One-to-one iris identification method for scale variation stability characteristics and multi-algorithm voting

A technology of scale change and iris recognition, which is applied to acquisition/recognition of eyes, character and pattern recognition, calculation, etc. It can solve the problems of iris feature extraction deviation, judgment error, and unstable distribution of iris texture features.

Active Publication Date: 2018-06-08
JILIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The three types of algorithms have achieved good results in experiments, but there are still some problems. First, the first and second types of algorithms are aimed at pixel texture information and require high image quality, so the ability to resist noise is poor.
The feature extraction of the third type of algorithm is more comple

Method used

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  • One-to-one iris identification method for scale variation stability characteristics and multi-algorithm voting
  • One-to-one iris identification method for scale variation stability characteristics and multi-algorithm voting
  • One-to-one iris identification method for scale variation stability characteristics and multi-algorithm voting

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0080] The whole process of operating on a certain person (named A) under the framework of claim 1:

[0081] 1) collect the eye image of A through the iris collector, and extract the iris information in the eye image of A through the computer;

[0082] After the eye image is collected, the computer determines that the iris information can be extracted from the clarity of the collected eye image through the Tenengrad gradient method. Through the method of canny edge detection and hough detection circle, find the location of the pupil and iris boundary, calculate the area of ​​the inner ring of the two boundaries, and find the gray distribution of the iris area according to the gray histogram, and then calculate the iris according to the gray distribution The ratio of the area of ​​the area to the ring, and the proportion of the iris accounts for one-third of the ratio of the iris ring, so the computer determines that the iris area in the captured eye image can extract enough ir...

Embodiment 2

[0096] The whole process of operation performed by two persons (named B and C) within the framework of claim 1:

[0097] 1) Collect the eye image of B through the iris collector, and extract the iris information in the eye image of B through the computer;

[0098] After the eye image is collected, the computer determines that the iris information can be extracted from the clarity of the collected eye image through the Tenengrad gradient method. After that, the computer finds the location of the pupil and the iris boundary through the method of canny edge detection and hough detection circle, calculates the area of ​​the inner circle of the two boundaries, and finds the gray distribution of the iris area according to the gray histogram, and then according to the gray The ratio of the area of ​​the iris area in the ring is calculated by distribution, and the iris ratio accounts for 50% of the iris ring ratio, so the computer determines that the iris area in the captured eye imag...

Embodiment 3

[0112] The whole process of operating on a certain person (named D) under the framework of claim 1:

[0113] 1) Collect the eye image of D through the iris collector, and extract the iris information in the eye image of D through the computer;

[0114] After the eye image is collected, the computer determines that the iris information can be extracted from the clarity of the collected eye image through the Tenengrad gradient method. Through the method of canny edge detection and hough detection circle, find the location of the pupil and iris boundary, calculate the area of ​​the inner ring of the two boundaries, and find the gray distribution of the iris area according to the gray histogram, and then calculate the iris according to the gray distribution The proportion of the area of ​​the area in the ring, the proportion of the iris accounts for 69% of the proportion of the iris ring, so the computer determines that the iris area in the captured eye image can extract enough ir...

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PUM

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Abstract

The invention discloses a one-to-one iris identification method for scale variation stability characteristics and multi-algorithm voting. Personal information relates to an iris and identification people is stored into an infrared radio frequency scanning identity card to serve as a comparison party in an experiment, and then, the iris of a testing person is collected during normal collection to serve as a testing party in the comparison experiment. By use of the method, on a premise that the effective characteristics of the iris are guaranteed, the interference of redundancy and noise is reduced, a vote is taken through multiple algorithms, a risk of an identification error situation due to a collection environment influence is lowered, the correctness identification rate and the robustness of the iris can be increased, safety and reliability are increased, and the method is simple in operation and easy in mastering.

Description

technical field [0001] The invention relates to the fields of electricity, digital image processing, digital signal transmission and biological feature identification. The concept of scale-varying stable features is proposed. And extract the information of the scale change stable characteristics of the collected iris, and use the method of multi-algorithm voting to determine whether two irises are of the same category in a one-to-one form. Background technique [0002] At present, biometric technology is widely used. Face recognition, iris recognition, fingerprint recognition, etc. have begun to appear in our daily life in large numbers. For some places that require high confidentiality and high security, such as prisons, banks, military bases, etc., iris is the most effective and reliable biometric feature. The key to iris recognition is feature extraction and expression. [0003] Iris feature extraction is currently mainly divided into three types of methods: the first ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06T7/13G06T7/40
CPCG06T7/13G06T7/40G06T2207/30168G06V40/193G06V10/446
Inventor 刘元宁刘帅朱晓冬董立岩冯家凯郑少阁沈椿壮苏丹扬
Owner JILIN UNIV
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