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Automated personal identification system based on human iris analysis

机译:基于虹膜分析的自动个人识别系统

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In general, a typical iris recognition system includes iris imaging, iris liveness detection, iris image quality assessment, and iris recognition. This paper presents an algorithm focusing on the last two steps. The novelty of this algorithm includes improving the speed and accuracy of the iris segmentation process, assessing the iris image quality such that only the clear images are accepted so as to reduce the recognition error, and producing a feature vector with discriminating texture features and a proper dimensionality so as to improve the recognition accuracy and computational efficiency. The Hough transform, polynomial fitting technique, and some morphological operations are used for the segmentation process. The phase data from 1D Log-Gabor filter is extracted and encoded efficiently to produce a proper feature vector. Experimental tests were performed using CASIA iris database (756 samples). These tests prove that the proposed algorithm has an encouraging performance.
机译:通常,典型的虹膜识别系统包括虹膜成像,虹膜活动度检测,虹膜图像质量评估和虹膜识别。本文提出了一种针对最后两个步骤的算法。该算法的新颖性包括:提高虹膜分割过程的速度和准确性;评估虹膜图像质量,以便仅接受清晰的图像,以减少识别误差;以及生成具有可辨别纹理特征和适当特征的特征向量。从而提高识别精度和计算效率。 Hough变换,多项式拟合技术和一些形态运算用于分割过程。一维Log-Gabor滤波器的相位数据被提取并有效编码,以产生适当的特征向量。使用CASIA虹膜数据库(756个样本)进行了实验测试。这些测试证明了所提出的算法具有令人鼓舞的性能。

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