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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B5. Beijing 2008 
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scan have effected accuracy of computed orientation parameters. 
The method is useful when require tamsformation of laser scans. 
There are another kind of methods to compute transformation 
parameters and applay for adjacent overlap laser scans data 
related with survey instrument configuration, object surface and 
measurement area. Particularly, image based registration 
methods is used frequently (Dold and Brenner, 2006). To laser 
scanning while moving, the integration of the terrestrial laser 
and GPS/IMU sensors was done (Talaya, 2004). In this system, 
all the scanning data have been oriented correctly in reference 
frame directly. Independent model triangulation method is 
combined laser scanner data as similar method in aerial 
triangulation (Scaioni, 2002). In addition, there are too many 
different methods in literature for 3D modelling and combining 
of laser scanning data in reference coordinate system (Scaioni, 
2005; Zhi and Tang, 2002). 
In this study, combination of laser scanner data by one image 
was investigated. Image taken which cover adjacent laser scan 
area, and registration was performed by select point seen on the 
image and on the scans. This article has been organised form 
explain our work in section 2, experiments in section 3, 
conclusion and future work in section 4 and acknowledgement. 
2. OUR WORK 
In our work, it was investigated that registration of adjacent 
scans in common coordinate system by one image. The image 
has been taken form seen each adjacent scans. These scans have 
been registered by selected conjugate points on the scans and 
image. The steps of the our aproach are below; 
• The projection center coordinate and rotation angels 
of the taken image related with scan 1 (S1 ) and scan 2 
(S2) were calculated. 
• Rotation parameters are applied to the every scan (SI 
and S2). In this way, coordinate axes of the each scan 
are parallel for image cordinate axes. 
• Translation vector between the scans has calculated 
by differences projection center coordinates for the 
each scan. 
This steps were explained in subsections. 
2.1. Camera locate estimation 
Camera locate estimation is defined of determining the position 
of calibrated camera from 3D references points and their images 
(Figure 1). It is also called space resection in the 
photogrammetry community and computer vision. The most 
part of the problem is determine of distances from image 
projection center to object reference points. The solve of the 
problem has required least 3 conjugate points on object and 
image. With any two points of the three points, equation (1) can 
be writen in below; 
Pij (Xj, xj) = Xj Z + Xj z + CyXjXj — dij 2 = 0 ( 1 ) 
Cÿ = -2 cos Gy 
where, xi and xj is distance from i th and j th object points to 
image center, and they are not known. The other parameters in 
the equation is known. 0y is angle between i and j directions in 
the projection center C. dy is obtained with object coordinates 
of the points. 
For two pairs of the three points is writed three polynom as 
below, 
12 
t (xi, x 2 ) = xi 2 + x 2 2 + c, 2 x,x 2 - d, 2 2 
r 13 (Xj, X 3 ) = Xi 2 + x 3 2 + C 13 XjX 3 - d 13 2 
P23 (X 2 , X 3 ) = x 2 2 + x 3 2 + c 23 x 2 x 3 - d 23 2 
(2) 
These equations are singuler, and if Sylvester method is applied 
for eleminate x 3 and x 2 . Afterwards g x is hand related x^x; 
q x =a 4 x 4 +a 3 x 3 +a 2 x 2 +a t x 1 +a<)=0 
(3) 
This equation is solved singular value decompositon method 
(SVD) (Zhi and Tang, 2002). There are indefinities solving 
poblem by three points. There are not indefinities for four 
points. Three g x functions is obtained for four points and, SVD 
is applied by Maple software for these functions. After x h x 2 ,x 3 
and X4 was obtained, camera location (Xo,Y 0 ,Z 0 ) is calculated in 
object coordinate system. 
Image 
plane 
Figure 1. Image and object points. 
2.2. Rotation angels between image and laser scanner data 
Rotation angels between image and the each laser scanner data 
is calculated by collinearity equations (Equation 4). Number of 
the equation is selected point as much as the image and the each 
scans. 
X = X n -c 
y = y 0 -c 
r ii(X-X 0 ) +r 2 ,(Y-Y 0 )+r,,(Z-Z 0 ) 
r i3 (X - X 0 )+ r 23 (Y - Y 0 )+ r 33 (z - Z 0 ) 
r i2 (X ~ X 0 )+ r 22 (Y — Y 0 )+ r, 2 (Z - Z 0 ) (¿y 
r 13 (X-X„) +% (Y-Y 0 ) + r H (Z-Z 0 ) 
where; 
x,y : image point coordinates, 
x 0 ,y o : image pricipal point coordinates, 
c : focal lenght, 
r : elements of rotation matrix related 00,9,k. 
X,Y,Z: obeject system coordinates, 
X 0 ,Y 0 ,Z 0 : coordinates of the projection center in object system. 
The initial values of the unknowns (<B,(p,K,Xo,Y 0 ,Z 0 ) in the 
equation 4 is reguire. Initial values of the Xo,Y 0 ,Z 0 is accept 
projection center coordinates. Initial values of the rotation