论文标题
紧凑的多尺度周期识别使用安全特征
Compact multi-scale periocular recognition using SAFE features
论文作者
论文摘要
在本文中，我们提出了一种基于特征扩展（安全）描述符对称评估的眼周识别的新方法，该方法编码图像关键点周围的各种对称曲线家族的存在。我们将巩膜中心用作特征提取的单关键点，突出显示了集中在这一唯一眼中的对象样的身份属性。如证明，这种歧视性能可以用简化的对称曲线进行编码。实验是使用用数码相机捕获的眼周图像的数据库进行的。我们针对参考周期特征测试系统，并以较小的特征向量（通过使用单个密钥点给出）实现最高性能。所有测试的系统还显示出采集距离和性能之间几乎稳定的相关性，并且在没有在相同距离处捕获注册和测试图像时，它们也能够很好地应对。还提供了可用系统之间的融合实验。
In this paper, we present a new approach for periocular recognition based on the Symmetry Assessment by Feature Expansion (SAFE) descriptor, which encodes the presence of various symmetric curve families around image key points. We use the sclera center as single key point for feature extraction, highlighting the object-like identity properties that concentrates to this unique point of the eye. As it is demonstrated, such discriminative properties can be encoded with a reduced set of symmetric curves. Experiments are done with a database of periocular images captured with a digital camera. We test our system against reference periocular features, achieving top performance with a considerably smaller feature vector (given by the use of a single key point). All the systems tested also show a nearly steady correlation between acquisition distance and performance, and they are also able to cope well when enrolment and test images are not captured at the same distance. Fusion experiments among the available systems are also provided.
