EXTENDED GAUSSIAN IMAGES FOR THE REGISTRATION OF TERRESTRIAL SCAN DATA

Abstract

Terrestrial laser scanning instruments are coming more and more into operation. Up to now vendors of laser scanners mainly use manual or semi-automated registration techniques combined with artificial targets to register single scans. The automatic matching of multiple scans without additional targets is still a research topic in the field of terrestrial laser scanning. Many different proposals and algorithms have already been presented to solve this task. Nevertheless, a strong demand remains for fast and robust algorithms for the registration of multiple scans. The problem is difficult to solve and the process is often divided into two stages. First a coarse matching is done in order to determine a pre-alignment of the scanned surfaces. Then a fine matching algorithm is used to achieve more accurate results. Robust algorithms like the well known iterative closest point (ICP) algorithm and lots of variants already exist for the fine matching, whereas the existing methods for the pre-alignment of the scan data are often rudimental and limited. In this paper a proposal for automatic registration of terrestrial laser scanning data using extended Gaussian images is introduced. The method is placed in the coarse matching stage of the registration process and can be used to determine the rotation component between different scan positions. Therefore normal vectors of local or segmented planes of the input data are used.