CASIA OpenIR  > 毕业生  > 硕士学位论文
指纹图像分析与识别
Alternative TitleFINGERPRINT IMAGE ANALYSIS AND RECOGNITION
郝瑛
Subtype工学硕士
Thesis Advisor谭铁牛 ; 王蕴红
2002-05-01
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword生物特征识别 指纹识别 融合多生物特征的身份鉴别 Biometrics Fingerprint Identification/verification System Multi-biometric Identity Verification System
Abstract随着社会的日益信息化,身份鉴别日益显示出其重要性和必要性。作为历 史最为悠久、最为人们所接受的指纹身份鉴别受到了广泛的关注。本文作者在模式识别国家重点实验室攻读硕士学位期间,主要从事指纹身份鉴别系统核心算法 的研究。本文的主要贡献在于:1.对指纹身份鉴别系统的核心算法给出了一个较为全面的综述; 2.指纹图像分析的目的是鲁棒地提取图像上的特征,通常可以分为指纹图 像增强和特征检测两个步骤。在图像增强方面,我们采用纹路宽度估计 实现了自适应指纹增强,并在此基础上比较了三种典型指纹增强滤波器 的性能;在指纹特征检测方面,我们提出了一种指纹后处理的实现方法, 该方法在精度和速度上都能够达到实时系统的要求;最后,我们还给出 了一种结合局部方向方差和Poincaré Index的奇异点检测方法以及中心 点的精确定位方法。 3.在指纹特征匹配方面,我们提出了一种基于误差扩散的指纹匹配算法。 该方法能够自适应地根据已匹配点的误差估计待匹配点的误差,从而实 现补偿非线性形变的目的。该方法在NIST-24和NLPR数据库上分别取 得了2.05%和1.5%的等错误率。 4.在多生物特征融合的身份鉴别系统方面,我们给出了一个融合声纹和指 纹的身份验证系统的实例。实验结果表明,通过适当的融合算法,结合 多种生物特征能够很好地提高系统的性能。
Other AbstractIn today's complex, geographically mobile and increasingly electronically inter-connected information society, accurate personal identification is becoming more and more important and difficult. The use of fingerprint as a biometric is both the oldest mode of automatic personal identification and the most prevalent in use today. This thesis focuses on algorithms related to Automatic Fingerprint Identification Systems (AFIS), and the main contributions are as follows: 1. A comprehensive survey is presented on the state of the art of the core algorithms related to AFIS as well as some system issues (such as the architecture and technical evaluation of biometrics system). 2. The ultimate objective of fingerprint image analysis is to achieve the most reliable features and can be divided into two consecutive parts: pre-processing and feature extraction. In pre-processing, we proposed a projection analysis method to establish a reliable estimation of ridge width map. Based on this information, we compared the performance of three typical fingerprint filters and meaningful results are obtained. As to feature extraction, we developed an effective implementation of fingerprint post-processing, which meets the accuracy and response-time requirements of real-time systems. Finally, we proposed a singularity detection algorithm which integrate, s local orientation variance and Poincaré Index. 3. A novel error propagation based fingerprint matching algorithm is proposed, which is capable of adaptively tracking the nonlinear deformation commonly observed in fingerprint images. The main idea of this approach is to estimate the errors of the unmatched minutiae according to those of the matched minutia pairs. To prevent the matching procedure from being misguided by mismatched minutia pairs, a flexible diffusion scheme is developed. The EERs of 2.05% and 1.5% are obtained on NIST-24 and NLPR databases respectively. 4. A prototype multi-biometric identity verification system, which integrates both voice print and fingerprint information, is developed. The outputs of two subsystems are regarded as a two-dimensional feature vector and linear discriminant function based on Fisher criteria is used in the integrated classifier. Experimental results demonstrate that our decision fusion scheme performs well.
shelfnumXWLW639
Other Identifier639
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6765
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
郝瑛. 指纹图像分析与识别[D]. 中国科学院自动化研究所. 中国科学院研究生院,2002.
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