Bimodal biometrie person identification system under perturbations

Miguel Carrasco, Luis Pizarro, Domingo Mery

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations


Multibiometric person identification systems play a crucial role in environments where security must be ensured. However, building such systems must jointly encompass a good compromise between computational costs and overall performance. These systems must also be robust against inherent or potential noise on the data-acquisition machinery. In this respect, we proposed a bimodal identification system that combines two inexpensive and widely accepted biometric traits, namely face and voice information. We use a probabilistic fusion scheme at the matching score level, which linearly weights the classification probabilities of each person-class from both face and voice classifiers. The system is tested under two scenarios: a database composed of perturbation-free faces and voices (ideal case), and a database perturbed with variable Gaussian noise, salt-and-pepper noise and occlusions. Moreover, we develop a simple rule to automatically determine the weight parameter between the classifiers via the empirical evidence obtained from the learning stage and the noise level. The fused recognition systems exceeds in all cases the performance of the face and voice classifiers alone.

Original languageEnglish
Title of host publicationAdvances in Image and Video Technology - Second Pacific Rim Symposium, PSIVT 2007, Proceedings
Number of pages14
StatePublished - 2007
Event2nd IEEE Pacific Rim Symposium on Video and Image Technology, PSIVT 2007 - Santiago, Chile
Duration: 17 Dec 200719 Dec 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4872 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd IEEE Pacific Rim Symposium on Video and Image Technology, PSIVT 2007


  • Biometrics
  • Face
  • Gaussian noise
  • Identificacion
  • Multimodal
  • Occlusions
  • Probabilistic fusion
  • Salt-and-pepper noise
  • Voice


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