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摘 要
生物识别技术（Biometric Identification Technology）是利用人的生理特征的唯一性以及不可以复制性来进行身份验证的解决方案。与传统的密码相比，人的生物特征具有很多优势，可以大幅度提高安全性能。指纹识别技术是生物识别中较为成熟的一种。它在很多领域得到广泛的应用，如罪犯鉴定，访问控制，自动银行等。
指纹识别系统的主要内容包括：指纹采集，指纹识别，指纹验证，指纹分类。首先指纹图像分析是指纹识别的基础，在指纹识别系统中占有重要位置，它通过指纹图像的增强，图像二值化及细化，指纹方向场的计算等来获取指纹信息。接着通过对指纹特征的提取，剔除虚假的特征，再对细节特征进行匹配，从而最终实现指纹的鉴证和识别。
本文在图像增强部分利用指纹增强算法对图像进行滤波增强，改善图像质量。然后对指纹图像进行细化，消除噪声，得到冗余指纹信息，为后面的特征提取和匹配工作打下基础。本文综合有关文献，利用点集模型，在弹性匹配的条件下对指纹匹配的算法进行了一定的研究。这种算法能够不通过其他的辅助手段找出提取出的指纹与已存指纹模板之间的联系。并且它能修正和补偿由于指纹的非线性变形和位置不精确所造成的误差。并用matlab根据算法进行仿真，可以看到增强后的指纹图像有明显的变化。
关键词：指纹识别，指纹特征，图像增强，方向场，特征匹配
Abstract
Biometric Identification Technology is one of the personal identification methods. It makes use of the character, which is exclusive in the physiology.
Compared with the conventional passwords, it has many advantages. It can improve the capability of the safety. Fingerprint verification is one of the most reliable personal identification methods. It plays a very important role in many fields, such as criminal identification, access control, and ATM card verification.
The main content of the Fingerprint verification system are: Fingerprint Acquisition, Fingerprint verification, Fingerprint Identification. Fingerprint Classification. First, the analysis of the Fingerprint is the basic of the system. It gets the minutia of the fingerprint by three steps: first, fingerprint enhancement; second, ridge extraction and ridge thinning, third, get rid of the bogus minutia and then minutia match无忧论文 【http://www.uklunwen.com】ing. At last it realizes the verification and identification.
In his paper, it describes fingerprint enhancement algorithm first to improve the quality of the fingerprint images, and then describes the algorithms of minutia extraction and minutia matching. In the end, it uses Matlab to do some emulators. We can see that the images enhanced are much more clear than before. For minutia matching, it describes an alignment-based elastic matching algorithm. This algorithm is capable of finding the correspondences between minutiae in the input image and the stored template without resorting to exhaustive search and has the ability of adaptively compensating for the nonlinear deformations and inexact pose transformations between fingerprints with high accuracy.
Key words: Fingerprint verification, fingerprint enhancement, orientation field, minutia matching
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