Abstract
This study develops a surface inspection methodology used to detect complex geometry products and metallic reflective surfaces imperfections. This work is based on combination of three complementary methods: an optical one (structured light information), an algorithmic one (data processing) and a statistical one (parameters processing).A usual industrial application illustrates this processing.
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Guerra, A.S.: Métrologie sensorielle dans le cadre du contrôle qualité visuel. Université de Savoie (2008), http://hal.archives-ouvertes.fr/tel-00362743/
Baudet, N.: Maitrise de la qualité visuelle des produits – Formalisation du processus d’expertise et proposition d’une approche robuste de contrôle visuel humain. Université de Grenoble (2012), http://tel.archives-ouvertes.fr/tel-00807304/
Le Goïc, G., Samper, S.: Système de détection d’anomalies d’aspect par la technique PTM (2011), http://hal.archives-ouvertes.fr/hal-00740313/
Baudet, N., Pillet, M., Maire, J.L.: Proposition d’une approche méthodologique pour réduire la variabilité dans le contrôle visuel à but esthétique. In: Proceeding of the International Conference on Surface Metrology, ICSM (2012), http://hal.univ-savoie.fr/hal-00740267/
ISO-8785 Geometrical Product Specification (GPS) – Surface Imperfection - Terms, definitions and parameters - International Organization for Standardization (1998)
Nguyen, T.S., et al.: Etude d’un algorithme de détection de défauts sur des images de chaussées. XXIIe colloque GRETSI (Signal and Image Processing). Dijon (2009), http://documents.irevues.inist.fr/handle/2042/29100
Dellepiane, M., et al.: High quality PTM acquisition: reflection transformation imaging for large objects. In: Proceedings of the 7th International Conference on Virtual Reality, Archeology and Intelligent Cultural Heritage (2006), http://dl.acm.org/citation.cfm?id=2384330
Duffy, S.: Polynomial texture mapping at roughting linn rock art site. In: Proceeding of the ISPRS Commission V Mid-Term Symposiumm’close range image measurement techniques (2010), http://www.isprs.org/proceedings/XXXVIII/part5/papers/159.pdf
Baril, J.: Modèles de representation multi-résolution pour le rendu photo-réaliste de matériaux complexes. Université Sciences et Technologies Bordeaux 1 (2010), http://hal.archives-ouvertes.fr/tel-00525125/
Palma, G.: Visual appareance: Reflectance transformation imaging, RTI (2013)
Tunwattanapong, B., et al.: Acquiring reflectance and shape from continuous spherical harmonic illumination. ACM Transactions on Graphics (TOG) 32(4) (2013)
Elhabian, S.Y., et al.: Towards efficient and compact phenomenological representation of arbitrary bidirectional surface reflectance. In: British Machine Vision Conference, Dundee (2011), http://mecca.louisville.edu/wwwcvip/research/publications/Pub_Pdf/2011/Shireen/Elhabian_BMVC2011.pdf
Zamuner, G.: Application of artificial vision to the quality inspection of surfaces of luxury products. Ecole Polytechnique Fédérale de Lausanne (2012)
Zheng, H., et al.: Automatic inspection of metallic surface defects using genetic algorithms. Journal of Materials Processing Technology (2002)
Morard, V.: Detection de structures fines par traitements d’images et apprentissage statistique: application au contrôle non destructif. Ecole nationale supérieur des Mines de Paris (2012), http://imanalyse.free.fr/publications/Morardi-2012-These.pdf
Morard, V., et al.: One-dimensional openings, granulometries and component trees in per pixel. IEEE Journal of Selected Topics in Signal Processing 6(7) (2012), doi:10.1109/JSTSP.2012.2201694
Jahanshahi, M.R., et al.: An innovative methodology for detection and quantification of cracks through incorporation of depth perception. Machine Vision and Application 24(2) (2011), doi:10.1007/s00138-011-0394-0
Jahanshahi, M.R., Masri, S.F.: A new methodology for non-contact accurate crack width measurement through photogrammetry for automated structural safety evaluation. Smart Materials and Structures 22(3) (2013), doi:10.1088/0964-1726
Ngan, H., et al.: Automated fabric defect detection – A review. Image and Vision Computing 29(7) (2011), doi:10.1016/j.imavis.2011.02.002
Serra, J.: Morphological filtering: An overview. Signal Processing 38(1) (1994), doi:10.1016/0165-1684(94)90052-3
Pillet, M.: Les plans d’expériences par la method Taguchi (2001), http://hal.archives-ouvertes.fr/hal-00470004/
Moon, H., Kim, J.: Intelligent crack detecting algorithm on the concrete crack image using neural network. In: Proceedings of the 28th ISARC (2011)
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Désage, SF. et al. (2014). Visual Quality Inspection and Fine Anomalies: Methods and Application. In: Ratchev, S. (eds) Precision Assembly Technologies and Systems. IPAS 2014. IFIP Advances in Information and Communication Technology, vol 435. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45586-9_13
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DOI: https://doi.org/10.1007/978-3-662-45586-9_13
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