Document degradation models and a methodology for degradation model validation
Document degradation models and a methodology for degradation model validation
Discrete Curvature Based on Osculating Circle Estimation
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Optimal Time Computation of the Tangent of a Discrete Curve: Application to the Curvature
DCGI '99 Proceedings of the 8th International Conference on Discrete Geometry for Computer Imagery
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Optimal blurred segments decomposition of noisy shapes in linear time
Computers and Graphics
Curvature estimation in noisy curves
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Robust estimation of curvature along digital contours with global optimization
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
Binomial convolutions and derivatives estimation from noisy discretizations
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
An elementary algorithm for digital line recognition in the general case
DGCI'05 Proceedings of the 12th international conference on Discrete Geometry for Computer Imagery
A discrete geometry approach for dominant point detection
Pattern Recognition
Convergence of binomial-based derivative estimation for C2 noisy discretized curves
Theoretical Computer Science
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Several curvature estimators along digital contours were proposed in recent works [1,2,3]. These estimators are adapted to non perfect digitization process and can process noisy contours. In this paper, we compare and analyse the performances of these estimators on several types of contours and we measure execution time on both perfect and noisy shapes. In a second part, we evaluate these estimators in the context of corner detection. Finally to evaluate the performance of a non curvature based approach, we compare the results with a morphological corner detector [4].