Knowledge-Based Image Analysis for 3D Road Reconstruction
development. If the gap is not too long, and 1) within the gap is a road region, e.g. a parking lot right beside road, or 2) within the gap is a shadow, or shadow mixed with road region, or 3) the gap is caused by tree occlusion (determined with image classification result and the data of DSM minus DTM), or 4) within the gap is terrain as determined by the DSM, or 5) road marks are extracted within the gap, and the connecting angles between PRSPs and gap comply with VEC25, a link is made for the two PRSPs.
Figure.2 Procedures for road extraction.
A road hypothesis is found by searching the graph using the depth-first method. Each hypothesis is associated with a score that is the summation of the relation measurement of the PRSPs it contains. The hypothesis with the highest score is selected as road.
3. Results
The described system is implemented as a standalone software package with a graphic user interface running on SGI platforms. Fig.3 shows a road image in a rural area where the road is occluded by tree shadows. The extracted road centerline is shown in the same image in red. In Fig.4 we show the road extracted in a suburban area by the developed method. Fig. 5 is an
