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基于机器学习的虹膜图像质量确定方法
谭铁牛; 孙哲南; 李星光
2011-12-29
Date Available2012-07-11
CountryCN
Subtype发明
Abstract一种基于机器学习的虹膜图像质量确定方法,包括步骤:对虹膜图像进行预处理;提取虹膜图像质量因子;利用多高斯模型拟合单一质量因子正负样本的概率密度函数;利用改进的Neyman-Pearson方法融合得到虹膜图像质量分数;通过假设检验的方法确定最优质量等级数。本发明针对离焦、运动模糊和斜眼,提出了鲁棒的检测方法,引入了Neyman-Pearson方法融合多质量因子,形成质量分数,最终通过假设检验的方法得到了具有统计意义的图像质量等级。本发明可用于虹膜图像采集时的质量确定,以及针对识别算法的性能预测。
Patent NumberCN201110451829.X
Status授权
Document Type专利
Identifierhttp://ir.ia.ac.cn/handle/173211/8647
Collection智能感知与计算研究中心
Affiliation中国科学院自动化研究所
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
谭铁牛,孙哲南,李星光. 基于机器学习的虹膜图像质量确定方法. CN201110451829.X[P]. 2011-12-29.
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