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Proceedings Paper

A new Rényi entropy-based local image descriptor for object recognition
Author(s): S. Gabarda; G. Cristóbal; P. Rodríguez; C. Miravet; J. M. del Cura
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Paper Abstract

This paper shows how local directional entropy can be used as a tool to build up a robust local image descriptor for image feature extraction. Among other possible choices, the Rényi entropy has been selected as the main technique for this application. Local directional entropy which is related with the anisotropy images has been considered here as the basis for the design of a new Rényi entropy-based local image descriptor (RELID). The properties of this new descriptor are described and evaluated. The experimental results confirm that the new descriptor is endowed by most of the invariant properties desired for object recognition applications.

Paper Details

Date Published: 6 May 2010
PDF: 13 pages
Proc. SPIE 7723, Optics, Photonics, and Digital Technologies for Multimedia Applications, 772312 (6 May 2010); doi: 10.1117/12.854901
Show Author Affiliations
S. Gabarda, Consejo Superior de Investigaciones Científicas (Spain)
G. Cristóbal, Consejo Superior de Investigaciones Científicas (Spain)
P. Rodríguez, Sener Ingeniería y Sistemas (Spain)
C. Miravet, Sener Ingeniería y Sistemas (Spain)
J. M. del Cura, Sener Ingeniería y Sistemas (Spain)


Published in SPIE Proceedings Vol. 7723:
Optics, Photonics, and Digital Technologies for Multimedia Applications
Peter Schelkens; Touradj Ebrahimi; Gabriel Cristóbal; Frédéric Truchetet; Pasi Saarikko, Editor(s)

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