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Automatic vision system for surface inspection and monitoring: Application to wheel inspection

Abstract : Visual inspection of finished products has always been one of the basic and most recognized applications of quality control in any industry. This inspection remains largely a manual process conducted by operators, and thus faces considerable limitations that make it unreliable. Therefore, it is necessary to automatize this inspection for better efficiency. The main goal of this thesis is to design an automatic visual inspection system for surface inspection and monitoring. The specific application of wheel inspection is considered to study the design and installation setup of the imaging system. Then, two inspection methods are developed: a defect detection method on product surface and a change-point detection method in the parameters of the non-stationary inspection process. Because in an industrial context it is necessary to control the false alarm rate, the two proposed methods are cast into the framework of hypothesis testing theory. A parametric approach is proposed to model the non-anomalous part of the observations. The model parameters are estimated to design a statistical test whose performances are analytically known. Finally, the impact of illumination degradation on the defect detection performance is studied in order to predict the maintenance needs of the imaging system. Numerical results on a large set of real images highlight the relevance of the proposed approach.
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Submitted on : Monday, May 28, 2018 - 4:58:12 PM
Last modification on : Monday, October 19, 2020 - 11:03:45 AM
Long-term archiving on: : Wednesday, August 29, 2018 - 3:24:42 PM


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  • HAL Id : tel-01801803, version 1




Karim Tout. Automatic vision system for surface inspection and monitoring: Application to wheel inspection. Signal and Image processing. Université de Technologie de Troyes - UTT, 2018. English. ⟨tel-01801803⟩



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