3D DIGITIZATION OF TRANSPARENT AND GLASS SURFACES: STATE OF THE ART AND ANALYSIS OF SOME METHODS
Keywords: Photogrammetry, Shape from X, 3D reconstruction, Transparent objects, Machine learning, Inspections
Abstract. In the field of industrial metrology, there is a rising need for 3D information at a very high resolution for micro-measurements and quality control of transparent objects such as glass bottles (beer, wine, cola, cosmetics, etc.). However, such objects are particularly challenging for optical-based 3D reconstruction methods and systems such as photogrammetry, photometric stereo, structured light scanning, laser scanning, typically resulting in poor metrological performances. Indeed, these methods require the surface of the object to diffusely reflect the incoming light, which is not the case with the glass material where refraction and absorption phenomena do not permit their use. Over the years, various methods have been investigated and developed to avoid the coating (or powdering) treatment often used to make transparent objects opaque and diffusely reflecting. Most of the approaches require either some a priori knowledge of the transparent object or assumptions about how light interacts with the surface. This paper provides a general overview of state-of-the-art 3D digitization methods for optically non-cooperative surfaces featuring absorption, scattering, and refraction. The paper reviews research works summarizing them into four categories including shape-from-X, direct ray measurements, hybrid, and learning-based approaches. Moreover, we provided some 3D results to better highlight the advantages and disadvantages of each method in practice when dealing with transparent objects.