Abstract

Like fingerprint, human face can be applied as a security system because it has almost the same characteristics as that of fingerprint, in terms of the uniqueness and non transferable. Therefore, in this paper, we design and simulate fast human face recognition for the security system. It is realized by implementing the compact features of face image as data dimensional reduction and the shifting-mean LDA as data classifier. The compact features is set of dominant frequency contents and statistical moment of face image and the shifting-mean LDA is an alternative LDA-based classifier which can avoid retraining problem of incremental data. From both off-line and real-time experimental results, the proposed method provides good enough achievements in terms of recognition rate, false rejection rate (FRR), and false acceptance rate (FAR) with requiring short time processing.

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