Gamal Seedahmed
marks are registered onto the film by projecting an image of the mark through a small lens housed
inside the cone (Schenk, 1999). Since each fiducial is designed and projected separately, small
variations may occur.
Fiducial marks have typical patterns, made up of geometrical structures including straight-line
segments, crosses, solid squares and circles, and annulus, see Fig. (1). Most of the structures serve the
identification process and lend themselves as suitable candidates for a Hough Transform. The actual
fiducial center, whose coordinate is known from camera calibration, is a small disc, just slightly bigger
than the measuring mark of the analytical plotter (Schenk, 1999).
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Fiducial Image CAD Drawing of Fiducial
Fig. 1: A portion of a fiducial image and its CAD design provided by the manufacturer.
1.3 Overview of Automatic Interior Orientation
The automation of the interior orientation needs to concentrate primarily on recognizing and measuring
the fiducial marks. In general there are many different ways to automatically or semi-automatically
locate the fiducials on the digital images, such as manual identification or providing an approximate
position of the fiducial and then determine its center by using an automatic mensuration technique e. g.
mathematical morphology or fully automatic fiducial identification and mensuration (Lue, 1997).
Interior orientation in most existing softcopy workstations requires at least one or two fiducials to be
measured manually before the remaining fiducials can be automatically determined. In general, interior
orientation is approached as a template-matching problem augmented with least squares matching
(Lue, 1997) or with a modified Hough Transform for rough localization (Kersten and Haering, 1997).
Also interior orientation is solved via binary correlation with a hierarchical approach for rough
localization and gray level correlation for subpixel accuracy (Schickler and Poth, 1996).
In this study, we benefit from the fact that fiducial marks are artificial objects projected onto the film
during the exposure time. Based on this fact, the interior orientation problem is approached as a model-
based object recognition task utilizing most of the available prior knowledge regarding the fiducials, in
terms of providing the CAD design data, their shape, their location, the camera optics e. g. the
projection factor of the fiducials and the pixel size of the image. At the identification level the interior
orientation is solved as an object-recognition problem, and at the precise localization level it is solved
as an ordinary least-squares adjustment problem.
1.4 Objective of Autonomous Interior Orientation
A system is autonomous to the extent that its behavior is determined by its own experience. In the
context of this research and our view of digital photogrammetry we are going to use Schenk's (1999)
definition of autonomous “as if the process is really 100% automatic and does not require human
intervention- sort of a black-box- then the word autonomous can be used to describe the system”.
The objective of autonomous interior orientation can be summarized in the following points. The main
objective is the identification and approximate localization, subpixel localization of fiducial centers,
and computation of the transformation parameters between the pixel coordinate system and the photo
coordinate system. Identification includes the task of determining which of the fiducial marks is
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International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000.