Face morphing versus face averaging: Vulnerability and detection
Face morphing versus face averaging: Vulnerability and detection
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面部变形与面部平均：漏洞和检测
DOI：
10.1109/btas.2017.8272742
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
C. Busch
中科院分区：
文献类型：
--
作者：
Ramachandra Raghavendra;K. Raja;S. Venkatesh;C. Busch
人脸识别系统（FRS）是已知的容易受到攻击的变形的脸。由于电子护照（电子通行证）中必须使用人脸特征，变形攻击在边境安全中引起了潜在的担忧。在本文中，我们分析了FRS的脆弱性，新的攻击使用平均脸。平均的脸是由对应于两个不同的主题的两个人脸图像的简单的像素级平均。我们基准的脆弱性的商业FRS传统的变形和平均为基础的面部攻击。我们进一步提出了一种新的算法的基础上，从颜色空间中提取的微观纹理特征的协作表示可靠地检测变形和平均的面部攻击的FRS。在新构建的163个受试者的变形和平均人脸图像数据库上进行了广泛的实验。数据库的建立考虑到护照签发的实际情况，通常接受申请人打印的护照照片，然后进一步扫描并存储在电子通行证中。因此，新构建的数据库被构建为具有打印扫描的真实、变形和平均的面部样本。实验结果表明，该方法在打印扫描变形和平均人脸数据库上的性能得到了提高。
The Face Recognition System (FRS) is known to be vulnerable to the attacks using the morphed face. As the use of face characteristics are mandatory in the electronic passport (ePass), morphing attacks have raised the potential concerns in the border security. In this paper, we analyze the vulnerability of the FRS to the new attack performed using the averaged face. The averaged face is generated by simple pixel level averaging of two face images corresponding to two different subjects. We benchmark the vulnerability of the commercial FRS to both conventional morphing and averaging based face attacks. We further propose a novel algorithm based on the collaborative representation of the micro-texture features that are extracted from the colour space to reliably detect both morphed and averaged face attacks on the FRS. Extensive experiments are carried out on the newly constructed morphed and averaged face image database with 163 subjects. The database is built by considering the real-life scenario of the passport issuance that typically accepts the printed passport photo from the applicant that is further scanned and stored in the ePass. Thus, the newly constructed database is built to have the print-scanned bonafide, morphed and averaged face samples. The obtained results have demonstrated the improved performance of the proposed scheme on print-scanned morphed and averaged face database.