Registration and integration of multiple laser scanned data for reverse engineering of complex 3D models

In reverse engineering or rapid prototyping of a complex 3D object, there is often a need to scan a complete 3D model using laser digitizers. However, most digitizers scan objects in a 2.5D way such that the multiple data sets need to be aligned and integrated. In this paper a surface registration algorithm is proposed to solve the problem using a nonlinear minimization approach. Multiple data sets with different orientations can thus be aligned and integrated to construct a complete 3D data set. To control the accuracy of the registration process, uncertainty analysis of the registration parameters is investigated. A registration uncertainty model is developed to predict the uncertainty of the registration process. Using this model, we can predict the minimum number of the scanned data points to satisfy the required registration accuracy.