7B-2-4 
Table 1. Performance of road segmentation 
Test 
No image pairs 
Successfully segmented road 
1. 
24 
100% 
2. 
64 
93% 
3. 
24 
96% 
Results presented in Table 1 shows that the segmentation 
algorithm presented (Section 2.2) works well. In most of the 
cases the road and the points on the road boundary are extracted 
correctly. Unfortunately, the measurement of road widths is 
inaccurate. The main reason of low accuracy is the presence of 
the errors in the parallax measurement. The errors in 
determination of the parallax are caused by: 
• Presence of multiple road boundary paintings e.g., 
highways. 
• Presence of cars, especially long vehicles 
• Bad visibility of the road width caused by cars parked 
on the roadsides. 
• Low respectively high saturation of the images. 
• Very strong shadows. 
• Perspective effect i.e. foreshortening, (Nalwa, 1993) 
3 DISCUSSION 
The practical test of automatic measurement was compared to the 
model based on classical errors propagation and to semi 
automatic measurements. The classical errors propagation model 
was based on simulation studies of MMS (Gajdamowicz, 1994). 
It was assumed that the positions of the camera was establish 
with double differential GPS method with position errorr Xo = 
oy 0 = crZo = 0.02 m. For the camera system the terrestrial 
photogrammetry model (normal case) was assumed. The cameras 
were situated 1.6 m from each other and 2 m above the road 
surface. The camera system was considered to point little 
downward with the pitch angle a> = -22^ (k, q> - 0^). The 
accuracy of angular measurements was considered to be 
a („= <J V - a K = 0®r. The road was assumed to be a planar 
surface (XY) with the Y-axis parallel to the direction of 
photography, the X-axis perpendicular to Y, and the Z-axis 
pointing up, and corresponding to heightAssuming no errors in 
the system the 12 m road width (in distance of 15 m from the 
cameras), can be measured with a precision oicrdT = 0.11 m. 
The precision of the road width measurement is proportional to 
the distance from the cameras and to the distance of the road 
boundaries from the road centreline (Fig 6). 
Figure 6. Theoretical precision of the stereo measurements (from 
Gajdamowicz, 1994) 
The road width was measured on more than 300 image pairs. 
From those images 112 were selected as representative ones 
(Table 1). The discrepancy values (e) were calculate (Eq. 3) 
e = measured value (Automatic) ~ 8 iven value (Semi Automatic) 
(3) 
Then, the accuracy of the method was determined by calculating 
the root mean square error (discrepancy).? (Hallert et.al, 1967). 
The s values in Test 1, Test 2 and Test 3 were 50.50 m, 64.02 
and 55.98 m respectively. Such huge errors are mainly due to 
gross errors i.e. high discrepancy values caused by incorrect 
parallax determination (Section 2.3). To estimate the accuracy of 
the algorithm for automatic road measurement some data pre 
processing is required, namely, rejection of outliers. To 
overcome the problem of outliers a simple rejection rule based on 
robust median and median deviation (rather than mean and 
standard deviation) was used. Such method is called “Hubber 
skipped means” and applies the following rule: Reject 
everything, which is more than 5.2 median deviations away from 
the median, and take the mean from the reminder (Hampeit al., 
1986). The median value was calculated from absolute values of 
discrepancy (e). 
Let us closely analyse the test 2 in Table 1, (Figure 7). In a set of 
64 measurements one can easily notice extreme outliers that 
reach from 20 m up to 380 m. Because of such errors the 
discrepancy respectively root square errors are always very large. 
The results of measurement in 55 stereo pairs were analysed 
(Figure 7). The semi-automatic method was considered as a 
reference. The total amount of outliers in the set of 55 
measurements was 32%. After rejection of outliers the average 
road width measured automatically was 8.18 ra&dA = 0.83 m 
where semi-automatic method resulted in an average road width 
of 8.36 m, (JdSA ~ 0-29 m. 
In comparison with the theoretical valuecr £ /7' = 0.11 m, the 
precision of the automatic and semiautomatic measurement is 
much lower. In case of the automatic method the main reason for 
low precision is because of errors in the matching procedure. 
Even if least square matching was used, computation of