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Communication dans un congrès

High dynamic range reflectance transformation imaging: an adaptive multi-light approach for visual surface quality assessment

Abstract : Visual inspection of surfaces is a complex sensory process that depends on several factors related to the observer [1]-[3] (his knowledge, experience, tiredness or the purpose of observation), the object observed and the light environment. In order to reduce the subjectivity and to improve the robustness of the analysis of the appearance quality of the inspected surfaces, multi-lighting imaging techniques like RTI (Reflectance Transformation Imaging) are being used more and more. However, and to make the most of this technique, it is necessary to control the acquisition and processing, especially for highly reflective surfaces and / or having particular surface topographies. Thus, we propose an innovative implementation based on the RTI technique by increasing it with an acquisition and a processing in high dynamic range (HDR), adapted and adaptive. This coupling makes it possible to avoid the low dynamic range (LDR) of the cameras and therefore ensures a faithful estimate, for each pixel, of the angular component of the reflectance of the surface inspected, in particular in the case of non-Lambertian surfaces, and heterogeneous surfaces in terms of material and / or geometric texturing. Beyond appearance reconstruction, maps associated with geometric and statistical indicator maps (local slope/kurtosis/skewness/entropy) are used to show the relevance and performance of the proposed HDR-RTI methodology.
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Contributeur : IMVIA - université de Bourgogne Connectez-vous pour contacter le contributeur
Soumis le : vendredi 7 février 2020 - 16:47:53
Dernière modification le : mercredi 3 novembre 2021 - 07:46:50




Marvin Nurit, Castro yuly, Abir Zendagui, Gaëtan Le Goïc, Hugues Favreliere, et al.. High dynamic range reflectance transformation imaging: an adaptive multi-light approach for visual surface quality assessment. 14th International Conference on Quality Control by Artificial Vision, Univ Haute Alsace; Mulhouse Alsace Agglomerat; Region Grand Est; IDS GmbH; Fac Sci Mulhouse, May 2019, Mulhouse, France. pp.UNSP 1117213, ⟨10.1117/12.2521788⟩. ⟨hal-02471024⟩



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