Yan Ping, Bowyer Kevin W
Department of Computer Science and Engineering, University of Notre Dame, Notre Dame. In 46556, USA.
IEEE Trans Pattern Anal Mach Intell. 2007 Aug;29(8):1297-308. doi: 10.1109/TPAMI.2007.1067.
Previous works have shown that the ear is a promising candidate for biometric identification. However, in prior work, the preprocessing of ear images has had manual steps and algorithms have not necessarily handled problems caused by hair and earrings. We present a complete system for ear biometrics, including automated segmentation of the ear in a profile view image and 3D shape matching for recognition. We evaluated this system with the largest experimental study to date in ear biometrics, achieving a rank-one recognition rate of 97.8 percent for an identification scenario and an equal error rate of 1.2 percent for a verification scenario on a database of 415 subjects and 1,386 total probes.
先前的研究表明,耳朵是生物特征识别的一个很有前景的对象。然而,在之前的工作中,耳朵图像的预处理存在人工步骤,并且算法不一定能处理由头发和耳环引起的问题。我们提出了一个完整的耳朵生物识别系统,包括在侧面视图图像中自动分割耳朵以及用于识别的3D形状匹配。我们用迄今为止耳朵生物识别领域最大规模的实验研究对该系统进行了评估,在一个包含415名受试者和总共1386个探测样本的数据库上,对于识别场景,获得了97.8%的一级识别率,对于验证场景,获得了1.2%的等错误率。