摘要
指纹增强是指纹识别预处理算法中的关键环节,对算法识别率起到关键的作用。本文提出了一种基于曲波域的指纹增强算法,将指纹图像在曲波域中分解为粗尺度系数和细尺度系数,并分别利用方向滤波器和软阈值函数进行增强和去噪。在曲波域中,利用方向滤波器对粗尺度系数进行增强,同时利用软阈值函数对细尺度系数进行去噪,这使它与传统的基于空域和基于频域的增强方法有本质的区别。在FVC2004指纹数据库上的实验结果表明,对于低质量的指纹图像,该算法比传统算法具有更好的增强和去噪效果,并且执行时间也更短。
Fingerprint enhancement is an essential preprocessing step and it is crucial for the efficiency of the fingerprint recognition algorithm.An algorithm based on curvelet domain is proposed.The input image is decomposed into coarse and fine scales coefficients,and directional filters and soft threshold function are applied fully to enhance image and reduce noise.In curvelet domain,directional filters are used to enhance coarse scales coefficients.Meanwhile,soft threshold function is used to reduce noise of fine scales coefficients,which is much different from the conventional methods based on spatial domain and frequency domain.Experiments are carried out on FVC2004 databases.For fingerprint with bad quality,the results indicate that the proposed algorithm can better enhance fingerprint images and reduce noise than traditional methods,and need less time.
出处
《光电工程》
CAS
CSCD
北大核心
2010年第8期98-103,共6页
Opto-Electronic Engineering
基金
国家自然科学基金项目(60574051)
关键词
指纹增强
曲波域
方向滤波器
软阈值函数
fingerprint enhancement
curvelet domain
directional filters
soft threshold function
