critique of: automatic and accurate extraction of road intersections from raster maps
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Vikram Reddy Donthi Reddy Toufong Vang CSCI 8715 September 20, 2011. Critique of: Automatic and Accurate Extraction of Road Intersections from Raster Maps. by Yao-Yi Chiang · Craig A. Knoblock · Cyrus Shahabi · Ching-Chien Chen. Problem Statement. - PowerPoint PPT PresentationTRANSCRIPT
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Critique of:Automatic and Accurate Extraction of Road
Intersections from Raster Mapsby Yao-Yi Chiang · Craig A. Knoblock · Cyrus Shahabi · Ching-Chien Chen
Vikram Reddy Donthi ReddyToufong VangCSCI 8715September 20, 2011
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Problem StatementDifficult to accurately and automatically extract road intersections from raster maps.
Significance of Research Spatial Data set for rasters does not
include or identify road intersections. (Road intersections are object-based models .)
These features may be used to combine or process spatial data sets.
Developed a framework for accurate and automatic separation of specific object-based models from raster.
Difficulty in Accomplishing Maps are complex. Computers have difficulty
distinguishing map features and elements from one another.
Current methods require user input/intervention to process.
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ContributionsMajor Contributions of the Research Developed method for automatically extracting road data.
95% precision. 75% completeness.
Researchers’ method does not require prior knowledge of the map.
Most significant? 95% accuracy + 75% completeness. Automatic extraction of map data.
Why? Rapid development and integration of
data where none may exist.
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Key Concepts
Chiang et al, 2009
Go from raster image of Tehran…(Google map.)
…to hybrid map.(Google map + Tourist map.)
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Key ConceptsThe Approach
1. Automatic Segmentation
Raster Map
2. Extract and rebuild road layer
3. Identify road intersections and extract.
Binary Map
Road Layer
Road Intersection Pts, connectivity, and orientation
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Key Concepts
Segmentation (remove background).
Researchers premise: foreground colors has high contrast to background colors.
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Key ConceptsPreprocessing (extract road layers a and b).
Rebuild road layer (c and d).
ID and extract road data (e).
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Validation Methodology
Related WorkUtilized related research and methods.
Segmentation process. Road extraction and rebuild.
Researchers’ Prior WorkLocalized template matching (LTM)
(compare experiment results with original raster)
The Experiment
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Validation Methodology
Verification of accuracy of process.Geometric Similarity(Lay term: how close is the extracted point from to the original point on the raster?)
Evaluation
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CritiqueResearch assumption
1) Road lines are straight within small distances.
2) Linear structures are mainly roads.
Falls apart when handling canals and other man-made non-road features.
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Revisions?Framework Straightforward. Solid.
Add… Process for handling artificial map features that are not necessarily roads (e.g.,
canals)