The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
Original 
coordinate 
points 
Original 
watermark 
IWT 
■o- 
High 
frequence 
coefficients 
I IWT 
Low 
frequence 
coefficients 
Watermark 
Coordinate 
points with 
watermark 
Watermak 
embedding 
Low 
frequence 
coefficients 
Seed K 
pseudo-randan 
sequence 
Figure 3. The basic flow of embedding watermark 
2 THE CREATING AND PRE-PROCESSING OF 
WATERMARK 
In the paper, the meaning watermark is used. Figure 1 shows 
the watermark that is an image with 30><130 pixels which will 
be used as an experimental example in the paper. 
Copyright 
Figure 1 the watermark for experiment 
By scanning, the watermark can be represented as: 
M = {m(k)},k = 0,1, —,« — 1, m(k) = ±1. 
For enhancing the robustness, the algorithm shuffles the 
watermark before embedding. The pseudo-random sequence 
based on seed is generated as: 
P = {p(k)}>k = 0,1,-•*,« —1 ,p(k) = ±1 
The shuffling watermark can be got by bit XOR operation with 
M and P 
W = (w(A:) = m{k) © p{k)}, k = 0,1, • • •, n -1 
shown in Figure 3. 
The rule of embedding watermark is 
D[x\k)\ = D[x(&)] + p * w(k) k e [0, n -1] 
Where Z)[x(k)\ represents the low frequence coefficients of 
coordinates by integer wavelet transform, Yl is the number of 
bit for the embedded watermark, p is the intensity of 
embedded watermark and p = 2 in the paper. 
4 THE DETECTING ALGORITHM FOR VECTOR 
GEO SPATIAL DATA 
Detecting watermark is the inverse of embedding watermark in 
fact. By comparing the low frequence coefficients of the 
original data and detecting data, watermark W which is the 
shuffling watermark can be detected. Further, watermark 
M can be obtained by inverse shuffling. Finally, by 
autocorrelation detection, if the vector geo-spatial data have 
watermark can be judged. The basic flow of detecting 
watermark is shown as Figure 4 
On the comparison of low frequency coefficients, the rule is as 
follows. 
The shuffling watermark is shown in figure 2. 
Figure 2 the shuffling watermark 
3 THE EMBEDDING ALGORITHM FOR VECTOR 
GEO-SPATIAL DATA 
c(k) = D[ X< ,{k)]-D[x 0 (k)] 
w d (*) = 
c(k) > 0 
c(k) < 0 
Where X d (k) represents the coordinates need to be detected, 
X Q {k) represents the original coordinates, W d (A:) 
represents the detected coordinates. 
The integer wavelet transform can be for X coordinates, 
y coordinates or both of them (Here is for X coordinates). And 
the watermark is embedded into the low frequence coefficients 
of integer wavelet transform. Then the data with watermark is 
transformed by inverse integer wavelet. Finally the watermark 
is embedded in the original vector geo-spatial data. The basic 
flow of embedding watermark for vector geo-spatial data is 
The normalization correlation detection is used in detecting 
watermark for enhancing the robustness, and the rule is as 
follow: 
k=n-1 
^ m(k)*m'(k) 
n