EuroSDR Projects - Host Ireland

Appendix 4: General Characteristics of the Approaches
Chunsun Zhang
Key features: the approach extracts 3-D road network from stereo aerial images by integrating
knowledge processing of color image data and existing digital geo-database. It uses existing
knowledge, image context, rules and models to restrict search space, treat each road subclass
differently, check the plausibility of multiple possible hypotheses, and derive reliable criteria,
therefore provides reliable results
Strong points: 1. fusion of information from different cues 2. works directly in object space 3.
different classes of roads are treated using different features 4. multiple cues are used to create
redundancy to reduce the complexity of image processing, to account for errors, and to increase
success rate and the reliability of the results 5. junctions are generated and modeled 6. almost all the
roads in rural areas are correctly and reliably extracted
Weaknesses or limitations: the performance is poor in urban areas
Optimal exploitations in practical applications: the developed system will soon be used for 3-D
road production in rural areas.
Most important features for practical road extraction: completeness and reliability
Jason Hu
Key features: 1. multi resolution method is used 2. a fast and template matching based algorithm is
used - 3. hierarchical perceptual grouping approach
Strong points: before the grouping for segment linking, evaluating the saliency of the primitives and
using a sequential grouping method make it more reliable
Weaknesses or limitations: need to integrating more informations on complicated texture and
contextual for road extraction from dense urban area
Optimal exploitations in practical applications: it should be fused into a practical system
seamlessly. easy-to-use and flexible.
Most important features for practical road extraction: to meet the demands in accuracy,
robustness and interactivity so the efficiency. it should be integrated into a practical system (for
digitizing etc.)
Markus Gerke
Key features: Verification/Falsification of roads in a database (no generalized data) - Making use of
additional knowledge (context classes, attributes of roads)
Strong points: reliable results for rural areas -supports an operator: he/she has to focus attention just
on objects where the automated process did not find a road
Weaknesses or limitations: success of extraction algorithm in dense urban areas or in forest areas
depends on degree of occlusions -extraction of "new" roads reliable only in open landscape
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