Iris recognition method based on wavelet packet decomposition

A technology of wavelet packet decomposition and iris recognition, which is applied in the field of biometrics, can solve the problems of small iris feature space and difficulty in guaranteeing the recognition rate, and achieve the effect of improving classification performance, improving accuracy rate, and high correct recognition rate

Pending Publication Date: 2021-01-26
CHONGQING BUSINESS VOCATIONAL COLLEGE
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Problems solved by technology

Lim uses the Haar wavelet as the mother wavelet to filter and decompose the normalized area of ​​the iris four times, and modulates the high-frequency area of ​​the fourth layer obtained by the decomposition, and forms 87 bits with the mean value of the high-frequency coefficients of the wavelet decomposition of the first to third layers Iris feature coding uses the

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  • Iris recognition method based on wavelet packet decomposition
  • Iris recognition method based on wavelet packet decomposition
  • Iris recognition method based on wavelet packet decomposition

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[0093] Using MATLAB R2019a version, the iris image comes from the iris database of the CASIA (V1.0) version of the Chinese Academy of Sciences. The iris database contains 108 categories of human iris images, and each category includes 6 human iris images. Decompose the wavelet base and choose sym2 wavelet, its scale function and wavelet function are as attached Figure 18 shown.

[0094] In the authentication mode, select one pair of iris images of each type of human eye and extract features as a template, compare with other iris features of the same type, and generate similar Hamming distance. In the recognition mode, select one pair of iris images of each type of human eye and extract features as a template, compare with other 107 types of iris features of different types, and generate a total of different kinds of Hamming distances. like Figure 19 As shown, the same and different types of Hamming distance distribution curves have large intervals, little overlap, and ...

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Abstract

The invention discloses an iris recognition method based on wavelet packet decomposition, and the method comprises the steps: collecting a human eye image, carrying out the iris image preprocessing, obtaining a processed iris image, modulating the diagonal high-frequency information of the wavelet packet decomposition of the iris image into an iris feature code through a threshold value, extracting the iris features, and finally, adopting a Hamming distance classifier to perform classification and matching calculation on iris features, and judging whether the two feature codes are from the same iris or not by calculating the similarity between the current iris feature code and iris codes in an iris template library, so that iris images are classified. The iris features extracted through the iris feature recognition method have good classification performance, so that the iris recognition precision is improved.

Description

technical field [0001] The invention belongs to the technical field of biological identification, and in particular relates to an iris identification method based on wavelet packet decomposition. Background technique [0002] Iris recognition is a kind of biometric recognition technology, which has higher recognition rate and security than fingerprint, face and other biometric technologies. Feature extraction is a key link in iris recognition. The characteristics of identity identification are extracted from iris texture, and then identity confirmation or identification is carried out by pattern recognition methods. The early iris recognition algorithms mainly include: Daugman's two-dimensional Gabor method, Wildes' Gauss-Laplace pyramid method, and the Daugman method tends to decrease significantly when recognizing iris images with poor quality, and the algorithm is only from a qualitative point of view The features representing the iris are lacking in representing the det...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/40G06K9/46G06K9/52G06K9/62
CPCG06V40/193G06V40/197G06V10/30G06V10/44G06V10/52G06F18/24
Inventor 周俊王帅
Owner CHONGQING BUSINESS VOCATIONAL COLLEGE
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