Full text: XVIIIth Congress (Part B5)

IMPLEMENTATION OF SEQUENTIAL ESTIMATION FOR SINGLE-SENSOR VISION METROLOGY 
Kenneth Edmundson and Clive S. Fraser 
Department of Geomatics 
University of Melbourne 
Parkville, Victoria 3052, Australia 
email: kle 9 sunburn.sli.unimelb.edu.au 
Clive Fraser 8 mac.unimelb.edu.au 
Commission V, Working Group 1 
KEYWORDS: Algorithms , On-line Triangulation, Precision, Sequential Estimation, Vision Metrology 
ABSTRACT 
Investigations into on-line triangulation, robot vision, image sequence analysis, and autonomous vehicle navigation 
have established the merits of sequential estimation methods in aerial and non-topographic photogrammetry utilising 
both film-based cameras and digital sensors. These merits generally focus on enhancement of the speed and 
efficiency of the triangulation procedure through the incorporation of quality control and observational error detection 
into the measurement procedure. The on-line quality control of industrial measurement with vision systems utilising a 
single sensor such as a CCD camera is a natural extension for sequential techniques. This paper examines how the 
sequential estimation process may be incorporated into single-sensor vision metrology for typical industrial 
photogrammetric inspection. Issues investigated in the context of the industrial application include the sequential 
nature of data collection and adjustment, the influence of normal equation structure on system response, generation of 
approximate values, additional parameters for systematic error compensation, blunder detection procedures, and 
datum establishment. 
With regard to datum establishment, a factorisation method for recursively updating the 
equation system obtained in a free-net adjustment by inner constraints is suggested. 
1.0 INTRODUCTION 
Multi-camera, stereo configurations have, up to now, 
been the focus of the bulk of the research effort in close- 
range vision metrology (VM). The recent commercial 
availability of large-area, high-resolution CCD cameras, 
coupled with the proven advantages of a single metric 
camera for high accuracy measurement, has heightened 
the potential for the single-sensor VM system in industrial 
inspection. The performance of industrial measurement 
tasks such as localised inspection, re-work, and fit 
checking is additionally enhanced through the use of VM 
systems containing an on-line link between the camera 
and an external computer. While real-time three 
dimensional measurements are not achievable with the 
single camera system, the near real-time image 
measurement capabilities associated with digital 
imagery, in combination with sequential estimation 
techniques such as on-line triangulation (OLT) can 
provide rapid data turnaround. 
The acceptance of CCD cameras for industrial 
photogrammetry continues at a pace which is 
constrained primarily by questions of accuracy related to 
the typically reduced format and resolution of CCD 
sensors as compared to medium and large format film- 
based metric cameras. Studies presented in Fraser & 
Shortis (1995) and Maas & Kersten (1994) have 
indicated that CCD and still video cameras such as the 
Kodak DCS200 (and DCS420) can yield acceptable 
accuracies for many industrial measurement tasks. One 
consequence of the lower resolution afforded by CCD 
sensors is that significantly more images may be 
necessary to achieve a precision comparable to a 
network obtained with a metric film camera. The 
potential of the VM system eases previous limitations in 
the number of images that may be readily processed and 
allows their incorporation into the network with minimal 
time expenditure. After an optimal convergent camera 
station network is in place, the use of multiple exposures 
is the principal means of improving object space 
precision. Here, OLT can serve as a mechanism for 
recursively monitoring object point accuracy. The 
photogrammetrist, while still on site, can interactively 
strengthen the network geometry until the desired level of 
accuracy is obtained. 
OLT methods have typically focused on the detection and 
removal of gross errors. By incorporating quality control 
and observational error detection into the measurement 
process, the speed and efficiency of the overall 
triangulation is enhanced. A comprehensive historical 
background of sequential estimation as applied to OLT 
can be found in Gruen (1985). Several recent studies 
apply these methods in non-topographic applications. 
These include robot vision (Gruen & Kersten, 1992), 
image sequence analysis (Kersten & Balfsavias, 1994), 
and autonomous vehicle navigation (Edmundson & 
Novak, 1992). The suggested application of sequential 
estimation in OLT to industrial quality control (Kersten et 
al, 1992) has for the most part remained unexamined. 
This paper, which builds upon work reported in 
Edmundson & Fraser (1995), explores the utilisation of 
sequential estimation for OLT in single-sensor vision 
metrology. We begin with a re-examination of the 
mathematics behind the general sequential estimation 
problem focusing on the computational algorithm, an 
orthogonal transformation technique known as Givens 
133 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part BS. Vienna 1996 
 
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.