指纹识别新方法：Minutia Cylinder-Code技术

需积分: 5 91 浏览量更新于2024-07-09 收藏 4.96MB PDF 举报

"Minutia Cylinder-Code: A New Representation and Matching Technique for Fingerprint Recognition" 指纹识别技术是生物特征识别领域中的重要组成部分，尤其在安全和身份验证应用中扮演着核心角色。Minutia Cylinder-Code（MCC）是一种创新的指纹表示和匹配技术，旨在提高指纹识别的准确性和效率。该技术由Raffaele Cappelli、Matteo Ferrara和Davide Maltoni等人提出，并在2010年的IEEE Transaction on Software Engineering期刊上发表。 MCC方法的核心是将指纹的细节特征——即minutiae（纹线的终止、分叉和环形点）——转换成一种新的编码形式，这种编码考虑了指纹的三维结构。传统的方法通常仅依赖二维图像上的minutiae信息，而MCC引入了“cylinder”概念，模拟了皮肤表面的曲率，从而更准确地捕捉minutiae的方向和相对位置。在MCC中，每个minutia被表示为一个圆柱体，其轴线与minutia的方向对齐。圆柱体的半径反映了minutia附近的纹线密度，这样编码不仅包含了minutia的位置信息，还包含了关于纹线结构的额外信息。这种表示方式能够更好地处理因压力变化或采集设备的差异导致的指纹变形。匹配过程则基于这些编码的minutia圆柱体之间的距离和方向差异进行。通过计算两个指纹的MCC编码之间的相似度，可以确定它们是否来自同一手指。这种方法降低了匹配错误的可能性，提高了系统的鲁棒性。论文的作者们，如Matteo Ferrara和Davide Maltoni，都在持续研究深度学习架构和连续学习等相关的项目，这表明MCC技术可能与当前的深度学习方法有潜在的结合点，以进一步提升指纹识别的性能。 Minutia Cylinder-Code提供了一种更为精确且适应性强的指纹识别解决方案，对于生物特征识别领域的进步有着显著的贡献。它在提高识别准确性的同时，也增强了系统对各种环境因素变化的适应性，这对于安全关键的应用来说至关重要。

variable and depends on the local minutiae density; this can

lead to a more complex local matching, but, in principle, is

more tolerant against missing and spurious minutiae. Two

drawbacks of [7] are: 1) the absolute encoding of radial angles

(whose corresponding relative encoding is denoted as d

Fig. 7) that requires a sophisticated local matching and 2) the

missing directional difference between the central minutia

and the neighboring ones (denoted as d



in Fig. 7).

Furthermore, the approach in [7], like most fixed-radius

ones, can lead to border errors: In particular, minutiae close to

the local-region border in one of the two fingerprints can be

mismatched because local distortion or location inaccuracy

may cause the same minutiae to move out of the local region

in the other fingerprint. The technique proposed by Feng in

[12] does not suffer from the above drawbacks and can be

considered a state-of-the-art fixed-radius local matching

algorithm. In particular, the border problem is dealt with by

considering minutiae not close to the border as matchable and

minutiae near the border as should-be-matchable.

This paper introduces a novel minutiae-only local

representation aimed at combining the advantages of both

neighbor-based and fixed-radius structures, without suffer-

ing from their respective drawbacks.

The rest of this paper is organized as follows: Section 2

introduces the main motivations of this work and sum-

marizes the advantages of the new technique. Section 3

defines the minutiae local structures and discusses how to

measure the similarity between them. Section 4 proposes

four simple approaches to consolidate local similarities into

a global score. In Section 5, a large number of experiments

are reported to compare the new approach with three

“minutiae-only” implementations of the well-known ap-

proaches described in [6], [7], [12]. Finally, Section 6 draws

some concluding remarks.

2MOTIVATIONS AND CONTRIBUTIONS

The main motivations that induced us to design a new local

minutiae matching technique are:

. Need for accurate and interoperable minutiae-only algo-

rithms. Most of the fingerprint matching algorithms

rece ntly proposed exploit several extra features

besides minutiae; in [34], some statistics about the

features used by FVC2004 participants are reported.

Researchers have shown that combining features (at

least partially independent) is a very effective way to

improve accuracy. On the other hand, unlike

minutiae features, there is still no convergence on

standards that precisely define and encode these

extra features (one of the first attempts is CDEFFS

(2008) [35], but it is still at an early stage). The world-

wide large-scale deployment of fingerprint systems

demands a new generation of accurate and highly

interoperable algorithms and, for this reason, we

believe that minutiae-only matching algorithms

compliant to ISO/IEC 19794-2 (2005) [36] (or the

very similar ANSI/INCITS 378 (2004) [37]) will play

a central role in coming years. Furthermore, minu-

tiae-only templates also allow us to compress into a

few hundred bytes the salient fingerprint informa-

tion, thus enabling their storage on inexpensive

smart cards.

. Portability on light architectures. One effective way to

secure biometric applications against external attacks

is to confine the computation inside a closed system,

that is, a secure hardware platform such as a smart

card or a system-on-a-chip. Unfortunately, the

computational power of these low-cost secure plat-

forms is a hundred or thousand times lower than that

of a modern PC [1] and resource demanding

algorithms cannot be executed on board. Algorithms

designers then concentrated on the development of

simplified optimized versions, often based on local

minutiae matching techniques and precomputed

information. However, recent MINEX II results [38]

have shown that the best existing match-on-card

algorithms cannot compete with the corresponding

PC implementations and further research efforts are

necessary. Analogous conclusions were drawn in [34]

concerning the performance drop of the light cate-

gory with respect to the open category in FVC2004.

. Suitability for template protection techniques. Template

protection is currently receiving much attention

because of the great benefits it can provide (e.g.,

nonreversibility, diversity, and revocability) [39], [1].

Unfortunately, designing effective template protec-

tion techniques (e.g., fuzzy vault [40], [41], [42], [43],

[44]) without incurring a relevant accuracy drop is

very challenging and seems to require alignment

free, fixed-length, and noise-tolerant feature coding.

As of now, no fully satisfactory solution has been

proposed.

The local minutiae representation introduced in this paper is

based on 3D data structures (called cylinders), built from

invariant distances and angles in a neighborhood of each

minutia. Cylinders can be created starting from a subset of

mandatory features in standards like ISO/IEC 19794-2 (2005).

In particular, we use only the position and direction of the

minutiae, but not the minutiae type and the minutiae quality:

In fact, minutiae type is not a robust feature and the definition

of minutiae quality is not semantically clear in the standards

(and could lead to interoperability problems). Thanks to the

cylinder invariance, fixed-length, and bit-oriented coding,

some simple but effective metrics can be defined to compute

cylinder similarity. Four global-scoring techniques are then

proposed to combine local similarities into a unique global

score denoting the overall similarity between two finger-

prints. The main advantages of the new method, called

Minutia Cylinder-Code (MCC), are:

. MCC is a fixed-radius approach and therefore it

tolerates missing and spurious minutiae better than

nearest neighbor-based approaches.

. Unlike traditional fixed-radius techniques, MCC

relies on a fixed-length invariant coding for each

minutia and this makes the computation of local

structure similarities very simple.

. Border problems are gracefully managed without

extra burden in the coding and matching stages.

. Local distortion and small feature extraction errors

are tolerated thanks to the adoption of smoothed

functions (i.e., error tolerant) in the coding stage.

. MCC effectively deals with noisy fingerprint regions

where minutiae extraction algorithms tend to place

CAPPELLI ET AL.: MINUTIA CYLINDER-CODE: A NEW REPRESENTATION AND MATCHING TECHNIQUE FOR FINGERPRINT RECOGNITION 2129

剩余14页未读，继续阅读

superdont

粉丝: 3661
资源: 80

指纹识别新方法：Minutia Cylinder-Code技术

最新资源