计算机科学 ›› 2014, Vol. 41 ›› Issue (Z11): 110-115.

• 模式识别与图像处理 • 上一篇    下一篇

一种基于PCNN的改进型虹膜识别算法

金鑫,聂仁灿,周冬明   

  1. 云南大学信息学院 昆明650091;云南大学信息学院 昆明650091;云南大学信息学院 昆明650091
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金(61365001,61463052),云南省应用基础研究计划项目(2012FD003)资助

Improved Iris Recognition Algorithm Based on PCNN

JIN Xin,NIE Ren-can and ZHOU Dong-ming   

  • Online:2018-11-14 Published:2018-11-14

摘要: 基于脉冲耦合神经网络(PCNN),提出一种改进的虹膜识别算法。针对虹膜定位准确性这个研究点,引入形态学滤波对人眼图像进行去噪,以提高定位准确性。介绍了PCNN的模型,并对神经元震荡时间序列(OTS)进行统计分析,得出不同虹膜纹理具有唯一的神经元OTS。最后计算OTS的欧氏距离并进行分类,实现了虹膜识别的改进方法。在CASIA-Iris-Interval虹膜数据库中的实验结果验证了该方法的有效性,显示了它比传统算法具有更好的识别率和识别速度。

关键词: 虹膜识别,脉冲耦合神经网络,形态学滤波,特征匹配

Abstract: We proposed an improved iris recognition algorithm based on pulse coupled neural network (PCNN).Because the iris location is not enough accuracy,the morphological filtering method was applied to image denoising,which can improve recognize accuracy.And,by the statistical analysis of oscillation time sequences of the neurons,we concluded that different iris textures have the unique neurons oscillation time sequences (OTS).Finally we achieved the improved iris recognition algorithm through calculating and classifying the Euclidean distance of the OTS.In the iris database of CASIA-Iris-Interval,the experimental results show the effectiveness of the method proposed in this paper,and reveal that this method is better than traditional methods in recognition accuracy and recognition rate.

Key words: Iris recognition,PCNN,Morphological filtering,Feature matching

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