Iris activity detection method based on feature fusion and machine learning

A feature fusion and machine learning technology, applied in deception detection, biometric identification, instruments, etc., can solve problems such as inability to defend against iris attacks, low accuracy of iris activity detection, and inability to guarantee the security of iris recognition systems, and to achieve shortened The effect of data processing time, enhancing data generalization ability, and improving method detection speed

Pending Publication Date: 2019-08-13
JIANGSU UNIV
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Problems solved by technology

[0005] According to the problems existing in the prior art, the present invention proposes an iris activity detection method based on feature fusion and machine learning. Defense against iris attacks and the inability to guarantee the security of iris recognition systems

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  • Iris activity detection method based on feature fusion and machine learning
  • Iris activity detection method based on feature fusion and machine learning
  • Iris activity detection method based on feature fusion and machine learning

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[0034] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0035] In this embodiment, both the artificially synthesized iris data samples and the real iris data samples adopt the standard data set provided by the CASIA Chinese Academy of Sciences, and the artificially synthesized iris data samples and the real iris data samples are each divided into two, and the training set samples include 50 % artificial iris samples and 50% real iris data samples, the test set samples contain 50% artificial iris samples and 50% real iris data samples. The training set is used to train the model. The test set is used to test the iris activity detection effect of the pre...

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Abstract

The invention discloses an iris activity detection method based on feature fusion and machine learning. The method comprises the following steps of preparing an iris image data set, respectively extracting LBP features and HOG features of the iris image, carrying out dimension reduction processing on the extracted LBP features and HOG features, and fusing the LBP features and HOG features after dimension reduction by using a canonical correlation analysis method; and inputting the fused features into a support vector machine model, and carrying out training and classification on iris image features to realize iris activity detection. The iris activity detection method can solve the problems that in an existing iris activity detection method, the iris activity detection accuracy is not high, iris attacks cannot be effectively defended, and the safety of an iris recognition system cannot be guaranteed.

Description

technical field [0001] The invention belongs to the technical field of image processing and pattern recognition, in particular to an iris activity detection method based on feature fusion and machine learning. Background technique [0002] With the continuous development of human society on the road of informatization in recent years, the importance of identity authentication has become more prominent. At the same time, traditional identity authentication methods have also been severely challenged. As a new identity authentication method, biometrics has attracted more and more attention due to its natural high uniqueness, security and convenience. Moreover, the identity authentication method based on this, that is, biometric identification, has also achieved rapid development. Among them, iris recognition has its incomparable advantages in stability, uniqueness and non-invasiveness, and occupies a very important position in the field of identification. [0003] The rapid d...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/193G06V40/197G06V40/45G06F18/2135G06F18/2411G06F18/253
Inventor 陈健美王玉玺于磊春胡杨王国辉
Owner JIANGSU UNIV
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