在虹膜检测方法中易受到部分眼睑和睫毛的遮挡，从而降低虹膜识别的准确性,针对该问题，提出了一种基于2D-Gabor滤波器的虹膜噪音检测方法.该方法首先利用2D-Gabor检测归一化后虹膜图像中的眼睑和睫毛等噪音，然后记录噪音干扰区域，最后在匹配时去除虹膜代码中的干扰位来尽量避免噪音对于虹膜识别的影响.在CASIA(3.0)图库上进行实验的结果表明，采用噪音检测操作时正确识别率为99.02%，不采用噪音检测时正确识别率仅为98.46%.

The accuracy of iris recognition is lowered due to the shelter by part of eyelid and eyelash during the process of iris detection.A noise detection method using the 2D-Gabor filter is proposed for it.Firstly,the eyelid and eyelash are detected using 2D-Gabor filter in the normalized iris images.Then the noise regions are marked.Finally,the interferential bits in the iris codes are eliminated to avoid the noise effect to the recognition as much as possible.The experiments by using the CASIA(3.0)database are finished.The result shows that the recognition rate with the noise detection is 99.02%,but the recognition rate without the noise detection is 98.46%.