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    基于平移不变预处理的小波变换的虹膜识别算法

    Iris Recognition Based on Wavelet Transform with Shift Invariance Preprocessing

    • 摘要: 普通的离散小波变换具有平移敏感性,无法稳定地表示小波域下的虹膜特征.为了减弱虹膜图像的旋转变化对小波分解系数的影响,提出一种基于虹膜的方向能量分布序列的平移不变预处理方法,以校正虹膜纹理图像角度旋转变化.通过对小波变换系数进行阈值化处理,以双位二进制形式编码虹膜特征.在验证模式下,采用加权Hamming距对未知虹膜进行多模板匹配得出识别结果.基于虹膜图像库进行比对实验,结果表明,增强了小波变换编码虹膜特征的可用性,能够有效地进行虹膜识别.

       

      Abstract: The normal discrete wavelet transform is sensitive to the initial position of asignal and can not be used to extract stable iris features. To weaken the negative effect on the recognition result due to the shift sensitivity of the wavelettransform,a shift invariance preprocessing method based on directional energy distribution sequences is proposed to correct the angular rotation of different iris textures, which corresponds to the horizontal shift of normalized iris blocks. A threshold scheme is then performed to transform all the wavelet coefficients into a binary vector to represent iris features. In verification mode, the weighted Hamming distance classifier is finally adopted to perform multi-template matching to identify the unknown feature vector. Comparison experiments show that the proposed algorithm enhances the availability of iris feature representation by wavelet transform and leads to a good performance of iris recognition.

       

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