基于多方向Gabor滤波器和Adaboost的虹膜识别方法

A Multi-orientation Gabor Filter and Adaboost Based Iris Recognition Method

结合虹膜的整体和局部纹理信息,提出一种新的虹膜特征提取和识别方法.首先将归一化虹膜进行分块,然后利用多方向Gabor滤波器分别对整个虹膜和虹膜子块进行编码并生成特征向量,最后使用Adaboost算法训练得到识别性能较好的特征用于识别.在数据库CASIA-IrisV3-Lamp中实验,该算法的识别率达到99.85%;在包含大量低质量虹膜图像的数据库NICE:Ⅱ中实验,算法也具有较好的识别性能,表明了算法既能充分地利用虹膜的纹理信息,又能有效地减少噪声的影响.

A new method for iris feature extraction and recognition was proposed based on the global and local texture information of iris. The normalized iris was divided first. Then the multi- orientation Gabor filters were used to encode the whole iris and sub-block iris, and the feature vector was constructed. Furthermore, the Adaboost algorithm was adopted to choose some features whose recognition performances are good. The results of the experiments carried out on CASIA-IrisV3-Lamp database indicate that the accuracy of recognition reaches up to 99.85%. Moreover, the algorithm has good recognition performance on the NICE： ]] database which contains a large amount of poor quality images. It shows that the method not only can take fully advantage of the texture information of iris, but also can reduce efficiently the effect of noises.