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Proceedings Paper

Performance of composite correlation filters for object recognition
Author(s): Everardo Santiago-Ramirez; J. A. González-Fraga; J. I. Ascencio-Lopez; Olimpia Buenrostro
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Paper Abstract

Correlation filters have become an important tool for detection, localization, recognition and object tracking in digital media. This interest in correlation filters has increased thanks to the processing speed advances of the computers that enable the implementation of digital correlation filters in real-time. This paper compares the performance of three correlation filters in the activity of object recognition, specifically human faces with variations in facial expression, pose, rotation, partial occlusion, illumination and additive white Gaussian noise. The analyzed filters are k-law, MACE and OTSDF. Simulation results show that the k-law nonlinear composite filter has the best performance in terms of accuracy and false acceptance rate. Finally, we conclude that a preprocessing algorithm improves significantly the performance of correlation filters for recognizing objects when they have variations in illumination and noise.

Paper Details

Date Published: 3 November 2011
PDF: 8 pages
Proc. SPIE 8011, 22nd Congress of the International Commission for Optics: Light for the Development of the World, 801174 (3 November 2011); doi: 10.1117/12.902129
Show Author Affiliations
Everardo Santiago-Ramirez, Univ. Autónoma de Baja California (Mexico)
J. A. González-Fraga, Univ. Autónoma de Baja California (Mexico)
J. I. Ascencio-Lopez, Univ. Autónoma de Baja California (Mexico)
Olimpia Buenrostro, Univ. Autónoma de Baja California (Mexico)


Published in SPIE Proceedings Vol. 8011:
22nd Congress of the International Commission for Optics: Light for the Development of the World
Ramón Rodríguez-Vera; Ramón Rodríguez-Vera; Ramón Rodríguez-Vera; Rufino Díaz-Uribe; Rufino Díaz-Uribe; Rufino Díaz-Uribe, Editor(s)

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