Research on Face Recognition Method by Autoassociative Memory Based on RNNs

Author:

Han Qi12ORCID,Wu Zhengyang3,Deng Shiqin1,Qiao Ziqiang4,Huang Junjian2ORCID,Zhou Junjie5,Liu Jin3ORCID

Affiliation:

1. Intelligent School of Technology and Engineering, Chongqing University of Science and Technology, 401331 Chongqing, China

2. Key Laboratory of Machine Perception and Children’s Intelligence Development, Chongqing University of Education, 400067 Chongqing, China

3. College of Safety Engineering, Chongqing University of Science and Technology, 401331 Chongqing, China

4. China United Engineering Corporation Limited, 310052 Hangzhou, Zhejiang, China

5. Chongqing Energy Investment Group Science and Technology Co., Ltd., 400061 Chongqing, China

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.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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