Full text: CMRT09

In. Stilla U, Rottensteiner F, Paparoditis N (Eds) CMRT09. IAPRS, Vol. XXXVIII, Part 3/W4 — Paris, France, 3-4 September, 2009 
An extracted road border is assumed to be correct if the 
maximum distance between the extracted road border and its 
corresponding reference does not exceed the buffer width. 
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(a) 
(b) 
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H 
(c) (d) 
Figure 11. Capture of roundabout outline: (a) initial snakes in 
black and road arms in white, (b) and (c) evolving curves, and 
(d) reconstructed roundabout. 
Figure 12. Sample roundabout extraction results for scenes with 
varying degrees of complexity including disturbances. 
A smaller value of the buffer width can be chosen for an 
application that requires more accurate extraction results. A 
reference road border is assumed to be matched if the maximum 
deviation from the extracted object is within the buffer width. 
Based on these assumptions, three quality measures were 
adopted, the first being completeness, which is the ratio of the 
number of matched reference road borders to the number of 
reference objects. The second is correctness, which is the ratio 
of the number of correctly extracted road borders to the number 
of extracted objects, while the third is geometric accuracy, 
which is expressed by the average distance between the 
correctly extracted road border and the corresponding reference 
border, expressed as a Root Mean Square (RMS) value falling 
within the range of [0, buffer width]. 
Road border extraction results computed with different buffer 
width values are shown in Table 1. The completeness of the 
road border extraction increased as the buffer width value 
increased from 0.5m to 3m, implying that the results are more 
complete for higher buffer width values. The geometric 
accuracy increase is inversely proportional to buffer width so 
that results obtained with a value of 0.5m are more accurate 
than those obtained with a larger buffer width. For the buffer 
width value 0.5 m, the completeness is rather low. The reason is 
that a slight deviation of the extraction results from the true 
boundaries exceeding the buffer width frequently occurs due to 
disturbances and sometimes also due to road markings. 
Buffer width (m) 
0.5 
1 
2 
3 
Number of road borders 
41 
41 
41 
41 
Completeness 
53% 
62% 
74% 
85% 
Geometric accuracy (m) 
0.30 
0.38 
0.50 
0.58 
Table 1. Evaluation results for road borders. 
As seen in Table 2, a favourable evaluation result was achieved 
in the extraction of central islands, which proved the robustness 
of the proposed method. Central islands of roundabouts were 
extracted with high values for completeness and correctness for 
the buffer width of 0.5m, implying the effectiveness of the 
proposed hybrid evolution strategy. For the buffer width value 
1 m, all of central islands were extracted correctly. 
Buffer width (m) 
0.5 
1 
Number of central islands 
10 
10 
Completeness 
90% 
100% 
Correctness 
90% 
100% 
Geometric accuracy (m) 
0.26 
0.35 
Table 2. Evaluation results for central islands. 
5. CONCLUDING REMARKS 
A new snake-based approach to automatic extraction of road 
roundabouts has been described and analysed. Under the 
approach, the snake’s external force field is modified based on 
the shape of the central island to delineate the roundabout 
border. The modified snake force field can overcome various 
disturbances inside and outside the central island. It was shown 
that the use of prior-knowledge derived from an existing 
topographic database can considerably enhance the extraction 
performance. Furthermore, a level set approach with a hybrid 
evolution strategy was proposed to extract central islands. This 
produced good results in all 10 test cases, as central islands 
were extracted correctly for an assigned buffer width of lm. 
Nevertheless, partial occlusion of the central island border by 
large trees and shadowing cannot be overcome at this stage 
(Fig. 13). There are several possibilities to further enhance the 
results obtained so far and to be able to deal with more complex 
scenes. The incorporation of high-level prior knowledge about
	        
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