gao.ppt
TRANSCRIPT
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Bridge Extraction based on Constrained Delaunay Triangulation
Feng GaoLei Hu
Zhaofeng He
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Bridge Extraction
Panchromatic Image:High reolution provides detailed descriptions.
Challenge:Bridges are surrounded by complex backgrounds.
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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
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Bridge DetectionInput
Output
Approach:1.1. River SegmentationRiver Segmentation2.2. Bridge ExtractionBridge Extraction
Approach:1.1. River SegmentationRiver Segmentation2.2. Bridge ExtractionBridge Extraction
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• Extract water regionsRiver Segmentation
?Water/land segmentation
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• 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
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• Important characteristic of bridgeBridge Extraction
Intersection relationship with river flow
Morphological thinning operation+ Easy to implement− Computation time is too long
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• Extract Bridges along the medial axis of riverBridge Extraction
Constrained Delaunay Triangulation (CDT)
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• Extract Bridges along the medial axis of river
Bridge Extraction
River boundary CDT and medial axes
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• 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}
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Experiments
Extensive experiments are performed on high resolution image gathered from Google earth.However, swells and building shadows cause many false alarms.
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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.
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Acknowledgements
Special thanks to Shewchuk for providing the Triangle program
Special thanks to anonymous reviewers
Special thanks to session chair and audience
Thank you
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Q&A