, 2016
Journal IEEE Transactions on Image Processing
Print ISSN 1057-7149
Electronic ISSN 1057-7149
Publisher Institute of Electrical and Electronics Engineers
Peer Reviewed Peer Reviewed
Volume 18
Issue 1
Public URL
Publisher URL
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