Volume 2, Issue 1

Range imaging has become a valuable technology for many kinds of applications in recent years. Numerous systematic deviations occur during the measurement process carried out by available systems. These systematics are partly excited by external and partly excited by internal influences. In this paper the following investigations will be presented in closer detail. First the statistics of the distance measurement of the analyzed range imaging cameras SwissRanger TM SR-2 and SR-3000 will be shown. Besides the question if the measurements are Gaussian distributed, the precision of the measurements will be shown. This aspect is of importance to answer the question if the mean value of a series of measurements leads to more precise data. Second diverse influencing parameters like the target's reflectivity and external as well as internal temperature are aimed. The dependency of the distance measurements with respect to the amplitude is one of the main aspects in this paper. A specialized set up has been developed in order to derive experimentally the detailed correlation, which is expressed in terms of linearity deviations. Besides the results of some specific aspects, an overview of the recommended calibration procedure is given. The reader of this paper will be enabled to understand the calibration steps needed to gain highly accurate data from the investigated range imaging cameras. Due to the fact that range imaging cameras are on their way to become state of the art in 3D capturing of the environment, it is of importance to develop strategies for the calibration of such sensors in order to enable users to revert to these principles for the sake of simplicity. Therefore, these strategies long for sophisticated approaches and reliable results of investigations. This paper will introduce such an approach to be discussed within the scientific and user environment. One of the main achievements of this work is the introduction of a method to significantly decrease the influence of temperature on the distance measurements by means of a differential measurement principle setup. The verification of the functionality is presented, as well.

Fingerprints are important biometric cues. Compared to conventional fingerprint sensors the use of contact-free stereoscopic image acquisition of the front-most finger segment has a set of advantages: Finger deformation is avoided, the entire relevant area for biometric use is covered, some technical aspects like sensor maintenance and cleaning are facilitated, and access to a three-dimensional reconstruction of the covered area is possible. We describe a photogrammetric workflow for nail-to-nail fingerprint reconstruction: A calibrated sensor setup with typically 5 cameras and dedicated illumination acquires adjacent stereo pairs. Using the silhouettes of the segmented finger a raw cylindrical model is generated. After preprocessing (shading correction, dust removal, lens distortion correction), each individual camera texture is projected onto the model. Image-to-image matching on these pseudo ortho images and dense 3D reconstruction obtains a textured cylindrical digital surface model with radial distances around the major axis and a grid size in the range of 25–50 µm. The model allows for objective fingerprint unwrapping and novel fingerprint matching algorithms since 3D relations between fingerprint features are available as additional cues. Moreover, covering the entire region with relevant fingerprint texture is particularly important for establishing a comprehensive forensic database. The workflow has been implemented in portable C and is ready for industrial exploitation. Further improvement issues are code optimization, unwrapping method, illumination strategy to avoid highlights and to improve the initial segmentation, and the comparison of the unwrapping result to conventional fingerprint acquisition technology.

The precise measurement of water surface models or profiles plays an important role in experimental hydromechanics. Conventional gauge-based techniques often come with a large instrumental effort and a limited spatial resolution. The paper shows an efficient non-contact photogrammetric technique for the measurement of water-surface profiles, which is based on an extension of the well-known laser light sheet projection technique. While the original laser lightsheet triangulation technique is limited to surfaces with diffuse reflection properties, the developed technique is capable of measuring on reflecting instationary surfaces. This article presents the basic principle, potential and limitations of the method. Several evolution steps of the system with different applicability and different complexity are shown. A double projection plane system capable of simultaneously measuring water surface height and tilt profiles marks the ceiling of the development. Besides the geometrical models of different levels of complexity, system calibration procedures are described. The applicability of the techniques and their accuracy potential are shown in several practical tests.

In this paper the application of knowledge-based systems for the analysis and evaluation of geodetic measurements is described. The first part gives a nontechnical overview over existing software products like GeoFit and current research activities (e.g. TUNCONSTRUCT, KASIP) with special focuses on tunneling and natural disaster management. The second part of the paper describes a case study from technical surveying in detail: the knowledge-based evaluation of the quality of free stationing on construction sites (e.g. tunnel sites). One main goal of the knowledge-based approach is to automate the time consuming daily process of manually checking lots of datasets by human experts. The paper shows the development of the knowledge-based system ranging from knowledge acquisition over knowledge analysis and representation up to the software prototype. A practical example is presented which indicates the capability of the system even to reproduce the often intuitive ratings of human experts.

A mapping system by vision-aided inertial navigation was developed for areas where GNSS signals are unreachable. In this framework, a methodology on the integration of vision and inertial sensors is presented, analysed and tested. The system employs the method of “SLAM: Simultaneous Localisation And Mapping” where the only external input available to the system at the beginning of the mapping mission is a number of features with known coordinates. SLAM is a term used in the robotics community to describe the problem of mapping the environment and at the same time using this map to determine the location of the mapping device. Differing from the robotics approach, the presented development stems from the frameworks of photogrammetry and kinematic geodesy that are merged in two filters that run in parallel: the Least-Squares Adjustment (LSA) for features coordinates determination and the Kalman filter (KF) for navigation correction. To test this approach, a mapping system-prototype comprising two CCD cameras and one Inertial Measurement Unit (IMU) is introduced. Conceptually, the outputs of the LSA photogrammetric resection are used as the external measurements for the KF that corrects the inertial navigation. The filtered position and orientation are subsequently employed in the photogrammetric intersection to map the surrounding features that are used as control points for the resection in the next epoch. We confirm empirically the dependency of navigation performance on the quality of the images and the number of tracked features, as well as on the geometry of the stereo-pair. Due to its autonomous nature, the SLAM's performance is further affected by the quality of IMU initialisation and the a-priory assumptions on error distribution. Using the example of the presented system we show that centimetre accuracy can be achieved in both navigation and mapping when the image geometry is optimal.

Positioning services based on GNSS Permanent Networks (PNs) disseminate the reference frame to users; hence the networks must be adjusted by constraining the ITRF coordinates of some permanent stations (PS), with the satellite orbits and clocks constrained to the values published by the International GNSS Service (IGS). Furthermore, the positioning service provider must use analysis methods, conventions and practices fully consistent with IGS standards. In this framework some problems arise. A first one is that long term solutions for the IGS PS coordinates are not always fully consistent with weekly IGS products, requiring an appropriate use of IGS PS weekly solutions. Moreover, the consistence of the reference frame implied by different positioning services must be checked, to avoid discontinuities between neighbouring networks. Clearly, in order to monitor the PS coordinates, the adjustment of a network needs to be performed on a quasi real time continuous (daily or weekly) basis. However, from a practical point of view, a continuous update of the PS coordinates is neither appropriate nor possible and alternative proposals will be presented. Finally, most users of real-time positioning services need coordinates in another reference frame, perhaps a local one or the national one. In this case the real-time service provider must distribute the transformation between the broadcasted frame and the user required reference frame. In this work some possible solutions of the aforementioned problems are presented, based on experiences obtained during data processing and adjustments of the Piemonte and Lombardia (Northern Italy) networks.