Name
Abstract | ||
|---|---|---|
This paper presents the fusion of monogenic signal processing and differential geometry to enable monogenic analyzing of local intrinsic 2D features of low level image data. New rotational invariant features such as structure and geometry (angle of intersection) of two superimposed intrinsic 1D signals will be extracted without the need of any steerable filters. These features are important for all kinds of low level image matching tasks in robot vision because they are invariant against local and global illumination changes and result from one unique framework within the monogenic scale-space. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-78157-8_35 | RobVis |
Keywords | DocType | Volume |
global illumination change,monogenic scale-space,monogenic analyzing,monogenic signal processing,low level image data,steerable filter,monogenic signal representation,differential geometry,new rotational invariant,robot vision,low level image,signal processing,global illumination,scale space,image analysis | Conference | 4931 |
ISSN | ISBN | Citations |
0302-9743 | 3-540-78156-0 | 5 |
PageRank | References | Authors |
0.60 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lennart Wietzke | 1 | 163 | 11.40 |
| Gerald Sommer | 2 | 5 | 0.60 |
| Christian Schmaltz | 3 | 146 | 10.53 |
| Joachim Weickert | 4 | 5489 | 391.03 |