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Face recognition method based on optics nonsubsampled Contourlet conversion

A non-subsampling contour and non-subsampling technology, applied in the field of pattern recognition, can solve problems such as difficult to meet real-time face recognition and slow recognition speed

Inactive Publication Date: 2009-11-04
CHONGQING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] However, the huge amount of calculation in the application of non-subsampling Contourlet transform restricts its further promotion. The face recognition technology based on non-subsampling Contourlet transform has the obvious disadvantage of slow recognition speed, and it is difficult to meet the real-time requirements of face recognition. Require

Method used

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  • Face recognition method based on optics nonsubsampled Contourlet conversion
  • Face recognition method based on optics nonsubsampled Contourlet conversion
  • Face recognition method based on optics nonsubsampled Contourlet conversion

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Embodiment 1

[0046] Embodiment 1: the structure of the optical non-subsampling Contourlet transformation module is as follows figure 2 As shown, the helium-neon laser 1 is located at 18 cm ahead of the pinhole filter 2, the pinhole filter 2 is located at the front focal plane of the collimator lens 3, and a beam splitter 4 is installed at 18 cm behind the collimator lens 3, and the beam splitter 4 rear Install the first electrical addressing spatial light modulator 5 at 28 cm, the electrical addressing spatial light modulator 5 is located at the front focal plane of the first Fourier lens 6, and the first Fourier lens 6 is installed at the rear focal plane A CCD optocoupler device 7; a plane reflector 8 is installed at 28 cm below the beam splitter 4, and a second electric addressing spatial light modulator 9 is installed at a place 28 cm behind the plane reflector, and the electric addressing spatial light modulator 9 is located at the second Fu At the front focal plane of the Liye lens ...

Embodiment 2

[0055] Embodiment 2 has the same structure and method as Embodiment 1, but the difference is that in Embodiment 2, the helium-neon laser 1 is positioned at 16 cm in front of the pinhole filter 2, and a beam splitter 4 is installed at 16 cm behind the collimating lens 3, and the beam splitter 4 A first electrical addressing spatial light modulator 5 is installed at the rear 26 cm, a plane reflector 8 is installed at 26 cm below the beam splitter 4, a second electrical addressing spatial light modulator 9 is installed at 26 cm behind the plane mirror 8, and the beam splitter The beam splitting angle is 50 degrees.

Embodiment 3

[0056] Embodiment 3 has the same structure and method as Embodiment 1, except that in Embodiment 3, the helium-neon laser 1 is positioned at 20 cm in front of the pinhole filter 2, and a beam splitter 4 is installed at 20 cm behind the collimating lens 3, and the beam splitter 4 The first electrical addressing spatial light modulator 5 is installed at the rear 30 cm, the plane reflector 8 is installed at 30 cm below the beam splitter 4, the second electrical addressing spatial light modulator 9 is installed at the rear 30 cm of the plane mirror 8, and the beam splitter The beam splitting angle is 70 degrees.

[0057] Apply the optical non-subsampling Contourlet transformation module to realize the non-subsampling Contourlet transformation of the face image, such as figure 2 As shown, a helium-neon laser 1 passes through a pinhole filter 2 and a collimating lens 3 to form parallel light, transmits it on a first electrical addressable spatial light modulator 5 through a beam sp...

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Abstract

The invention relates to a face recognition method based on optics nonsubsampled Contourlet conversion; the device for the method comprises an optics nonsubsampled Contourlet conversion module, a feature extraction module and a pattern classification module; firstly, nonsubsampled Contourlet conversion is realized for face picture by the optics nonsubsampled Contourlet conversion module to obtain the numerical result of face picture nonsubsampled Contourlet conversion; then, the feature extraction module extracts the features such as outline and posture of the face, and organs such as eyes, noses, mouth and the like from the numerical result of face picture nonsubsampled Contourlet conversion; finally, the pattern classification module carries out similarity comparison between the extracted face features and features of standard face picture to obtain face recognition result. The face recognition method provided by the invention can be used in numerous fields such as secret information access control, registered residence and identity card management, entrance guard control system and the like. Compared with traditional face recognition method, the invention can improve face recognition speed.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition and relates to face recognition technology, in particular to a face recognition method based on optical non-subsampling Contourlet (contourlet) transformation. Background technique [0002] Today's human society has entered the information society, and information security has shown unprecedented importance. Biometric identification technology uses the unique physiological or behavioral characteristics of the human body for identification. It has good security, reliability and effectiveness, and has been widely used in confidential information access control, household registration and ID card management, and criminal identification. , prison security, access control systems and many other fields. As a biometric feature, the face has the advantages of being difficult to forge, not lost, unchanged for life, and portable. Compared with other biometrics, face recognition has the characte...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62G02F1/35
Inventor 韩亮钟将温罗生李勇明蒲秀娟覃剑余传祥蒲亨立
Owner CHONGQING UNIV
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