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Screen edge-based mobile phone playback living body attack identification method

A screen edge and attack recognition technology, applied in the field of image processing, can solve the problem that video playback attacks cannot be effectively avoided, and achieve the effect of strong generalization ability and high operating efficiency

Inactive Publication Date: 2020-04-10
CHINA SCI INTELLICLOUD TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method cannot effectively avoid video playback attacks

Method used

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  • Screen edge-based mobile phone playback living body attack identification method
  • Screen edge-based mobile phone playback living body attack identification method
  • Screen edge-based mobile phone playback living body attack identification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] A mobile phone playback live attack recognition method based on the edge of the screen, this method is based on a recognition system, such as figure 1 As shown, the recognition system includes an input module, an image out-of-focus detection module, a screen edge detection module and a judgment output module;

[0054] Described input module carries out facial recognition to the photo that camera is captured, and after identifying human face, frame-selects human face image, extracts the human face image in the range of frame selection, and transmits human face image to image out-of-focus detection module;

[0055] The image out-of-focus detection module performs image out-of-focus detection on the face image input by the image transmission module, and transmits the face image that is determined not to be out of focus after the image out-of-focus detection to the screen edge detection module;

[0056] The screen edge detection module performs screen edge detection on the...

Embodiment 2

[0061] The present invention is on the basis of above-mentioned embodiment 1, in order to realize the present invention better, as figure 2 As shown, further, the image out-of-focus detection specifically includes the following steps:

[0062] Step S1: Gaussian blur denoising is performed on the face image;

[0063] Step S2: Grayscale the face image after Gaussian denoising;

[0064] Step S3: Filtering the gray-scaled face image through the Laplacian algorithm;

[0065] Step S4: Calculate the mean and variance of the filtered face image;

[0066] Step S5: Preset the variance threshold M for determining out-of-focus, compare the variance calculated in step S4 with the variance threshold M as a standard, and determine whether the face image input by the image transmission module is a face image that is not out of focus;

[0067] Step S6: Transmit the face image determined not to be out of focus to the screen edge detection module.

[0068] Working principle: Image out-of-fo...

Embodiment 3

[0071] The present invention is on the basis of above-mentioned embodiment 1-2, in order to realize the present invention better, as image 3 As shown, further, the screen edge detection specifically includes the following steps:

[0072] Step S7: performing canny edge extraction on the out-of-focus face image;

[0073] Step S8: performing Huffman straight line extraction on the face image after canny edge extraction;

[0074] Step S9: performing line segment filtering on the face image after Huffman line extraction;

[0075] Step S10: Count the number of line segments on the face image after line segment filtering;

[0076] Step S11: Transmit the statistical result of the line segment number counting in step S10 to the judgment output module.

[0077] Working principle: For the face image sent by the image out-of-focus detection module, after operations such as canny edge extraction, Huffman line extraction and line segment filtering, line segment filtering is to filter so...

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Abstract

The invention discloses a screen edge-based mobile phone playback living body attack identification method. The method comprises an input module, an image out-of-focus detection module, a screen edgedetection module and a judgment output module; a face image in an image shot by a camera is extracted through the input module; the image out-of-focus detection module is used for carrying out image out-of-focus detection on the face image; the face image which is judged to be a clear image after the image out-of-focus detection is transmitted to the screen edge detection module for screen edge detection; and finally, a detection result is transmitted to the judgment output module, and the judgment output module performs playback living body attack and outputs a result. With the method adopted, the simultaneous processing of photo playback and video playback is finally realized.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to a mobile phone playback living body attack recognition method based on screen edges. Background technique [0002] In our daily life and production activities, face recognition technology is being used more and more widely. Compared with biometric features such as fingerprints and irises, facial features are the easiest to obtain. At present, the face recognition system has gradually begun to be commercialized, and is developing towards automation and unsupervised trends. At the same time, the demand for live attack recognition technology is also increasing. [0003] Liveness detection in a general sense is to judge whether the biometric information is obtained from a legitimate user with a living body when the biometric information is obtained from a legitimate user. The method of living body detection is mainly carried out by identifying the physiological informati...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06F21/32
CPCG06F21/32G06V40/172G06V40/45
Inventor 曾强
Owner CHINA SCI INTELLICLOUD TECH CO LTD