Fifteenth International Conference on Quality Control by Artificial Vision 2021
DOI: 10.1117/12.2589748
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Improved visual saliency estimation on manufactured surfaces using high-dynamic reflectance transformation imaging

Abstract: Reflectance Transformation Imaging (RTI) is a technique for estimating the surface local angular reflectance and characterizing the visual properties by varying lighting directions and capturing a set of stereo-photometric images. The proposed method, namely HD-RTI, is based on the coupling of RTI and HDR imaging techniques. The HD-RTI automatically optimizes the necessary exposure times for each angle of illumination by using the response of the scene. Our method is applied to industrial surfaces with micro-s… Show more

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Cited by 3 publications
(1 citation statement)
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“…The principle of this technique is illustrated in Figure 1, where PTM, HSH, and DMD are RTI reconstruction models and stand for Polynomial Texture Mappings, Hemispherical Harmonics, and Discrete Modal Decomposition, respectively. Many new RTI acquisition modalities have recently been developed, including multispectral approaches [34,35], approaches to measure the complete luminance dynamic (HD-RTI, [36][37][38]) self-adaptive approaches to determine the relevant lighting directions (NBLP-RTI, [39]), and even robot-based RTI systems [40]. Within the framework of this research, we focus on the RTI acquisition parameters associated with the conventional approach.…”
Section: Reflectance Transformation Imagingmentioning
confidence: 99%
“…The principle of this technique is illustrated in Figure 1, where PTM, HSH, and DMD are RTI reconstruction models and stand for Polynomial Texture Mappings, Hemispherical Harmonics, and Discrete Modal Decomposition, respectively. Many new RTI acquisition modalities have recently been developed, including multispectral approaches [34,35], approaches to measure the complete luminance dynamic (HD-RTI, [36][37][38]) self-adaptive approaches to determine the relevant lighting directions (NBLP-RTI, [39]), and even robot-based RTI systems [40]. Within the framework of this research, we focus on the RTI acquisition parameters associated with the conventional approach.…”
Section: Reflectance Transformation Imagingmentioning
confidence: 99%