Abstract
Fringe projection profilometry (FPP) is a popular technique for measuring three-dimensional (3D) objects and is widely used in industrial production, quality detection, and visual guidance, among other applications. However, with traditional FPP systems based on triangulation, significant changes in the surface height of the measured object can lead to occlusion and shadowing in measured scenes. To deal with this problem, a multidistance constraint (MDC) approach based on a coaxial fringe projection system is developed here. This proposed method changes the position of the projector multiple times to increase the number of geometric constraints, and every pixel on the imaging plane of the camera can then obtain more phase information from different-frequency patterns. By constructing a model of the geometric relationship between the phase and the 3D coordinates of object, depth information can be obtained by a least-squares algorithm. Experiments confirm that the MDC method can effectively recover 3D shapes of objects with stepped heights and deep holes while avoiding shadowing.
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