International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004
Table 3. Root mean square error of both automatically
and manually
Automatically
Int. orient. Manually
r.m.s.e int.orient.
Image No (pixel) r.m.s.e(pixel)
9061 0.37 0.22
9062 0.37 0.25
9063 0.37 0.33
9064 0.71 0.35
9065 0.46 0.22
9066 0.81 0.25
9067 0.73 0.35
9068 0.46 0.26
9069 0.06 0.28
9070 0.89 0.35
5. CONCLUSIONS
In this study, we showed that the positions of fiducial marks
were found using cross correlation method, which is one of the
area based matching techniques. Transformation parameters are
obtained from two different coordinates of fiducial marks that
are pixel coordinate system and image coordinate system at the
end of the fiducial mark searching process. The value of the
root mean square error of the affine transformation is used as a
confirmation criterion for the accuracy. The values of the root
mean square error of the affine transformation are 0.06 to 0.89
pixel. Furthermore, manually the values of the root mean
square error of the affine transformation are 0.22 to 0.35 pixel.
The root mean square errors derived using cross correlation are
bigger than the root mean square error derived by human
operator (approximately twice the other values).
The reliability of the algorithm depends on mainly on the
radiometric and geometric quality of the digitised images.
ACKNOWLEDGEMENTS
This paper is partly based on Ph.D. thesis carried out by H.
Karabork and prepared in Selcuk University.
6. REFERENCES
Heipke®, C., 1996, Automation of Interior, Relative, and
Absolute ^ Orientation, International Archives
Photogrammetry and Remote Sensing (31) B3, p 297-311
Heipke®, C., 1996. Overview of Image Matching Techniques,
OEEPE Official Publication
Karabork, 2002, Digital Fotogrametride Manuel ve Yari
Otomatik Yóntemlerin Degerlendirme Dogruluguna Etkisi
Uzerine Bir Arastirma, Ph.D. Thesis, , Selcuk University, 143
page, Konya
Lang, F. and Fórstner, W., 1998, Matching Techniques, Third
Course in Digital Photogrammetry, Chapter 5, 41 page, Bonn
Lue, Y., 1997. One Step to A Higher Level of Automation for
Softcopy Photogrammetry Automatic Interior Orientation,
of
814
ISPRS Journal of Photogrammetry & Remote Sensing 52
(1997) 103-109
Schenk, T. , 2000. Object Recognition in Digital
Photogrammetry, Photogrammetric Record, 16(95): 743-762
Seedahmed, G., Schenk, T. 2000, Model-Based Autonomous
Interior Orientation, International Archives of Photogrammetry
and Remote Sensing, Vol XXXIII, Part B3, Amsterdam