指纹图像细化是自动指纹识别的关键技术之一，图像细化效果对自动指纹识别系统的性能有着重要的影响。
Fingerprint thinning is a key part in the automatic fingerprint identification technology. The fingerprint thinning result has an important influence of the AFIS.
实验结果表明：该算法能有效地判断半导体指纹传感器的图像质量，有助于提高自动指纹识别系统的整体性能。
Experimental results show that this algorithm is quite effective in fingerprint image quality estimation, and help to improve the performance of the fingerprint identification system.
主要介绍基于ARM9的嵌入式自动指纹识别系统的实现方法，并具体说明了该系统的硬件组成部分和软件组成部分。
This paper introduces an implementation method of Embedded Automatic Fingerprint Identification Systerm(AFIS), dealing mainly with hardware components and software modules based on ARM9.
指纹增强对于提高细节特征的准确率以及整个自动指纹识别系统的性能都有着十分重要的意义。
Fingerprint enhancement is important for improving the accuracy of minutia extraction, even for the total automated fingerprint identification system.
本文对自动指纹识别系统整个过程中的一些关键算法进行了讨论和改进。
This paper discusses and improves the key algorithms of auto fingerprint identification system.
研究了自动指纹识别系统中的指纹校准算法。
In this paper, the fingerprint alignment algorithm in the automatic fingerprint identification system is studied.
预处理是指纹自动识别系统中非常关键的部分，它直接影响着指纹识别的最终效果。
Preprocessing plays a key role in the fingerprint identification system, which directly influences the final ac-curacy of fingerprint identification.
本文在综合分析近年来国内外有关自动指纹识别技术研究成果的基础上，对自动指纹识别系统的算法进行了研究。
Based on latest extensive discourses and technology journals in this field, the dissertation is trying to make studies on algorithms of AFIS.
第二章详细分析了自动指纹识别系统的结构及工作流程，并对嵌入式自动指纹识别系统专门进行了研究。
In the second chapter, the structure and work procedure of AFIS, especially embedded AFIS, are analyzed in detail.
本文针对自动指纹识别系统的各个组成环节进行了研究，主要包括指纹图像预处理、指纹特征提取、指纹特征匹配三个部分。
The components of automatic fingerprint recognition system are investigated in this paper which mainly include preprocessing, fingerprint feature extraction and fingerprint feature matching.
本文针对自动指纹识别系统的各个组成环节进行了研究，主要包括指纹图像预处理、指纹特征提取、指纹特征匹配三个部分。
The components of automatic fingerprint recognition system are investigated in this paper which mainly include preprocessing, fingerprint feature extraction and fingerprint feature matching.
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