This paper discusses the possibility of evaluating the shape of a free-form object in comparison with its shape prescribed by a CAD model. Measurements are made based on a single-shot recording using dual-wavelength holography with a synthetic wavelength of 1.4 mm. Each hologram is numerically propagated to different focus planes and correlated. The result is a vector field of speckle displacements that is linearly dependent on the local distance between the measured surface and the focus plane. From these speckle displacements, a gradient field of the measured surface is extracted through a proportional relationship. The gradient field obtained from the measurement is then aligned to the shape of the CAD model using the iterative closest point (ICP) algorithm and regularization. Deviations between the measured shape and the CAD model are found from the phase difference field, giving a high precision shape evaluation. The phase differences and the CAD model are also used to find a representation of the measured shape. The standard deviation of the measured shape relative the CAD model varies between 7 and 19 μm, depending on the slope.

A concept for targetless, computer-aided design (CAD)-based, close-range photogrammetry for online shape inspection is introduced. The shape of an object, which is arbitrarily located on a conveyor belt, is to be measured and compared with its nominal shape as defined by a CAD model. For most manufactured objects, deviations are only measured at a few given comparison points. These deviations can be estimated using local photogrammetry based on a priori geometrical information given by the CAD model and the comparison points. Our method results in faster output with higher precision, because we do not generate a shape representation of the entire measured object using typical photogrammetric methods. Images depicting the object from convergent angles are captured by an array of cameras in a precalibrated network, and the CAD model is matched and aligned, within the projective geometry of the camera network, to the depicted object in the images without the use of targets. An algorithm for solving this virtual projective targetless shape matching problem is presented.

In automotive industry there is an interest of controlling the shape of a large number of identical components on-line in the manufacturing process. We propose a method to do this by capturing a digital hologram of the object and then using information from its computer aided design (CAD) model to calculate the shape and determine the agreement between the manufactured object and the CAD-model. The holographic recording of the object is done using dual wavelengths with a synthetic wavelength of approximately 400 μm. The optical measurement results in a wrapped phase map with the phase values in the interval [ − π, π]. Each phase interval represents a depth distance on the object of about 0.2 mm. The phase unwrapping is done iteratively using information from the CAD-model. This implies that it is possible to measure large discontinuities on the surface of the measured object. The method also gives a point-to-point correspondence between the measurement and the CAD-model which is vital for tolerance control.