基于逐阶共识计算的虚假物理身份属性检测方法

Fake Physical Identity Attributes Detection Method Based on Order-of-Consensus-Calculation

通过使用面具、变更指纹等技术,个人可以轻松冒充他人,这给物理身份识别带来巨大挑战。针对身份识别过程中属性伪造的问题,提出了一种基于逐阶共识计算的虚假物理身份属性检测方法。该方法首先进行身份识别;然后利用错误识别结果近邻关系的差异,逐阶分析得到共识身份;最后分析共识身份在识别结果中的排序,以检测虚假属性。在人脸、指纹和声纹数据库上的实验结果表明,与多数表决方法相比,本文方法能有效检测出虚假物理身份属性,并具有更高的准确率。

Individuals could easily impersonate others by wearing masks or using altered fingerprints or other technologies,which brings enormous challenges to physical identity recognition.Aiming at the existence of fake attributes during identification,a method based on order-of-consensus-calculation is presented for fake physical identity attributes detection.It first executes identity recognition,then uses the differences of proximity relationship of misidentification result to obtain consensus identity with analysis in order,finally detects fake attributes by analyzing the rank of consensus identity in the recognition result.Experimental results on the face,fingerprint and voiceprint databases demonstrate that compared with the majority decision method,the proposed method can detect fake physical identity attributes effectively and has a higher accuracy.