Name
Abstract | ||
|---|---|---|
The Max-Tree is an efficient data structure that represents all connected components resulting from all possible image upper threshold values. Usually, most of its nodes represent irrelevant extrem a, i.e. noise, or small variations of a connected component. This paper proposes the Maximal Max-Tree Simplification (MMS) filter with a normalized threshold criterion (MMS-T) and a Maximally Stable Extremal Regions (MSER) criterion (MMS-MSER) and a methodology to apply them using the Extinction filter We show that after applying our simplification methodology which sets the number of maxima in the image, the number of Max-Tree nodes is at most twice this number. Two applications of the proposed methodology are illustrated. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICPR.2014.540 | Pattern Recognition |
Keywords | DocType | ISSN |
data structures,filtering theory,image representation,MMS filter,MMS-MSER,MMS-T,MSER criterion,data structure,extinction filter,image upper threshold values,maximal max-tree simplification,maximally stable extremal regions,normalized threshold criterion,Composite node,Extinction filter,MMS filter,MSER,Max-Tree,Sub-branch | Conference | 1051-4651 |
Citations | PageRank | References |
4 | 0.43 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roberto Souza | 1 | 72 | 9.78 |
| Leticia Rittner | 2 | 82 | 12.95 |
| Rubens Campos Machado | 3 | 50 | 3.17 |
| Roberto de Alencar Lotufo | 4 | 572 | 53.61 |