Near-infrared face vivo detection method and system

A technology of living body detection and infrared human beings, which is applied in deception detection, equipment, character and pattern recognition, etc., can solve the problems of long training time, easy disappearance, and lack of robustness, etc., to reduce the amount of parameters, facilitate transplantation, reduce small size effect

Inactive Publication Date: 2018-11-27
NORTHEASTERN UNIV
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Problems solved by technology

[0003] The existing research on live face detection algorithms can be roughly divided into two categories: static detection algorithms and dynamic detection algorithms, but these two algorithms have a single method and cannot accurately describe the characteristics of li

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  • Near-infrared face vivo detection method and system
  • Near-infrared face vivo detection method and system
  • Near-infrared face vivo detection method and system

Examples

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Embodiment 1

[0054] Use the OpenCV code to call the near-infrared camera to collect images of personnel, collect 5 images per second and save them locally. By collecting close-range images of personnel, the collected personnel need to have faces such as front, side, and blinking eyes. A large number of images are collected as The original positive sample. Then, the original positive sample image should be printed on paper, and the infrared camera should be used for secondary acquisition. In order to enrich the data set, the collected photos need to have various transformation forms, and the collected image is used as the original negative sample. The original positive and negative samples such as Figure 4 , 5 shown. During the secondary acquisition, 5 methods were used: including vertical and horizontal forward and backward movement; left and right rotation along the vertical axis; forward and backward rotation along the horizontal axis; bending in and out along the vertical axis; in an...

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Abstract

The invention provides a near-infrared face vivo detection method. The method comprises the steps: S1, original positive samples and original negative samples are collected through a near-infrared camera, S2, preprocessing the original samples through the face region detection model in deep learning so as to select the standard face images which can be fed into the network to be trained; S3, constructing a training set and a test set from the selected positive and negative samples suitable for network training and substituting the samples into the lightweight convolutional neural network to betrained so as to obtain the trained face vivo detection model; and S4, the images to be judged collected by the near-infrared camera are inputted into the face vivo detection model for vivo judgment.The parameter quantity is reduced through the lightweight convolutional neural network, the size of the model is reduced, transplanting to the mobile terminal is more convenient and thus the method and the system can be widely popularized in the field of biological characteristic identification technology for the above reasons.

Description

technical field [0001] The invention relates to the technical field of biological feature recognition, in particular to a near-infrared human face living body detection method and system. Background technique [0002] With the rapid development of computer technology, the recognition rate of biometric recognition technology is also steadily increasing. Among various recognition technologies, face recognition is characterized by high security, good stability, naturalness, non-contact and concealment. And other advantages, are widely used in criminal investigation, monitoring system and security detection technology. Fake face attack refers to illegal users attempting to obtain system access by providing false data, that is, duplicating legitimate user pictures, videos, and 3D molds. Among them, duplicating legitimate user pictures and videos to intercept user pictures, due to low cost and simple implementation, has become The main attack method used by illegal intruders. For...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/16G06V40/45G06F18/214
Inventor 王浩然张奔奔
Owner NORTHEASTERN UNIV
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