基于AdaBoost算法与神经网络的快速虹膜检测与定位算法

针对目前已有的虹膜检测与定位算法的局限性, 设计了一组具有局部互联结构的神经网络, 结合AdaBoost算法用于虹膜的检测与定位. 算法主要有以下特征： 根据虹膜图像的特点设计了一组具有不同感受野和不同复杂程度的局部互联神经网络虹膜分类器; 应用AdaBoost算法整合神经网络分类器, 产生一个具有很强虹膜检测能力的总分类器; 采用级联结构提高系统的检测速度. 实验结果表明, 该方法具有极高的检测精度与速度, 有效地解决了包含大量脸部区域的虹膜检测与定位问题, 以及以往方法很难解决的白内障患者的虹膜检测和定位问题.

Fast Iris Detection and Localization Algorithm Based on AdaBoost Algorithm and Neural Networks

The present paper presents an iris detection and localization method based on AdaBoost algorithm and neural networks with local interconnection structures to overcome the limits in the current iris detection and localization algorithms.It has following features: according to the features of the iris image,we(designed) a set of local interconnection neural networks iris classifiers with different receptive fields and different complexity;we used AdaBoost algorithm to integrate neural networks classifiers to generate a chief classifier with powerful iris detection ability;cascade connection structure was applied to increasing the detection speed.Experimental results show that this algorithm has a very high detection accuracy and speed.It can solve the iris detection and localization problems efficiently in the case of with large face region and those of cataract patients.