Abstract
In order to avoid the risk of the biological database being attacked and tampered by hackers, an Autoassociative Memory (AAM) model is proposed in this paper. The model is based on the recurrent neural networks (RNNs) for face recognition, under the condition that the face database is replaced by its model parameters. The stability of the model is proved and analyzed to slack the constraints of AAM model parameters. Besides, a design procedure about solving AAM model parameters is given, and the face recognition method by AAM model is established, which includes image preprocessing, AAM model training, and image recognition. Finally, simulation results on two experiments show the feasibility and performance of the proposed face recognition method.
Highlights
With the development of information and Internet, biometric technology has been rapidly developed for security, confidentiality, and convenience in Internet applications
Based on the aforementioned discussion, the main contributions of this paper are listed as follows: (1) To protect the face features database fundamentally, a new face recognition method by Autoassociative Memory (AAM) based on recurrent neural networks (RNNs) is proposed without establishing face feature database, in which the face features are transformed into the parameters of the AAM model
The face recognition method proposed in this paper is implement through AAM based on RNNs
Summary
With the development of information and Internet, biometric technology has been rapidly developed for security, confidentiality, and convenience in Internet applications. Current approaches to BED are based on garbled circuits [16] and homomorphic encryption [15], but these schemes are much more complex than the representations used in the aforementioned articles [17] These schemes achieved some success, they do not completely eliminating the risk of hacker attacking and tampering the templates. In order to tackle this problem, a new face recognition method by associative memory (AM) is proposed in this paper. (1) To protect the face features database fundamentally, a new face recognition method by AAM based on RNNs is proposed without establishing face feature database, in which the face features are transformed into the parameters of the AAM model.
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