Identity identification method based on cell neural network self associative memory model

A technology of associative memory and neural network, applied in the field of image recognition, can solve the problems of error-prone, low safety factor, easy to be copied, etc., and achieve the effect of preventing leakage and enhancing security
CN107330404AInactive Publication Date: 2017-11-07CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
Publication Date
2017-11-07
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

The invention discloses an identity identification method based on a cell neural network self associative memory model. The method includes the steps of acquiring m fingerprint pictures and face pictures, grouping and numbering the pictures, setting the binary image luminance threshold for the fingerprint picture groups and face picture groups, obtaining a binary fingerprint picture set and a binary face picture set, establishing a fingerprint association memory input matrix and output matrix and a face association memory input matrix and output matrix, establishing a cell neural network fingerprint picture identification model with unknown fingerprint model parameters and a cell neural network face picture identification model with unknown face model parameters, determining the cell neural network fingerprint picture identification model, determining the cell neural network face picture identification model, and conducting identification and matching. Trough a data form, leakage during a transmission process is impossible, and the safety is high. The storage volume is small, and the identity identification effect is good.
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Description

technical field

[0001] The invention relates to the technical field of image recognition, in particular to an identity recognition method based on a cellular neural network self-associative memory model. Background technique

[0002] With the development of the big data era, people have identity information checks during travel, such as face recognition. Through identity recognition, identity verification is realized, the security performance of the system is improved, and different user identity information is confirmed.

[0003] When checking the face information, it must include the face information saved in the database and the face information waiting for verification. For the face information saved in the database, in the prior art, there are the following defects:

[0004] First: face information is often directly stored, which makes identity information easy to leak and has a low safety factor. Once leaked, it is easy to be copied and has poor reliability.

[0005] ...

Claims

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