CVGIP: Image Understanding
Estimation of Curvature and Tangent Direction by Median Filtered Differencing
ICIAP '95 Proceedings of the 8th International Conference on Image Analysis and Processing
Segmentation and Length Estimation of 3D Discrete Curves
Digital and Image Geometry, Advanced Lectures [based on a winter school held at Dagstuhl Castle, Germany in December 2000]
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
A Comparative Evaluation of Length Estimators of Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast, accurate and convergent tangent estimation on digital contours
Image and Vision Computing
Digital Straight Line Segments
IEEE Transactions on Computers
A concise and provably informative multi-scale signature based on heat diffusion
SGP '09 Proceedings of the Symposium on Geometry Processing
Shape analysis using the auto diffusion function
SGP '09 Proceedings of the Symposium on Geometry Processing
Curvature estimation in noisy curves
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Normals and curvature estimation for digital surfaces based on convolutions
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
Accurate curvature estimation along digital contours with maximal digital circular arcs
IWCIA'11 Proceedings of the 14th international conference on Combinatorial image analysis
Adaptive discrete Laplace operator
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
Multigrid convergent curvature estimator
DGCI'13 Proceedings of the 17th IAPR international conference on Discrete Geometry for Computer Imagery
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We propose a method that we call auto-adaptive convolution which extends the classical notion of convolution in pictures analysis to function analysis on a discrete set. We define an averaging kernel which takes into account the local geometry of a discrete shape and adapts itself to the curvature. Its defining property is to be local and to follow a normal law on discrete lines of any slope. We used it together with classical differentiation masks to estimate first and second derivatives and give a curvature estimator of discrete functions.