Fast fingerprint identification for large databases

Fingerprint matching has emerged as an effective tool for human recognition due to the uniqueness, universality and invariability of fingerprints. Many different approaches have been proposed in the literature to determine faithfully if two fingerprint images belong to the same person. Among them, minutiae-based matchers highlight as the most relevant techniques because of their discriminative capabilities, providing precise results. However, performing a fingerprint identification over a large database can be an inefficient task due to the lack of scalability and high computing times of fingerprint matching algorithms.In this paper, we propose a distributed framework for fingerprint matching to tackle large databases in a reasonable time. It provides a general scheme for any kind of matcher, so that its precision is preserved and its time of response can be reduced.To test the proposed system, we conduct an extensive study that involves both synthetic and captured fingerprint databases, which have different characteristics, analyzing the performance of three well-known minutiae-based matchers within the designed framework. With the available hardware resources, our distributed model is able to address up to 400 000 fingerprints in approximately half a second. Additional details are provided at http://sci2s.ugr.es/ParallelMatching.     

基于局部纹线特性的直接灰度图指纹特征提取

指纹特征提取是鉴别个体生物特征的关键步骤。指纹特征提取新研究的一个方向是用直接灰度图纹线跟踪法来提取特征，以减轻传统方法对预处理的依赖性。但该方法也存在易发生漏判、误判、特征点类型错判等症结，其中特征点类型错判是一个主要问题。提出了依据局部纹线特性的方法，抑制直接灰度图纹线跟踪法的漏误判，特别是有效地解决了特征点——端点、分叉点——类型误判的问题。     

A novel algorithm of fingerprint encryption using minutiae-based transformation

This paper presents a novel algorithm of fingerprint encryption which transforms fingerprint minutiae and performs matching in the transformed form. If an encrypted template is compromised, it can be cancelled by choosing just another transformed template. In our algorithm, a circular region is constructed around each minutia and non-invertible transformation is applied to all regions but only transformed regions are stored in the database. The proposed algorithm improves the accuracy of verification compared to related fuzzy vault systems. Experimental results show the comparative performance of matching using both transformed and original data. We find that transformed matching also has an impressive accuracy and speed.     

A method using long digital straight segments for fingerprint recognition

In this paper, we proposed a new method using long digital straight segments (LDSSs) for fingerprint recognition based on such a discovery that LDSSs in fingerprints can accurately characterize the global structure of fingerprints. Different from the estimation of orientation using the slope of the straight segments, the length of LDSSs provides a measure for stability of the estimated orientation. In addition, each digital straight segment can be represented by four parameters: x-coordinate, y-coordinate, slope and length. As a result, only about 600 bytes are needed to store all the parameters of LDSSs of a fingerprint, as is much less than the storage orientation field needs. Finally, the LDSSs can well capture the structural information of local regions. Consequently, LDSSs are more feasible to apply to the matching process than orientation fields. The experiments conducted on fingerprint databases FVC2002 DB3a and DB4a show that our method is effective.     

基于脊线跟踪的指纹图细节提取算法

自动指纹识别和认证作为生物特征识别这一新兴领域的主流技术,有着重要的研究意义和广泛的应用前景。大多数自动指纹识别系统（AFIS）是基于细节特征点（minutiae)的匹配,因此细节特征点的提取是指纹图象处理中的关键环节。本文提出了一种基于脊线跟踪的指纹细节提取算法,能够直接从灰度指纹图象中有效地抽取出细节点及其相关信息。实表明,由于该算法减少了很多不必要的计算量,相对于传统的方法具有明显的速度优势,而且保持了较高的准确率。     

有效的指纹自动识别系统的设计与实现

系统地介绍了一个高效的指纹自动识别系统，又称AFIS（automatic fingerprint identification system)。介绍的指纹自动识别系统不同于以前的一些系统，因为在系统开发的过程中采用了一组有效的算法，经实验测试此系统效果很好。     

指纹图像预处理与特征提取

指纹图像预处理与特征提取是指纹识别的前提。提出一套基于方向滤波与模糊数学方法的指纹图像预处理算法，并给出了指纹特征提取及其后处理算法。指纹图像预处理首先求出指纹的方向场，然后根据方向场进行滤波，最后用模糊数学方法得到二值化图像。指纹特征提取则先从细化指纹图中得到特征点，并依据伪特征点的脊线与角度特征剔除伪特征点。     

Fingerprint minutiae extraction based on principal curves

It is important to extract minutiae of a fingerprint for the implementation of an auto fingerprint identification system. In this paper, the principal graph algorithm proposed by Kegl is used to obtain principal curves, which can be served as the skeletons of a fingerprint. Based on the obtained principal curves, a minutiae extraction algorithm is proposed to extract minutiae of the fingerprint. The experimental results indicate that principal curves obtained from the principal graph algorithm are smoother than the ones obtained from thinning algorithm, and the minutiae extracted by the proposed algorithm are more efficient.     

Fingerprint matching from minutiae texture maps

The fingerprint matching using the original FingerCode generation has proved its effectiveness but it suffers from some limitations such as the reference point localization and the recourse to the relative fingerprint pre-alignment stage. In this paper, we propose a new hybrid fingerprint matching technique based on minutiae texture maps according to their orientations. Therefore, rather than exploiting the eight fixed directions of Gabor filters for all original fingerprint images filtering process, we construct absolute images starting from the minutiae localizations and orientations to generate our weighting oriented Minutiae Codes. The extracted features are invariant to translation and rotation, which allows us avoiding the fingerprint pair relative alignment stage. Results are presented demonstrating significant improvements in fingerprint matching accuracy through public fingerprint databases.     

Fingerprint matching using OrientationCodes and PolyLines

Effectively incorporating various features with minutiae in fingerprint matching is a challenging task. This paper presents an algorithm to extract two novel discriminative features that describe three kinds of information: macro orientation patterns, micro ridge representation, and minutiae of fingerprints. These features, namely OrientationCodes and PolyLines, are fixed-length, easy to be measured in similarity, and effective in various stages of fingerprint matching, such as alignment, minutiae pairing, matching score computation, and matching rates fusion. In addition, the scheme of the proposed method has advantages of programming implementation, manipulating fingerprint matching much simpler and smoother at a high level. Experimental results on six data sets of FVC2002 and FVC2004 indicate the proposed algorithm not only achieves remarkably lower EERs, but also consumes significantly less computational times.