A feature-based model of symmetry detection.

Full Abstract

Symmetry detection is important for many biological visual systems, including those of mammals, insects and birds. We constructed a symmetry-detection algorithm with two stages:
location of the visually salient features of the image, then evaluating the symmetry of these features over a long range, by means of a simple Gaussian filter. The algorithm detects the axis of maximum symmetry for human faces (or any arbitrary image) and calculates the magnitude of the asymmetry. We have evaluated the algorithm on the dataset of Rhodes et al. (1998 Psychonom. Bull. Rev. 5, 659-669) and found that the algorithm is able to discriminate small variations of symmetry created by computer-manipulating the symmetry levels in individual faces, and that the values measured by the algorithm correlate well with human psycho-physical symmetry ratings.

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Author information

Author/s: Scognamillo, Renata (R); Rhodes, Gillian (G); Morrone, Concetta (C); Burr, David (D);

Affiliation: Scuola Normale Superiore, Piazza dei Cavalieri, Pisa, Italy. r.scognamillo(-atsign-)sns.it

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Proceedings. Biological sciences / The Royal Society (Proc Biol Sci), published in England. (Language: eng)

Reference: 2003-Aug; vol 270 (issue 1525) : pp 1727-33

Dates: Created 2003/09/10; Completed 2003/10/23; Revised 2006/11/15;

PMID: 12965001, status: MEDLINE (last retrieval date: 11/6/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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