Full text: New perspectives to save cultural heritage

Merging and processing of laser scan data and high-resolution 
digital images acquired with a hybrid 3D laser sensor 
Johannes RIEGL, Nikolaus STUDNICKA, Andreas ULLRICH 
Key Words: RIEGL, laser scanning, photogrammetry, 3D laser scanner, calibrated digital camera, RiSCAN PRO 
We present a hybrid sensor consisting of a high-performance 3D imaging laser sensor and a high-resolution digital 
camera. We demonstrate the performance capabilities of the system by presenting an example and we describe the 
software package used for data acquisition, data merging and visualisation, RiSCAN PRO. Addressing the camera model 
and the data structure provides an insight into the well-organized, published and well-documented project format used by 
1 Introduction 
RIEGL Laser Measurement Systems GmbH is well 
known for developing, manufacturing, and marketing 
state-of-the-art 3D imaging laser sensors based on the 
time-of-flight measurement technique with near- 
infrared pulses. The sensors are unique with respect to 
the outstanding combination of high measurement 
accuracy, a very wide field-of-view, a wide 
measurement range, high data acquisition speed, and 
proven robustness and compactness. 
Recently, RIEGL started to offer the 3D imaging laser 
sensors with an optional high-resolution digital camera 
firmly mounted to the scanner. The camera used is 
calibrated and the orientation of the camera is known 
with respect to the sensor’s coordinate system. By 
taking a number of images, the whole wide field-of- 
view of the scanner of up to 90 x 360 deg can be 
covered. The combination of high-resolution calibrated 
and registered images and high-quality scan data 
provides a clearly improved usefulness of the acquired 
data by combining the advantages of laser scanning 
and photogrammetry. 
We describe in the subsequent sections our companion 
software package RiSCAN PRO. The data structure 
used by RiSCAN PRO to store all data is published in 
order to allow software developers to make full use of 
the data acquired and processed with RiSCAN PRO, 
e.g., in PHIDIAS from PHOCAD (PHOCAD 2003). 
We address the calibration tasks necessary to make use 
of the digital images in combination of the scan data. 
The capabilities of RiSCAN PRO and the RIEGL 
LMS-Z360 instrument with the camera option are 
demonstrated by an example. 
2 Software Package RiSCAN PRO 
RiSCAN PRO is the companion software package to 
the RIEGL 3D laser imaging sensors of the RIEGL 
LMS-Z series. RiSCAN PRO supports also the 
instrument with the camera option. It allows the 
operator of the 3D imaging sensor to perform a large 
number of tasks including sensor configuration, data 
acquisition, data visualization, data manipulation, and 
data archiving. 
RiSCAN PRO is project oriented. A project is stored 
within a single directory structure containing all scan 
data, registration information, additional descriptors, 
and processing outputs. RiSCAN PRO reflects thus a 
data acquisition campaign in the field. The structure of 
the project is stored in a text based and documented 
project file naking use of the XML format enabling 
post-processing software packages to make full use of 
the RiSCAN PRO data. Within RiSCAN PRO all data 
are organized in a tree structure for comfortable access 
and clarity. In the subsequent subsection we describe 
the key elements of the tree structure and address some 
background information useful for understanding data 
handling and data interpretation. 
RiSCAN PRO makes use of the following different 
coordinate systems: 
Scanner’s Own Coordinate System (SOCS) is the 
coordinate system in which the scanner delivers it’s 
raw data. Figure 1 shows the coordinate system of an 
LMS-Z210. The data of every RIEGL 3D laser 
imaging sensor contains for every laser measurement 
geometry information (Cartesian x, y, z coordinates or 
polar r, 0,4> coordinates) and additional descriptors (at 
least intensity, optionally color information). Thus the 
output of a RIEGL 3D laser imaging sensor can be 
addressed as an organized point cloud with additional 
vertex descriptors in the scanner’s own coordinate 

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