Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-12712-0_5 | CompIMAGE |
Keywords | Field | DocType |
curvature estimator,local geometry,classical differentiation mask,discrete set,auto-adaptive mask,discrete shape,discrete line,curvature estimation,auto-adaptive convolution,pictures analysis,discrete function,classical notion,discrete curve,functional analysis | Second derivative,Curvature,Convolution,Mathematical analysis,Heat kernel,Convolution theorem,Kernel (image processing),Overlap–add method,Mathematics,Estimator | Conference |
Volume | ISSN | ISBN |
6026 | 0302-9743 | 3-642-12711-8 |
Citations | PageRank | References |
4 | 0.49 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christophe Fiorio | 1 | 197 | 23.27 |
| Christian Mercat | 2 | 21 | 4.05 |
| Frédéric Rieux | 3 | 7 | 1.57 |