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An Identity Confirmation Method Based on Overall End-to-End Unsteady Iris Cognitive Recognition

An identity confirmation, non-steady-state technology, applied in the acquisition/recognition of eyes, character and pattern recognition, calculation, etc., to achieve the effect of improving accuracy, reducing the amount of training, and improving the convenience of expansion

Active Publication Date: 2022-03-29
JILIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The main purpose of the present invention is to solve the problem of iris recognition algorithm from data availability, recognition accuracy, scheme integrity and expansion convenience;

Method used

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  • An Identity Confirmation Method Based on Overall End-to-End Unsteady Iris Cognitive Recognition
  • An Identity Confirmation Method Based on Overall End-to-End Unsteady Iris Cognitive Recognition
  • An Identity Confirmation Method Based on Overall End-to-End Unsteady Iris Cognitive Recognition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0116] Under the framework of claim 1, a certain person (named A, the information of A has not been entered before, the test iris and the template iris are collected by the same iris collector, and the computer system has not entered anyone’s information before) The whole process of operation:

[0117]1) Use an iris collector to collect 2000 template iris grayscale images of A.

[0118] 2) The computer system extracts the eye image information of each template iris grayscale image of A, and uses A's 2000 template iris grayscale images to set the characteristics of A's eye image.

[0119] 3) The computer system extracts the iris quality information of each template iris grayscale image of A, and uses A's 2000 template iris grayscale images to set A's iris quality characteristics.

[0120] 4) The computer system converts each template iris grayscale image of A into a 256×32-dimensional template iris normalized image by the Daugman rubber band method.

[0121] 5) The computer s...

Embodiment 2

[0130] Under the framework of claim 1, to six people (named A, B, C, D1, D2, D3, the information of A, B, D1, D2, D3 has not been entered before, but the information of C has been entered, the test iris and The template iris is collected by the same iris collector) The whole process of operation:

[0131] 1) Use an iris collector to collect 2000 template iris grayscale images of A.

[0132] 2) The computer system extracts the eye image information of each template iris grayscale image of A, and uses A's 2000 template iris grayscale images to set the characteristics of A's eye image.

[0133] 3) The computer system extracts the iris quality information of each template iris grayscale image of A, and uses A's 2000 template iris grayscale images to set A's iris quality characteristics.

[0134] 4) The computer system converts each template iris grayscale image of A into a 256×32-dimensional template iris normalized image by the Daugman rubber band method.

[0135] 5) The comput...

Embodiment 3

[0152] Under the framework of claim 1, to six people (named A, B, C, D1, D2, D3, before entering the information of A, C, D1, D2, D3, but not the information of B entering, test iris and The template iris is collected by the same iris collector) The whole process of operation:

[0153] 1) Collect one test iris grayscale image of B.

[0154] 2) The computer system extracts the eye image information of the test iris grayscale image of B.

[0155] 3) The computer system extracts the iris quality information of the test iris grayscale image of B.

[0156] 4) The computer system matches the eye image information and iris quality information of B with the eye image features and iris quality features of A, C, D1, D2, D3 respectively, and extracts the template iris feature information of A, C, and D1.

[0157] 5) The computer system converts the test iris grayscale image of B into a 256×32-dimensional test iris normalized image by the Daugman rubber band method.

[0158] 6) The com...

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Abstract

The invention discloses an identity confirmation method based on the overall end-to-end unsteady-state iris cognitive recognition. The method is as follows: step 1, collecting 2000 iris grayscale images; step 2, setting the eye image of the template tester Feature; Step 3, setting the iris quality feature of the template tester; Step 4, converting the template iris normalized image; Step 5, setting 32-bit template features; Step 6, repeating Steps 1 to 5; Step 7, Collect 1 iris grayscale image; Step 8, extract eye image information; Step 9, extract iris quality information; Step 10, extract template iris feature information; Step 11, test iris normalized image; Step 12, test iris features information; step thirteen, the extracted matching value of the template features of the template tester; beneficial effects: improve the integrity of the scheme, improve the fit between data feature expression and recognition, improve the accuracy of recognition and the usability of data.

Description

technical field [0001] The invention relates to an iris-based identity verification method, in particular to an identity confirmation method based on overall end-to-end unsteady-state iris cognitive recognition. Background technique [0002] Because of its stability, vitality, and non-contact, the iris is an indispensable means of authentication, and its recognition accuracy is significantly higher than that of fingerprints and faces. With the continuous spread of the new crown epidemic in 2020, the disadvantages of face recognition and fingerprint recognition that need to take off protective equipment such as masks and gloves during the recognition process are more obvious. Therefore, compared with the current face recognition products and fingerprint recognition products that are more widely used , identity authentication products based on iris recognition have better development prospects and economic value. [0003] Compared with face recognition and fingerprint recogni...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V40/18G06V10/44G06V10/26
CPCG06V40/193G06V10/267G06V10/44
Inventor 刘帅刘元宁朱晓冬董立岩刘震刘静崔靖威李海鹏周智勇袁一航孙野张亚星董楠
Owner JILIN UNIV
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