Syntactic texture and perception for a new generic visual anomalies classification
| Autor: | Hugues Favreliere, Fabrice Frelin, Gilles Pitard, Simon-Frédéric Desage, Serge Samper, Jean-Luc Maire, Maurice Pillet, Gaëtan Le Goïc |
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| Přispěvatelé: | Laboratoire SYstèmes et Matériaux pour la MEcatronique (SYMME), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement |
| Rok vydání: | 2015 |
| Předmět: |
Surface imperfection
0209 industrial biotechnology Computer science media_common.quotation_subject classication 02 engineering and technology 010501 environmental sciences Research purpose 01 natural sciences Rendering (computer graphics) [SPI]Engineering Sciences [physics] 020901 industrial engineering & automation Perception medicine Computer vision 0105 earth and related environmental sciences media_common Pixel business.industry geometrical description visual eect Visual texture Visual inspection medicine.anatomical_structure Human visual system model visual texture Human eye Artificial intelligence business visual inspection |
| Zdroj: | SPIE Proceedings Quality Control by Artificial Vision (QVAV) Quality Control by Artificial Vision (QVAV), Jun 2015, Le Creusot, France. ⟨10.1117/12.2182819⟩ |
| ISSN: | 0277-786X |
| Popis: | The research purpose is to improve aesthetic anomalies detection and evaluation based on what is perceived byhuman eye and on the 2006 CIE report. 1 It is therefore important to de ne parameters able to discriminatesurfaces, in accordance with the perception of human eye. Our starting point in assessing aesthetic anomaliesis geometric description such as de ned by ISO standard, 2 i.e. traduce anomalies description with perceptionwords about texture divergence impact. However, human controllers observe (detect) the aesthetic anomalyby its visual e ect and interpreter for its geometric description. The research question is how de ne genericparameters for discriminating aesthetic anomalies, from enhanced information of visual texture such as recentsurface visual rendering approach. We propose to use an approach from visual texture processing that quantifyspatial variations of pixel for translating changes in color, material and relief. From a set of images from di erentangles of light which gives us access to the surface appearance, we propose an approach from visual e ect togeometrical speci cations as the current standards have identi ed the aesthetic anomalies.Keywords: visual inspection, classi cation, Surface imperfection, geometrical description, visual e ect, visualtexture |
| Databáze: | OpenAIRE |
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