智能手机实时人脸认证的防欺骗研究

IF 0.5 4区计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

Journal of Information Science and Engineering Pub Date : 2021-01-01 DOI:10.6688/JISE.20210537(3).0007

Tz-Chia Tseng, Teng-Fu Shih, C. Fuh

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引用次数: 0

摘要

该方法仅使用普通智能手机的RGB (Red, Green, Blue)前置摄像头，无需深度摄像头或红外热传感器，即可验证输入图像是否来自真实用户或欺骗攻击，包括纸质照片、数码照片和视频。我们首先通过单镜头多盒检测器捕获输入视频流中每帧的实时人脸，然后经过一定的数据增强后输入到我们设计的卷积神经网络中，最终得到训练良好的欺骗人脸分类器。最后，我们比较了Parkin和Grinchuk的结果，使用数据集CASIASURF[1]，并比较了CASIA-SURFT数据集中的vgg16、InceptionNet、ResNet、DenseNet和MobileNet的结果。

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Anti-Spoofing of Live Face Authentication on Smartphone

Our proposed method is capable of authenticating the input image is from real user or spoofing attack, including paper photograph, digital photograph, and video, using only the Red, Green, Blue (RGB) frontal camera of common smart phone, without the help of depth camera or infrared thermal sensor. We first capture live faces in each frame of input video streams by single shot multi-box detector then feed into our designed convolution neural network after certain data augmentation and finally obtain a well-trained spoof face classifier. Finally, we compared to Parkin and Grinchuk’s results, using dataset CASIASURF[1], and compare the result of vgg16, InceptionNet, ResNet, DenseNet and MobileNet in CASIA-SURFT dataset.

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来源期刊

Journal of Information Science and Engineering 工程技术-计算机：信息系统

CiteScore

2.00

自引率

0.00%

发文量

审稿时长

8 months

期刊介绍： The Journal of Information Science and Engineering is dedicated to the dissemination of information on computer science, computer engineering, and computer systems. This journal encourages articles on original research in the areas of computer hardware, software, man-machine interface, theory and applications. tutorial papers in the above-mentioned areas, and state-of-the-art papers on various aspects of computer systems and applications.