Feature-based image matching relies on the assumption that the features contained in the model are distinctive enough. When both model and data present a sizeable amount of clutter, the signal-to-noise ratio falls and the detection becomes more challenging. If such clutter exhibits a coherent structure, as it is the case for textured background, matching becomes even harder. In fact, the large amount of repeatable features extracted from the texture dims the strength of the relatively few interesting points of the object itself. In this paper we introduce a game-theoretic approach that allows to distinguish foreground features from background ones. In addition the same technique can be used to deal with the object matching itself. The whole procedure is validated by applying it to a practical scenario and by comparing it with a standard point-pattern matching technique. © 2010 IEEE.

Robust Figure Extraction on Textured Background: A Game-Theoretic Approach

ALBARELLI, Andrea;RODOLA', Emanuele;TORSELLO, Andrea
2010-01-01

Abstract

Feature-based image matching relies on the assumption that the features contained in the model are distinctive enough. When both model and data present a sizeable amount of clutter, the signal-to-noise ratio falls and the detection becomes more challenging. If such clutter exhibits a coherent structure, as it is the case for textured background, matching becomes even harder. In fact, the large amount of repeatable features extracted from the texture dims the strength of the relatively few interesting points of the object itself. In this paper we introduce a game-theoretic approach that allows to distinguish foreground features from background ones. In addition the same technique can be used to deal with the object matching itself. The whole procedure is validated by applying it to a practical scenario and by comparing it with a standard point-pattern matching technique. © 2010 IEEE.
2010
20th International Conference on Pattern Recognition
File in questo prodotto:
File Dimensione Formato  
icpr2010-figure-extraction.pdf

accesso aperto

Tipologia: Documento in Post-print
Licenza: Accesso chiuso-personale
Dimensione 529.53 kB
Formato Adobe PDF
529.53 kB Adobe PDF Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/23423
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? ND
social impact