Name
Abstract | ||
|---|---|---|
The subject of this paper is to propose and test a set ofnumerical descriptors of 2D binary planar shapes. Given a shape, A, the transformations of A with a given mathematical morphological operation and different structuring elements are considered. The measures of this family of transformed setsprovide a numerical description of the original set A.These descriptors are very robust against noise and maintain areasonable discriminatory power. The robustness against different levels of contour degradation is tested bysimulation. Starting with a clean (without noise) set, &Lgr;, it isassumed that the observed set, A, is a noisy version (with contourdegradation) of &Lgr;.The performance of the descriptors, when they are used to comparedifferent shapes or shapes from a scene with models, is studied andcompared with related descriptors based on thegranulometric analysis of the original set, which are the closest previous alternative to our approach in the literature. |
Year | DOI | Venue |
|---|---|---|
1999 | 10.1023/A:1008164518969 | International Journal of Computer Vision |
Keywords | Field | DocType |
2D binary shape description,stochastic mathematical morphology,granulometry,geometric covariogram,shape matching | Computer vision,Pattern recognition,Computer science,Robustness (computer science),Planar,Artificial intelligence,Structuring,Numerical descriptors,Machine learning,Shape analysis (digital geometry),Binary number | Journal |
Volume | Issue | ISSN |
34 | 1 | 1573-1405 |
Citations | PageRank | References |
3 | 0.49 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| E. De Ves | 1 | 119 | 7.62 |
| M. E. Díaz | 2 | 10 | 1.68 |
| G. Ayala | 3 | 16 | 3.55 |
| Juan Domingo | 4 | 3319 | 258.54 |
| A. Simó | 5 | 102 | 11.24 |