Fast and robust online three-dimensional measurement based on feature correspondence

Abstract

Online three-dimensional (3D) measurement plays an important role in industry. When phase-shifting profilometry is employed in online 3D measurement, pixel matching is an important step to keep objects at the same coordinate value. However, the correlation operation and marker feature matching algorithms may take a long time, increasing the complexity. So a fast and robust online 3D measurement based on feature correspondence is proposed. In this method, only one frame of the sinusoidal fringe pattern is projected onto the measured object, and image correction technique is employed to rectify pixel size. Then five frames of deformed patterns with equivalent displacement are captured by the camera, and the corresponding modulation patterns are extracted. The oriented fast and rotated brief feature algorithm is used to extract the matching pair of feature points, and the improved grid-based motion statistical feature algorithm can better eliminate the false match to achieve pixel matching. In this way, five frames of deformed patterns with an equivalent shifted-phase can be extracted. Finally, the 3D shape of the measured object is reconstructed by the five-step equivalent phase-shifting algorithm. Experimental results verify the effectiveness and feasibility of the proposed method.