Face recognition/detection by probabilistic decision-based neural network

Shang Hung Lin, Sun Yuan Kung, Long Ji Lin

Research output: Contribution to journalArticlepeer-review

421 Scopus citations


This paper proposes a face recognition system based on probabilistic decision-based neural networks (PDBNN). With technological advance on microelectronic and vision system, high performance automatic techniques on biometric recognition are now becoming economically feasible. Among all the biometric identification methods, face recognition has attracted much attention in recent years because it has potential to be most non-intrusive and user-friendly. The PDBNN face recognition system consists of three modules: First, a face detector finds the location of a human face in an image. Then an eye localizer determines the positions of both eyes in order to generate meaningful feature vectors. The facial region proposed contains eyebrows, eyes, and nose, but excluding mouth. (Eye-glasses will be allowed.) Lastly, the third module is a face recognizer. The PDBNN can be effectively applied to all the three modules. It adopts a hierarchical network structures with nonlinear basis functions and a competitive credit-assignment scheme. The paper demonstrates a successful application of PDBNN to face recognition applications on two public (FERET and ORL) and one in-house (SCR) databases. Regarding the performance, experimental results on three different databases such as recognition accuracies as well as false rejection and false acceptance rates are elaborated in Section IV-D and V. As to the processing speed, the whole recognition process (including PDBNN processing for eye localization, feature extraction, and classification) consumes approximately one second on SparclO, without using hardware accelerator or co-processor.

Original languageEnglish (US)
Pages (from-to)114-132
Number of pages19
JournalIEEE Transactions on Neural Networks
Issue number1
StatePublished - 1997

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications


  • Decision-based neural network (DBNN)
  • Eye localization
  • Face detection
  • Face recognition system
  • Hierarchical fusion
  • Positive/negative training sets
  • Probabilistic DBNN
  • Virtual pattern generation


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