Pre-classification of points and segmentation of urban objects by scan line analysis of airborne LIDAR data

Currently available laser scanners are capable of performing hundreds of thousands of range measurements per second at a range resolution of a few centimeters. Despite that increasing performance, up to now airborne LiDAR mapping has established itself only in fields of application that do not require on-line data processing. A typical example in this context is urban modeling. We want to point out some other tasks like object recognition, situation analysis and on-line change detection that have come into reach of today's LiDAR technology. Primary goal of the work presented in this paper is the on-line data preparation for subsequent analysis. We present a workflow of real-time capable filter operations to detect the ground level and distinguish between clutter and manmade objects in airborne laser scanner data of urban regions. Based on interpretation of single scan lines, straight line segments are first segmented and then connected, and the resulting surfaces are delineated by a polygon. A preliminary step is done towards fast reconstruction of buildings for rapid city-modeling, co-registration or recognition of urban structures.