Development of a visual inspection system and the corresponding algorithm for the detection and subsequent classification of paint defects on car bodies in the automotive industry / Kim Katharina Kieselbach in JOURNAL OF COATINGS TECHNOLOGY AND RESEARCH, Vol. 16, N° 4 (07/2019)  

[article]  inJOURNAL OF COATINGS TECHNOLOGY AND RESEARCH > Vol. 16, N° 4 (07/2019) . - p. 1033-1042 Titre : Development of a visual inspection system and the corresponding algorithm for the detection and subsequent classification of paint defects on car bodies in the automotive industry Type de document : texte imprimé Auteurs : Kim Katharina Kieselbach, Auteur ; Matthias Nöthen, Auteur ; Henning Heuer, Auteur Année de publication : 2019 Article en page(s) : p. 1033-1042 Note générale : Bibliogr. Langues : Américain (ame) Catégories : Automobiles -- Revêtements:Automobiles -- Peinture Contrôle technique Détection de défauts (Ingénierie) Qualité -- Contrôle Revêtements -- Défauts:Peinture -- Défauts Surfaces -- défauts Index. décimale : 667.9 Revêtements et enduits Résumé : Increasing expectations of customers on the appearance of cars force the automotive paint shops to inspect all car bodies with great care. Currently, skilled workers visually inspect each car body to detect and repair occurring paint defects. However, humans can neither detect nor judge the blemishes objectively and reliably over a longer period. Hence, this paper focuses on the development and validation of an algorithm for a surface inspection system, which improves the accuracy of detecting paint defects through an image processing system. Once they are detected, a reliable classifier is necessary to gain further information about the paint defects. The generated data can be utilized for improving the paint application process and for identifying the perpetrator of the paint defects once the defect classification is operational. As a consequence, the quality control circuit can be shortened, the surface quality of different paint formulae can be evaluated objectively, and actions can be taken in order to reduce the occurrences of certain defect types. This paper presents the physical setup of the visual inspection system and a detailed description of the algorithm for detecting the defects in the acquired images. Further research is essential to generate a classifier to differentiate the types of paint defects. Note de contenu : - EXPERIMENTAL METHODS AND MATERIALS : System description - Defect detection method - RESULTS AND DISCUSSION OF THE DEVELOPED ALGORITHM DOI : 10.1007/s11998-018-00178-y En ligne : https://link.springer.com/content/pdf/10.1007%2Fs11998-018-00178-y.pdf Format de la ressource électronique : Pdf Permalink : https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=32859 [article]

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