3D measurement technique for rigid moving objects

What is it about?

When phase-shifting (PS) and temporal-phase-unwrapping algorithms are employed for three-dimensional (3D) shape measurement, the measured object must be kept static during the projection and acquisition. If the measured object is moving, deviation among multiple fringe images will inevitably occur, which results in the 3D measurement error. In this paper, a novel 3D measurement technique for rigid moving objects obtained by using the PS algorithm and the three-pitch heterodyne-unwrapping (TPHU) algorithm is proposed, which consists of six steps. First, the pixel offset is estimated based on a centroid deviation calculation. Second, the phase offsets among multiple fringes are calculated. Third, a novel set of fringes for the projection is generated. Fourth, we offset the captured fringe images according to the pixel offsets to generate a new set of captured fringe images for the phase calculation. Fifth, the wrapped phase is calculated by the PS algorithm. Finally, the unwrapped phase is calculated by the TPHU algorithm. The proposed method can be applied to the 3D shape reconstruction of a rigid movement object with a determined movement trajectory and constant movement speed. This approach not only greatly improves the measurement efficiency but also inherits the high accuracy and robustness of the PS and TPHU algorithms.

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Why is it important?

It is well known that the 3D measurement of a static object based on the PS and TPHU algorithms has good measurement accuracy and robustness, but it is difficult to realize the 3D measurement of a moving object. In this paper, a novel 3D measurement technique for rigid moving objects with a determined movement trajectory and constant movement speed is proposed. Although the proposed method requires the movement trajectory and movement speed of the object to be constant, the measurement accuracy of the moving object on the conveyor is close to that of the static object, and the measurement efficiency is greatly improved. Since the proposed method inherits the advantages of PS and TPHU algorithms, it shows promise for helping to develop a 3D shape measurement system for moving objects with high accuracy and robustness.