Accurate 3D shape measurement of multiple separate objects with stereo vision

3D shape measurement has emerged as a very useful tool in numerous fields because of its wide and ever-increasing applications. In this paper, we present a passive, fast and accurate 3D shape measurement technique using stereo vision approach. The technique first employs a scale-invariant feature transform algorithm to detect point matches at a number of discrete locations despite the discontinuities in the images. Then an automated image registration algorithm is applied to find full-field point matches with subpixel accuracy. After that, the 3D shapes of the objects can be reconstructed according to the obtained point matching and the camera information. The proposed technique is capable of performing a full-field 3D shape measurement with high accuracy even in the presence of discontinuities and multiple separate regions. The validity is verified by experiments.