A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A comparative study of different corner detection methods
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Junction and corner detection through the extraction and analysis of line segments
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Image corner detection using hough transform
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
The monogenic curvature scale-space
IWCIA'06 Proceedings of the 11th international conference on Combinatorial Image Analysis
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This paper describes a new method for image corner detection based on the curvature scale space (CSS) representation. The first step is to extract edges from the original image using a Canny detector. The corner points of an image are defined as points where image edges have their maxima of absolute curvature. The corner points are detected at a high scale of the CSS image and the locations are tracked through multiple lower scales to improve localization. The CSS corner detector is very robust to noise and performed better than three other detectors it was compared to.