A feature fusion living body detection method

A technology of living body detection and feature fusion, which is applied in the field of image processing, can solve the problems of loss of color and texture information, and achieve strong robustness, improved classification accuracy, and good user experience

Inactive Publication Date: 2019-04-02
CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI +1
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AI Technical Summary

Problems solved by technology

The method of multispectral image processing is more versatile across data, but due to the influence of external light

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  • A feature fusion living body detection method
  • A feature fusion living body detection method
  • A feature fusion living body detection method

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Embodiment Construction

[0045] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0046] The present invention proposes a human face liveness detection method that globally automatically fuses visible light and near-infrared image information. The classification accuracy and robustness of the prosthetic face are also stronger.

[0047] Visible light images contain rich color, brightness, and chromaticity distribution information, as well as clear facial texture information. These information are important clues to distinguish living human faces from prosthetic human faces. Currently common prosthetic faces such as photos and masks are made of different materials from real skin. Different materials have different reflection information under the near-infrared spectrum. The reflection information recorded in the collected near-infrared images can also be used as an important clue to distinguish living human faces from p...

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Abstract

The invention relates to a feature fusion living body detection method, and belongs to the field of image processing. The method deeply combines the advantages of the two types of images, simply and effectively improves the classification accuracy of a real person face and prosthesis faces such as a photo, a video, a three-dimensional mask and the like, and the robustness is stronger. According tothe invention, rich color texture information in the visible light image and reflection information in the near infrared image are fully utilized; an end-to-end deep learning method is adopted for automatic global learning, features of the two types of images are fused and classified, the advantages of the two types of images are combined, and the classification accuracy of the real human face and the prosthesis face is simply and effectively improved; attacks of photos, videos and three-dimensional masks can be identified at the same time, and the robustness of cross-data and attack types ishigh; and user interaction and cooperation are not needed, non-inductive living body detection is realized, and the user experience is good.

Description

technical field [0001] The invention belongs to the field of image processing and relates to a living body detection method of feature fusion Background technique [0002] Traditional face recognition systems cannot distinguish whether the face in the currently acquired image is a living human face or a prosthetic human face. With the wide application of face recognition technology, prosthetic face attacks such as face photos, face videos, and 3D masks emerge in an endless stream, and face liveness detection has attracted more and more attention from industry and academia. Face liveness detection has gradually become an indispensable link in the face recognition system. From the perspective of processing image types, the current common face detection methods include methods based on visible light image processing and methods based on multispectral image processing. [0003] Methods based on visible light image processing usually analyze image texture information, motion in...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V40/161G06V40/168G06V40/45G06N3/045G06F18/253
Inventor 蒋方玲刘鹏程邵枭虎张宇周祥东石宇程俊罗代建
Owner CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI
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