摘要
对活体虹膜提出了一种新的分窗小波包分解和Hamming距离匹配相结合的识别算法,在特征提取过程中利用了奇异值分解,有效地减少了代码长度,不影响识别效果.实验结果表明,该方法计算速度快,提取特征的效果好,可用于实际的身份鉴别系统.
For iris recognition, a new algorithm is proposed combining wavelet packet decompositions and Hamming distance. That SVD （Singular Value Decomposition） is utilized in feature extraction can effectively reduce the length of code, without affecting the recognition. The experimental results show that the arithmetic presented in this paper improves the efficiency and accuracy of iris recognition and is a practical arithmetic for personal identification.
出处
《石家庄职业技术学院学报》
2008年第2期1-4,共4页
Journal of Shijiazhuang College of Applied Technology
关键词
活体虹膜
识别
小波包分解
特征提取
HAMMING距离
live iris
identification
wavelet packets decompositions
feature extraction
hamming distance
