Structured light is widely used for shape measurement of surfaces using the triangulation principle. To fulfill
this task, precise information about the optical path is necessary. We propose a novel method for the overall
calibration of a setup consisting of a structured light source, a projection screen and a camera. As computer
controlled video projectors become cheaper and cheaper, it is reasonable to use these off-the-shelf devices for
measurement applications. However, to achieve high accuracy with standard components, a precise calibration
of the measurement system is indispensable. Absolute position and orientation of the camera, the projector and
the projection screen has to be known. Furthermore, intrinsic calibration of both the camera and the projector
is necessary. After acquiring a large set of data points using a versatile phase encoding technique, we estimate
the optimal parameters using a bundle adjustment technique. We consider all extrinsic and intrinsic parameters
for the optical mapping including a distortion model for the projector and for the camera, respectively. We
propose a method which ensures complete knowledge about the optical mapping of each ray observed by the
camera. The proposed metric calibration method has also importance for other measurement applications as
e.g. shape reconstruction of specular surfaces. Hereby structured light patterns are projected on the screen, and
their reflection on the specular surface is observed by the camera.
Deflectometry has proven to be a very precise and reliable technique for the detection and measurement of bumps, dents, waviness and scratches on specular surfaces. Phase shifted fringe patterns are successively reflected at the surface and the spatial distortion of these reflected patterns is observed with a camera to extract information about the shape of the surface. Up to now, deflectometry could not be used for diffuse reflecting surfaces, because specular reflection does not occur. With the system developed at our institute it is now possible to inspect even diffuse reflecting surfaces like unpolished metal or plastics using the deflectometric measuring
principle. Hereby the fact is exploited that a surface becomes specular when the reflected light has sufficiently large wavelength compared to the surface roughness. For the diffuse surfaces
mentioned above the adequate range of the electromagnetic spectrum is far-infrared. In our approach a reflected infrared pattern is observed with a thermal camera. By analyzing four images of the
phase shifted pattern an image is calculated, which contains information about local surface curvature. The presented method has been successfully tested for the inspection of the diffuse
surfaces of unpainted car body parts.
Specular surfaces are used in a wide variety of industrial and consumer products like varnished or chrome plated parts of car bodies, dies, molds or optical components. Shape deviations of these products usually reduce their quality regarding visual appearance and/or technical performance. One reliable method to inspect such surfaces is deflectometry. It can be employed to obtain highly accurate values representing the local curvature of the surfaces. In a deflectometric measuring system, a series of illumination patterns is reflected at the specular surface and is observed by a camera. The distortions of the patterns in the acquired images contain information about the shape of the surface. This information is suited for the detection and measurement of surface defects like bumps, dents and waviness with depths in the range of a few microns. However, without additional information about the distances between the camera and each observed surface point, a shape reconstruction is only possible in some special cases. Therefore, the reconstruction approach described in this paper uses data observed from at least two different camera positions. The data obtained is used separately to estimate the local surface curvature for each camera position. From the curvature values, the epipolar geometry for the different camera positions is recovered. Matching the curvature values along the epipolar lines yields an estimate of the 3d position of the corresponding surface points. With this additional information, the deflectometric gradient data can be integrated to represent the surface topography.