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PROCEDURES OF CORRECTION OF THE GEOMETRY DISTORSIONS
FOR DIGITAL IMAGES
A. Guamieri, A. Vettore
Dip. Territorio TESAF - Università’ di Padova - Italy
AGRIPOLIS - Statale Romea 16
35020 Legnaro (Padova)
Phone +39-049-8275580, fax +39-049-8372713
e-mail: vettoan@ux 1 .unipd.it
Commission VI, Working Group 3
ABSTRACT
Since a few years digital fotocameras have widely spread on the market, principally because of their price, quality
image improvement and easy of use. In order to extract from these digital images reliable 3D informations regarding
objects position and dimension, both the exact knowledge about perspective and dimensional relations between image
and scene, and the knowledge about the geometric distortions parameters are needed.
Therefore, the aim of this work was to develope, in the ambit of the Photogrammetry course, an alternative calibration
method and to implement it as teaching software, by which the parameters of the major forms of geometric distortions,
i.e. radial, decentering and thin-prism, can be estimated. Basically, the proposed method was realized putting together
the Tsai-Lenz and Weng-Cohen-Hemiou calibration algorithms and applying the Levenberg-Marquardt algorithm as
non linear optimization procedure. The software was developed in Matlab programming language, because its code can
be to structured in text-like scripts, allowing therefore to share and to understand a program in easier way compared to
software written, fo instance, in Fortran or C.
The method has been implemented in such a way to allow a full camera calibration or a computation of the exterior
orientation parameters only, using inner orientation and distortion parameters determined from previous full calibration.
This approach can be useful if only an estimate of new targets positions is required, in which the inner and distortion
parameters are already given.
1. INTRODUCTION
The camera calibration, typical issue in computer
vision, is becoming today very important also in digital
photogrammetry applications, where dimensional mea
surements are required. The main aspect of camera ca
libration is concerned with the estimate of internal
parameters of the camera, that define the perspective
and dimensional relations between 3D points in the
scene and corresponding image coordinates. Another
important aspect of calibration regards the determi
nation of geometrical relations between camera and
scene through estimate of external parameters, and the
correction of geometrical lens distortions.
On the other hand, digital non-metric fotocameras are
widely spreading on the market since a few years,
principally because of their price, quality image impro
vement and easy of use. At the present the image
quality of amateur digital cameras is surely not at the
same level of film cameras in terms of resolution (300
dpi vs 2500 dpi with a 35mm film), image dimension
(640 x 480 pixels), colours spectrum (24 bits, rather
than continous) and limited dynamic range of the CCD,
in lights and shadows capturing. As rule of thumb,
increasing the dimension and the number of CCD cells
the image quality is improved, but the final price is
augmented as well. Despite the exposed drawbacks, the
easy and quickly download of images on a computer
and the perspective of improvements in image quality
lead to a reasonable scenario in next future, where digi
tal cameras will substitute the film ones in the most
common applications.
On the ground of these considerations, we have deve
loped an alternative calibration method of digital non
metric camera, in order to employ this kind of relative
expensive device in digital photogrammetry applica
tions.
Following the classification presented in [4], we can
identify three main groups for the existing camera cali
bration techniques:
1) Direct Nonlinear Minimization: in this category
the parameters estimation involves using an itera
tive algorithm, which tries to minimize residual
errors of some equations. The adopted camera
model can be very general, to cover many kind of
distortions, but it requires a good initial guess of
the parameters because the procedure is iterative.
Furthermore including the estimate of lens distor
tions, the procedure may be unstable, the correla
tion between external and distortions parameters
can lead to divergence or false solutions.
