A phase reconstruction method using frequency-shifting is proposed. The frequency-shifting method is
developed based on the properties of trigonometric functions. The computer simulation and the
experimental result are also presented to demonstrate the feasibility and validity of the proposed
approach in phase reconstruction.
It is usually difficult to calibrate the 3-D vision inspection system that may be employed to measure the large-scale
engineering objects. One of the challenges is how to in-situ build-up a large and precise calibration target. In this paper,
we present a calibration target reconstruction strategy to solve such a problem. First, we choose one of the engineering
objects to be inspected as a calibration target, on which we paste coded marks on the object surface. Next, we locate and
decode marks to get homologous points. From multiple camera images, the fundamental matrix between adjacent images
can be estimated, and then the essential matrix can be derived with priori known camera intrinsic parameters and
decomposed to obtain camera extrinsic parameters. Finally, we are able to obtain the initial 3D coordinates with
binocular stereo vision reconstruction, and then optimize them with the bundle adjustment by considering the lens
distortions, leading to a high-precision calibration target. This reconstruction strategy has been applied to the inspection
of an industrial project, from which the proposed method is successfully validated.
Texture blending is an important technique for generating a photorealistic appearance of a physical model or scene. In
this paper, we present an efficient texture blending algorithm that can be utilized to register and merge multiple
texture-mapped range images of physical objects acquired from different view points, resulting in a 3-D photorealistic
model. The technique details with respect to the proposed algorithm are described and verified by experiment results.