基于过零检测的虹膜特征提取算法

Iris Feature Extracting Algorithm Based on Zero-Crossing Detection

该文针对虹膜图像不理想、噪声影响较大情况下,虹膜识别率下降的问题,提出了一种基于过零检测的虹膜特征提取算法,利用过零检测算子与信号局部的相关性提取虹膜纹理特征,并根据所得的系数进行符号编码形成二值特征模板,最后采用相似度进行模式分类。仿真结果表明,该算法能够提取不理想虹膜图像的稳定特征,提高识别率。

In order to resolve the problem of recognition rate decrease in condition of unideal iris image and local noise, an iris feature extracting algorithm based on local zero-crossing detection is presented in this paper. This method extracts iris texture feature by using local relativity of zero-crossing operator and texture signal, then encodes iris texture to form iris feature template depend on coefficient sign, finally classifies different patterns using similarity. Simulation results show that stable feature of unideal iris image can be extracted and high recognition rate can be achieved using the algorithm.