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Proceedings Paper

Syntactic texture and perception for a new generic visual anomalies classification
Author(s): Simon-Frédéric Désage; Gilles Pitard; Maurice Pillet; Hugues Favrelière; Jean-Luc Maire; Fabrice Frelin; Serge Samper; Gaëtan Le Goïc
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Paper Abstract

The research purpose is to improve aesthetic anomalies detection and evaluation based on what is perceived by human eye and on the 2006 CIE report.1 It is therefore important to define parameters able to discriminate surfaces, in accordance with the perception of human eye. Our starting point in assessing aesthetic anomalies is geometric description such as defined by ISO standard,2 i.e. traduce anomalies description with perception words about texture divergence impact. However, human controllers observe (detect) the aesthetic anomaly by its visual effect and interpreter for its geometric description. The research question is how define generic parameters for discriminating aesthetic anomalies, from enhanced information of visual texture such as recent surface visual rendering approach. We propose to use an approach from visual texture processing that quantify spatial variations of pixel for translating changes in color, material and relief. From a set of images from different angles of light which gives us access to the surface appearance, we propose an approach from visual effect to geometrical specifications as the current standards have identified the aesthetic anomalies.

Paper Details

Date Published: 30 April 2015
PDF: 9 pages
Proc. SPIE 9534, Twelfth International Conference on Quality Control by Artificial Vision 2015, 953406 (30 April 2015); doi: 10.1117/12.2182819
Show Author Affiliations
Simon-Frédéric Désage, Lab. SYMME, Univ. de Savoie (France)
Gilles Pitard, Lab. SYMME, Univ. de Savoie (France)
Maurice Pillet, Lab. SYMME, Univ. de Savoie (France)
Hugues Favrelière, Lab. SYMME, Univ. de Savoie (France)
Jean-Luc Maire, Lab. SYMME, Univ. de Savoie (France)
Fabrice Frelin, Lab. SYMME, Univ. de Savoie (France)
Serge Samper, Lab. SYMME, Univ. de Savoie (France)
Lab. de Recherche en Mécanique Appliquée, CNRS, Univ. de Rennes 1 (France)
Gaëtan Le Goïc, Lab. SYMME, Univ. de Savoie (France)
Le2i, CNRS, Univ. de Bourgogne (France)


Published in SPIE Proceedings Vol. 9534:
Twelfth International Conference on Quality Control by Artificial Vision 2015
Fabrice Meriaudeau; Olivier Aubreton, Editor(s)

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