Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Sensitivity of the Hough Transform for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method to Detect and Characterize Ellipses Using the Hough Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use of the Hough transformation to detect lines and curves in pictures
Communications of the ACM
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hypothesis Testing: A Framework for Analyzing and Optimizing Hough Transform Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Shape context and chamfer matching in cluttered scenes
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A hierarchical approach for fast and robust ellipse extraction
Pattern Recognition
Journal on Image and Video Processing - Special issue on advanced video-based surveillance
Edge curvature and convexity based ellipse detection method
Pattern Recognition
New hypothesis distinctiveness measure for better ellipse extraction
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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A new feature of curves pertaining to the acceptance/rejection decision in curve detection is proposed. The feature measures a curve's distinctiveness in its neighborhood, which is modeled by a one-parameter family of curves. A computational framework based on the Hough transform for extracting the distinctiveness feature is elaborated and examples of feature extractors for the circle and the ellipse are given. It is shown that the proposed feature can be extracted efficiently and is effective in separating signals from false positives. Experimental results with circle and ellipse testing that strongly support the efficiency and effectiveness claims are obtained. The results further demonstrate that the proposed feature exhibits good noise resiliency.