Registration And Integration Methods Of Multiple Range Images

Reconstruction of 3-D objects is an important research problem of computer vision, which have been applied in many domains such as Virtual Reality, CAD reverse engineering, Pattern Recognition, ill product detection, and non-contact measurement of 3D human body. In the paper, the problem of registration and integration of multiple range images is addressed. Multiple range images can be obtained by turning the 3D object at different angles around sensor. The range images of different viewpoints are registered to estimate the relative transformations among the viewpoints, and then integrated to obtain a complete 3D geometric description of object.First, we introduce the principal of three-dimensional sensors and our data collecting system, and analyze two kinds of data errors in the range images. Next we propose a novel matching triangles registration algorithm. In some representative algorithms for the registration of multiple range images, the range image is only considered as a 3D point set. The motion parameters are estimated by matching the closest point in other range image. Their main drawback is the registration process doesn't make full use of the information of range images. So our algorithm defines cost function is the mean distance of two triangle meshes. By an imaginary uniform sampling on the original triangle mesh, our algorithm makes the 3D point set using in ICP algorithm not only approximatively uniformly distribute in the measured object surface, but also possess of more information of the object surface than classical ICP algorithm. The experimental results show the proposed registration method is computationally efficient and robust to outliers and initial motion parameters.Last we propose an algorithm for integration of multiple range images, which improves the zippered algorithm by inspecting the connectivity of the original triangle mesh after the procedure of removing redundant surfaces. Moreover we carefully consider all possibility of the gap of two original triangle meshes after the procedure of removing redundant surfaces, and then propose corresponding methods to deal with all these possibility. Experiments demonstrate that the method can satisfy the requirements of computing cost and accuracy of object model reconstruction.Our registration and integration methods provide an easy way to fastautomatically digitize 3D object model.Xie Feng (Pattern Recognition and Image Processing)supervised by Prof. Zhang Hongbin.