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Symmetry 2010, 2(2), 554-581; doi:10.3390/sym2020554

Symmetry as an Intrinsically Dynamic Feature

1,2,, 1,3,*  and 4
1 DMA, Università degli Studi di Palermo, via Archirafi 34, 90123 Palermo, Italy 2 CITC, Università degli Studi di Palermo, via Archirafi 34, 90123 Palermo, Italy 3 Istituto Nazionale di Ricerche Demopolis, via Col. Romey 7, 91100 Trapani, Italy 4 IEF, Université Paris IX–Orsay, Paris, France Deceased on 15 March 2009.
* Author to whom correspondence should be addressed.
Received: 4 March 2010 / Revised: 23 March 2010 / Accepted: 29 March 2010 / Published: 1 April 2010
(This article belongs to the Special Issue Feature Papers: Symmetry Concepts and Applications)
Download PDF [1977 KB, 1 April 2010; original version 1 April 2010]


Symmetry is one of the most prominent spatial relations perceived by humans, and has a relevant role in attentive mechanisms regarding both visual and auditory systems. The aim of this paper is to establish symmetry, among the likes of motion, depth or range, as a dynamic feature in artificial vision. This is achieved in the first instance by assessing symmetry estimation by means of algorithms, putting emphasis on erosion and multi-resolution approaches, and confronting two ensuing problems: the isolation of objects from the context, and the pertinence (or lack thereof) of some salient points, such as the centre of mass. Next a geometric model is illustrated and detailed, and the problem of measuring symmetry in a world where symmetry is not perfect nor the only attention trigger is tackled. Two algorithmic lines, based on the so-called symmetry kernel and its evolution with pattern warping, and by correlation of blocks with varying sizes and positions, are proposed and investigated. An extended illustration of the power of symmetry as a feature, based on face expression recognition, concludes the paper.
Keywords: symmetry; features; artificial vision symmetry; features; artificial vision
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Di Gesu, V.; Tabacchi, M.E.; Zavidovique, B. Symmetry as an Intrinsically Dynamic Feature. Symmetry 2010, 2, 554-581.

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