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Transcript of gao.ppt
Bridge Extraction based on Constrained Delaunay Triangulation
Feng GaoLei Hu
Zhaofeng He
Bridge Extraction
Panchromatic Image:High reolution provides detailed descriptions.
Challenge:Bridges are surrounded by complex backgrounds.
Textual and geometric information [R. Trias-Sanz04]+ Effective for small high-resolution images− Computation of texutre parameters takes a significant amount of time
Boolean and/or logical low-level operator [D. Chaudhuri08] + Effective for small bridges− Not appropriate for high-resolution images
Related Work
Bridge DetectionInput
Output
Approach:1.1. River SegmentationRiver Segmentation2.2. Bridge ExtractionBridge Extraction
Approach:1.1. River SegmentationRiver Segmentation2.2. Bridge ExtractionBridge Extraction
• Extract water regionsRiver Segmentation
?Water/land segmentation
• Extract water regions based on texture analysis. (MRF model)
River Segmentation
Our Approach:1.1. Calculate textural parametersCalculate textural parameters2.2. ICM algorithm to estimate the MAPICM algorithm to estimate the MAP3.3. Remove noisy regionsRemove noisy regions
Our Approach:1.1. Calculate textural parametersCalculate textural parameters2.2. ICM algorithm to estimate the MAPICM algorithm to estimate the MAP3.3. Remove noisy regionsRemove noisy regions
Original Im
age
Results
• Important characteristic of bridgeBridge Extraction
Intersection relationship with river flow
Morphological thinning operation+ Easy to implement− Computation time is too long
• Extract Bridges along the medial axis of riverBridge Extraction
Constrained Delaunay Triangulation (CDT)
• Extract Bridges along the medial axis of river
Bridge Extraction
River boundary CDT and medial axes
• Extract Bridges along the medial axis of riverBridge Extraction
Radon transform is used here to avlidate ROI
if parallel lines are detected{ ROI is real bridge region}Else{ ROI should be neglected}
Experiments
Extensive experiments are performed on high resolution image gathered from Google earth.However, swells and building shadows cause many false alarms.
Future work
River segmentation procedure will be refined to avoid the influence of swells in river and building shadows.
Better vectorization algorithms to make the skeletal description more accurate.
Acknowledgements
Special thanks to Shewchuk for providing the Triangle program
Special thanks to anonymous reviewers
Special thanks to session chair and audience
Thank you
Q&A