Abstract
The Achilles’ heel of most shape recognition systems is the decision stage, whose goal is to clearly answer the question of whether two shapes look alike or not. In this chapter we propose a method to address this issue, that consists in pairing two shapes as soon as their proximity is unlikely to be observed “by chance.” This is achieved by bounding the number of false matches between a query shape and shapes from the database. The same statistical principle is used to extract relevant shape elements from images, yielding a complete procedure to decide whether or not two images share some common shapes.
| Original language | English |
|---|---|
| Title of host publication | Statistics and Analysis of Shapes |
| Editors | Hamid KRIM, Anthony YEZZI |
| Place of Publication | Boston |
| Publisher | Birkhauser Boston |
| Pages | 107-136 |
| Number of pages | 30 |
| ISBN (Electronic) | 9780817644819 |
| ISBN (Print) | 9780817643768 |
| DOIs | |
| Publication status | Published - 2006 |
| Externally published | Yes |
Publication series
| Name | Modeling and Simulation in Science, Engineering and Technology |
|---|---|
| Publisher | Birkhauser |
| ISSN (Print) | 2164-3679 |
| ISSN (Electronic) | 2164-3725 |
Funding
This work was supported by the Office of Naval Research under grant N00014-97-1-0839, by the Centre National d’Études Spatiales, and by the Réseau National de Recherche en Télécommunications (projet ISII). Algorithms were implemented using the MegaWave2 free software.
Keywords
- a contrario decision
- background model
- level lines
- number of false alarms
- shape elements
- Shape recognition