ISPRS, Vol.34, Part 2W2, ‘‘Dynamic and Multi-Dimensional GIS”, Bangkok, May 23-25, 2001 
241 
Road Sign Recognition is a field of applied computer vision 
research concerned with the automatic detection and 
classification of traffic signs acquired from a moving car. Many 
researches have been developed since 1984 in Japan but almost 
Road sign recognition systems exist in developed countries. 
Complicated, expensive systems such as feature extraction from 
occluded images based in colors (Kentarnavaz, Estevez, 1994, 
USA), color based signs finder for highways (Frank, Haag, Lee 
Gang, Taiwan) etc have been developed but a simple, cheap 
algorithm that is suitable for developing countries has not been 
developed yet. 
In Thailand, there is no research on road sign recognition 
although “road accident’s account for the road is the highest 
deaths of people annually” (National Statistical Office, 1998). 
Moreover the development of highways systems changes rapidly 
in each year. This reason makes the road database and road 
map fast out-of-date. Thus the Mobile Mapping System and 
Road Sign Recognition System that are not complicated, and 
low-cost should be considered. 
In AIT, some parts of the mobile mapping have been developed. 
Improvement of the accuracy for RTK-GPS (Dinesh, 1998) and 
Measurement the center line of road (Ganesh, 1999) are the 
development of the position sensor, one part of mobile mapping 
but another part, road sign image recognition, that is important 
equally, has not been done. 
Therefore, the purpose of this study is to develop the new simple 
algorithm of the Thai Road Sign Recognition and Road Sing 
Positioning. The algorithm is descried in the next section. 
2 Sign Recognition 
For this section, the study was separated to two steps: Sign 
detection and Sign identification. 
Sign Detection 
The first step in the recognition of the sign is to identify the region 
of Interest or sign shape. This step is the semi-automated 
detection applied by affine geometric correction below: 
The affine transformation is applied to solve both rotated and 
scaling distortion of image due to the 3Dimension to 2Dimension 
projection of a camera by formulae below 
x' = ax + by 
y' = dx + ey - 
(1) 
Figure 3 the procedure of transformation 
Where 
x, y is the coordinate of old system. 
x\ y' is the coordinate of new system. 
a, b, c, d, e, f are the parameter solved by using the least square 
method below: 
B = Ax -> x = (A T .A)' 1 .A T .B (2) 
x'i~ 
*1 
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1 
0 
0 
0' 
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0 
0 
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yl 
1 
x' 2 
*2 
y 2 
1 
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y r 2 
A = 
0 
0 
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*2 
y 2 
1 
*3 
*3 
1 
0 
0 
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y'l 
0 
0 
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*3 
-V 3 
1 
x 'r 
[ 
*4 
J4 
1 
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J 4_ 
0 
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1