FM Model Based Fingerprint Reconstruction from Minutiae Template

Feng, Jianjiang; Jain, Anil K.

doi:10.1007/978-3-642-01793-3_56

Cited by 28 publications

(13 citation statements)

References 13 publications

(24 reference statements)

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“…The direction of singular points is not used here because it is a redundant feature as long as a few minutiae in the neighborhood of singularity are known, which is almost always the case in our data set. 1 As shown in Fig. 11, the reconstructed orientation field matches the original fingerprint very well, even if the singularity direction is not used.…”

Section: Reconstruction Of Orientation Fieldmentioning

confidence: 84%

“…Given a set of N fingerprint minutiae fx n ; y n ; n g, 1 n N, where ðx n ; y n Þ and n denote the location and direction of the nth minutia, respectively, the goal is to reconstruct the original fingerprint image modeled by (1). In terms of the FM model, this input means that we are given 1) the spiral phase and 2) the direction of instantaneous frequency of the composite phase at the locations of the N minutiae.…”

Section: Problem Statementmentioning

confidence: 99%

See 1 more Smart Citation

Fingerprint Reconstruction: From Minutiae to Phase

Feng

Jain

2011

IEEE Trans. Pattern Anal. Mach. Intell.

201

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Abstract-Fingerprint matching systems generally use four types of representation schemes: grayscale image, phase image, skeleton image, and minutiae, among which minutiae-based representation is the most widely adopted one. The compactness of minutiae representation has created an impression that the minutiae template does not contain sufficient information to allow the reconstruction of the original grayscale fingerprint image. This belief has now been shown to be false; several algorithms have been proposed that can reconstruct fingerprint images from minutiae templates. These techniques try to either reconstruct the skeleton image, which is then converted into the grayscale image, or reconstruct the grayscale image directly from the minutiae template. However, they have a common drawback: Many spurious minutiae not included in the original minutiae template are generated in the reconstructed image. Moreover, some of these reconstruction techniques can only generate a partial fingerprint. In this paper, a novel fingerprint reconstruction algorithm is proposed to reconstruct the phase image, which is then converted into the grayscale image. The proposed reconstruction algorithm not only gives the whole fingerprint, but the reconstructed fingerprint contains very few spurious minutiae. Specifically, a fingerprint image is represented as a phase image which consists of the continuous phase and the spiral phase (which corresponds to minutiae). An algorithm is proposed to reconstruct the continuous phase from minutiae. The proposed reconstruction algorithm has been evaluated with respect to the success rates of type-I attack (match the reconstructed fingerprint against the original fingerprint) and type-II attack (match the reconstructed fingerprint against different impressions of the original fingerprint) using a commercial fingerprint recognition system. Given the reconstructed image from our algorithm, we show that both types of attacks can be successfully launched against a fingerprint recognition system.

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Section: Reconstruction Of Orientation Fieldmentioning

confidence: 84%

Section: Problem Statementmentioning

confidence: 99%

Fingerprint Reconstruction: From Minutiae to Phase

Feng

Jain

2011

IEEE Trans. Pattern Anal. Mach. Intell.

201

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“…If the security of stored templates is compromised, the attacker can fabricate physical spoof samples to gain unauthorized access. Such efforts have been detailed in [11], [12] and [13]. The stolen templates can also be abused for other unintended purposes, e.g.…”

Section: Need For Template Protectionmentioning

confidence: 99%

Biometric Template Security using Dorsal Hand Vein Fuzzy Vault

Brindha¹

2012

J Biomet Biostat

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Biometric system is vulnerable to a variety of attacks aimed at undermining the integrity of the authentication process. More importantly template security is of vital importance in the biometric systems because unlike passwords, stolen biometric templates cannot be revoked. In this paper we describe the various threats that can be encountered by a biometric system. We specifically focus on attacks designed to elicit information about the original biometric data of an individual from the stored template. A few algorithms presented in the literature are discussed in this regard. We also examine techniques that can be used to deter or detect these attacks. Furthermore, we provide experimental results pertaining to a biometric system combining biometrics with cryptography, that converts dorsal hand vein templates into novel cryptographic structure called fuzzy vault. Initially, the pre-processing steps are applied to dorsal hand vein images for enhancement, smoothing and compression. Subsequently, thinning and binary encoding techniques are employed and then feature extracted. Then the biometric template and the input key are used to generate the fuzzy vault. For decoding, biometric template from dorsal hand vein image is constructed and it is combined with the stored fuzzy vault to generate the final key. The experimentation was conducted using dorsal hand vein databases and the FNMR and FMR values are calculated with and without noise.Citation: Brindha VE (2012) Biometric Template Security using Dorsal Hand Vein Fuzzy Vault. J Biomet Biostat 3:145.

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“…Recently, several research works showed that this reconstruction is possible. For example, fingerprint can, in fact, be reconstructed from a minutiae template (Cappelli et al, 2007), (Feng & Jain, 2009). …”

Section: Privacy Threats In Biometric Systemsmentioning

confidence: 99%