A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct least-squares fitting of algebraic surfaces
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVGIP: Image Understanding
Geometric Information Criterion for Model Selection
International Journal of Computer Vision
Computer Vision: A Unified, Biologically-Inspired Approach
Computer Vision: A Unified, Biologically-Inspired Approach
Grouping Based on Projective Geometry Constraints and Uncertainty
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Unified Curvature Definition for Regular, Polygonal, and Digital Planar Curves
International Journal of Computer Vision
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Estimation of a digital curve's curvature at any given point is needed for many tasks in computer vision, be it differential invariants or curvature scale space. However, curvature estimation is known to be very susceptible to noise on the contour. We shall show how noise on the contour affects the relative accuracy of the curvature computation. One interesting result is that, contrary to intuition, the accurate calculation of the curvature for low-curvature regions is in fact impossible for common image-sizes, while reasonable results may under favourable conditions be obtained for higher-curvature regions.