序列虹膜图像质量的评价方法

提出一种使用二维图像复杂度和傅里叶频谱值作为评价因子、利用分类器进行序列虹膜图像质量评价的方法.首先利用投影和图像二值化方法得到虹膜图像评价区域,然后计算该区域的图像二维复杂度和傅里叶频谱值,以此作为特征并使用分类器选择最清晰的一幅图像用于身份认证.实验表明,在K-NN,BP神经网络和支持向量机等多种分类器中使用上述评价因子的结果均比较理想,可以挑选出符合要求的虹膜图像.

A Novel Approach to Iris Image Sequence Quality Assessment

A novel approach to iris image sequence quality assessment is proposed. Firstly, two assessment image blocks of each input iris image are extracted by using image projection and binarization method. Secondly, values of a two-dimension complexity measurement called 2D-CO complexity and Fourier frequency spectrum of the assessment image blocks are computed as features. Finally, a classifier uses these features to select the clearest iris image for personal identification. Experiments were made by using K-NN, BP neural netwoxk and support vector machine classifiers based on these features, and the experimental results are satisfactory.