Biometric traits are frequently used by security agencies for automatic recognition of a person. There are numerous biometric traits used for person identification. In recent years, iris biometric trait becomes very popular and efficient in many security applications. However, biometric systems are prone to presentation attack. This attack is carried out by using spoofing of any biometric modality and present as a genuine trait. The effect of an artificial artifact of a humanoid iris could be in the form of contact lens attack and print attack make difficult the expected policy of a biometric liveness system. In this paper, the different and enhanced feature descriptor has been proposed i.e. Enhanced Binary Hexagonal Extrema Pattern (EBH_XEP) for forged iris detection. The relationship between the center pixel and its hexa neighbor has been explored by the suggested descriptor. The Proposed approach is tested on ATVS-FIr DB and IIIT-D CLI database for iris liveness detection and the results show better results for liveness detection in term of accuracy and average error rate.

安全机构经常使用生物特征来自动识别一个人。有许多用于人员识别的生物特征。近年来，虹膜生物特征在许多安全应用中变得非常流行和高效。然而，生物识别系统容易受到演示攻击。这种攻击是通过使用任何生物识别方式的欺骗来进行的，并作为真实特征呈现。人形虹膜的人工制品的影响可能是隐形眼镜攻击和打印攻击的形式，这使得生物识别活性系统的预期策略难以实现。在本文中，提出了不同的增强特征描述符，即增强型二元六边形极值模式（EBH _XEP) 用于伪造虹膜检测。建议的描述符已经探索了中心像素与其六边形邻居之间的关系。所提出的方法在 ATVS-FIr DB 和 IIIT-D CLI 数据库上进行了虹膜活体检测的测试，结果在准确度和平均错误率方面显示出更好的活体检测结果。