A robust automatic face recognition system for realtime personal identification

Purpose Aims to develop an efficient and robust system for realtime personal identification by automatic face recognition. Designmethodologyapproach A waveletbased image hierarchy and a guided coarsetofine search scheme are introduced to improve the computation efficiency in the face detection task. In addition, a Gaborbased low feature dimensional pattern is proposed to deal with the face recognition problem. Findings The proposal of a waveletbased image hierarchy and a guided coarsetofine search scheme is effective to improve the computation efficiency in the face detection task. The introduction of a low feature dimensional pattern is powerful to cope with the transformed appearancebased face recognition problem. In addition, the use of aggregated Gabor filter responses to represent face images provides a better solution to face feature extraction. Research limitationsimplications Provides guidance in the design of automatic face recognition system for realtime personal identification. Practical implications Biometrics recognition has been emerging as a new and effective identification technology that attains certain level of maturity. Among many body characteristics that have been used, face is one of the most commonly used characteristics and has drawn considerably large attentions. An automated system to confirm an individual's identity employing features of face is very attractive in many specialized fields. Originalityvalue Introduces a waveletbased image hierarchy and a guided coarsetofine search scheme to improve the computation efficiency in the face detection task. Introduces a Gaborbased low feature dimensional pattern to deal with the face recognition problem.