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Title
International cooperation and technology transfer
Author
Mussio, Luigi

265
Table 3: Relative position errors of backprojected
control points in reference system S c .
rad + dec
rad-r ihm
rad2 + dec t- thin
mean Xc
1/15569
i/15547
1:11759
mean Y c
1/13202
1/13172
1/9403
std Xc
L22D32
1/21990
1/12542
std Y c
i/18518
1/18555
1/11295
As pointed out in tables 2 and 3, beside of performing a
calibration with less or more distortion parameters, one
should choose the camera mode! according to lower
backprojection errors, which are represented by (mean
Xw, meanY w ) and (std X w , std Y w ) or, equivalently, by
corresponding relative values computed in I c . while
(stdr, stdc) can give a feeling of superimposed noise.
CONCLUSIONS
Today, the camera calibration is becoming even more
an important issue in the digital photogrammetry field,
in the same time non-metric photocameras are widely
spreading on the market, due their relative low price
and improvement of image quality, that is sufficient for
image processing. In order to put in touch these two
fields, in the ambit of the Photogrammetry course we
have developed an alternative calibration method, in
which the Tsai-Lenz and Cohen-Hemiou algorithms
were properly revised. The procedure was then imple
mented as teaching software, in which a graphic inter
face helps the user for data input, evaluation of calibra
tion parameters results and assessement of Its accuracy.
The proposed algorithm is able to taken into account
various combinations of lens distortions, allowing the
user to choose the best distortion model according to
the application field and calibration requirements.
Fig. 5 : DATA window for calibration parameters input
ACKNOWLEDGEMENTS
This work was developed with the project “Digital
surface modeling by laser scanning and GPS for 3D
city models and digital orthophotos”. partly financed
by MURST (Italian Ministry- of University and
Research) in 1998 as a project of relevant national
interest. National coordinator: Riccardo Galetto, Head
of the research unit Antonio Vettore.
REFERENCES
[1] Canny JL, January' 1990. “A computational appro
ach to edge detection”. IEEE Transaction on FAME
vol 8, n° 6, pp 679-698.
[2] Faig W., December 1975. “Calibration of close-
range photogrammetric systems: Mathematical for
mulation”, Photogramme trie Eng. Remote Sensing,
vol 41, n° 12, pp 1479-1486.
[3] Tsai R.. August 1987. "A versatile camera cali
bration technique for high-accuracy 3D machine
vision metrology using off-the-self tv cameras and
lenses”, IEEE Journal of Robotics and
Automation, vol RA-3, n° 4. pp 323-344.
[4] Press H. W., Teukolsky S. A., Vetterling W. T..
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Recipes in C: The Art of Scientific Computing”,
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[5] Weng J., Cohen P., Hemiou M., October 1992.
“Camera calibration with distortion models and
accuracy evaluation”, IEEE Transaction on PA ML
vol 14, n° 10, pp965-980.
Fig. 6 : The PARAMETERS window showing the
calibration results.