Large-scale three-dimensional object measurement: a practical coordinate mapping and image data-patching method

In a practical three-dimensional (3-D) sensing system, the measurement of a large-scale object cannot be completed in only one operation. A relieflike object is generally divided into several subregions, an optical sensor positioned at each of these locations, and the shape of the whole object obtained by patching together all the 3-D data of the subregions. It is important to have accurate 3-D coordinates (x, y, z) for each subregion. We propose a new phase-to-height mapping algorithm and an accurate lateral coordinate calibration method with which to obtain the 3-D coordinates. After all the subregions are measured, it is necessary to transform the local coordinates into global world coordinates; here we present a new image data-patching method based on a flood algorithm. This method provides the optimal path along which to patch all the subregions into the shape of the entire object. We have measured and successfully patched a large sandy pool (9 m x 5 m), and the reliability and feasibility of our method have been demonstrated by experiment.