Multimodal biometric systems provide a way to combat with the limitations of a unimodal biometric system which include less accuracy and user acceptability. In this context, a coding based approach called bit-transition code, is proposed for addressing the less-explored problem of designing a biometric-based authentication system by combining the iris and palmprint modalities. The approach is based on the encoding of binary transitions of symmetric and asymmetric parts of the Gabor filtered images at all pixel locations. Score-level fusion is employed to integrate the individual iris and palmprint performances. Experiments are carried out with three benchmark iris/palmprint databases, namely IITD iris and palmprint databases and PolyU palmprint database. The performance is measured in terms of receiver operator characteristics (ROC) curves and other metrics, like equal error rate and area under ROC curves. A comprehensive comparison, with several state-of-the-art approaches, is presented in order to validate the usefulness of the proposed approach.

多峰生物特征识别系统提供了一种克服单峰生物特征识别系统的局限性的方法，该局限性包括较低的准确性和用户可接受性。在这种情况下，提出了一种称为位转换码的基于编码的方法，以解决通过结合虹膜和掌纹模式来设计基于生物特征的认证系统的较少探讨的问题。该方法基于在所有像素位置对Gabor滤波图像的对称和不对称部分的二进制转换进行编码。分数级融合被用于整合各个虹膜和掌纹的表现。实验使用三个基准虹膜/掌纹数据库进行，即IITD虹膜和掌纹数据库以及PolyU掌纹数据库。性能是根据接收机操作员特性（ROC）曲线和其他度量标准来衡量的，例如相等的误码率和ROC曲线下的面积。为了验证所提出方法的实用性，本文提供了几种最先进方法的全面比较。