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Face recognition/detection by probabilistic decision-based neural network.

S H Lin1, S Y Kung, L J Lin

  • 1Dept. of Electr. Eng., Princeton Univ., NJ.

IEEE Transactions on Neural Networks
|January 1, 1997
PubMed
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This study introduces a face recognition system using probabilistic decision-based neural networks (PDBNN). The PDBNN system achieves high accuracy and fast processing speeds for reliable biometric identification.

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Biometrics

Background:

  • Biometric recognition systems are increasingly feasible due to technological advancements.
  • Face recognition is a user-friendly and non-intrusive biometric identification method.
  • Probabilistic decision-based neural networks (PDBNN) offer a robust approach for complex pattern recognition tasks.

Purpose of the Study:

  • To propose and evaluate a novel face recognition system utilizing PDBNN.
  • To demonstrate the effectiveness of PDBNN across multiple modules of a face recognition pipeline.
  • To analyze the performance and speed of the PDBNN-based system on diverse datasets.

Main Methods:

  • A three-module system: face detection, eye localization, and face recognition.

Related Experiment Videos

  • Application of PDBNN with hierarchical network structures and competitive credit assignment.
  • Utilized public (FERET, ORL) and in-house (SCR) databases for validation.

    • Main Results:

    • The PDBNN system demonstrated successful face recognition across three databases.
    • Detailed performance metrics including recognition accuracy, false rejection rates, and false acceptance rates were reported.
    • The entire recognition process, including detection, localization, feature extraction, and classification, completed in approximately one second on a Sparc10 system.

    Conclusions:

    • PDBNN is effectively applied to face recognition, offering a viable solution for biometric identification.
    • The proposed system achieves competitive performance in terms of accuracy and speed.
    • The PDBNN-based face recognition system is efficient and user-friendly.