Fingerprint retrieval approach based on novel minutiae triplet features

Yuan, Baoxi; Su, Fei; Cai, Anni

doi:10.1109/btas.2012.6374573

Cited by 14 publications

(16 citation statements)

References 11 publications

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“…4 shows the performance of the proposed approach along with the performance of two approaches proposed in [6] and [21]. The results of the algorithm in [21] shown here are based on an executable file provided by the authors [21], applied to the same database and features used in our approach. The hit rate at a penetration rate of 39% reported in [6] is shown here for Feng and Jain 2008, which is based on a much smaller background database of 10,258 rolled prints.…”

Section: Indexing Resultsmentioning

confidence: 98%

“…Yuan et al [21] improved the performance of triplet indexing technique by using triplets to count the number of polygons of various sides. Like [6], they also used manually marked minutiae in the latents and automatically extracted minutiae in the rolled prints.…”

Section: Related Workmentioning

confidence: 99%

“…Since the objective of our study is indexing, we assume, similar to the studies in [6] and [21], that minutiae features have been marked in the latents by examiners. This is the case for the NIST SD27 database.…”

Section: Latentsmentioning

confidence: 99%

“…Features extracted from the triangles (triplets) formed by minutia points have been popular for fingerprint matching and indexing [7,2,13,21]. The basic features in [7] consist of the length of the sides of the triangles, the ridge count between every pair of minutiae in the triplet, and the angle between minutiae direction and the side of the triangle.…”

Section: Constrained Triplets Indexingmentioning

confidence: 99%

“…**Feng and Jain [6] only reported the hit rate at a single penetration rate of 39%. ***The hit rate of algorithm in [21] evaluated on the database used in this paper is 58.1% @ PR=10%. indexing technique is improved by applying a rotation constraint to the matched triplets.…”

Section: %mentioning

confidence: 99%

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Latent fingerprint indexing: Fusion of level 1 and level 2 features

Paulino

Liu

Cao

et al. 2013

2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)

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Fingerprints have been widely used as a biometric trait for person recognition. Due to the wide acceptance and deployment of fingerprint matching systems, there is a steady increase in the size of fingerprint databases in law enforcement and national ID agencies. Thus, it is of great interest to develop methods that, for a given query fingerprint (rolled or latent), can efficiently filter out a large portion of the reference or background database based on a coarse matching (or indexing) strategy. In this work, we propose an indexing technique, primarily for latents, that combines multiple level 1 and level 2 features to filter out a large portion of the background database while maintaining the latent matching accuracy. Our approach consists of combining minutiae, singular points, orientation field and frequency information. Experimental results carried out on 258 latents in NIST SD27 against a large background database (267K rolled prints) show that the proposed approach outperforms state-of-the-art fingerprint indexing techniques reported in the literature. At a penetration rate of 20%, our approach can reach a hit rate of 90.3%, with a five-fold reduction in the latent search (indexing + matching) time, while maintaining the latent matching accuracy.

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Section: Indexing Resultsmentioning

confidence: 98%

Section: Related Workmentioning

confidence: 99%

Section: Latentsmentioning

confidence: 99%

Section: Constrained Triplets Indexingmentioning

confidence: 99%

Section: %mentioning

confidence: 99%

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Latent fingerprint indexing: Fusion of level 1 and level 2 features

Paulino

Liu

Cao

et al. 2013

2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS)

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Partial fingerprint indexing: a combination of local and reconstructed global features

Zhou

Wang

et al. 2015

Concurrency and Computation

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Existing work on partial fingerprint indexing attempts to make full use of the extracted features from the partial segments, such as singular points, minutiae, orientation field, and ridge count. However, singular points may not exist in partial fingerprints, and none of these features can form a complete set of feature vectors that can be used for matching with those derived from the corresponding full fingerprints for indexing. Our former work on fingerprint orientation model based on two-dimensional Fourier expansion (FOMFE) coefficients-based fingerprint indexing and global orientation field reconstruction has demonstrated the possibility of reconstructing a global feature vector for partial fingerprint indexing. In this paper, we design some novel features of minutiae triplets in addition to some commonly used features to constitute the local minutiae triplet features. Experiments carried out on fingerprint verification competition (FVC) 2000 DB2a, FVC 2002 DB1a, and National Institute of Standards and Technology (NIST) SD 14 demonstrate the performance improvement after adding the new features to minutiae triplet feature set. We then propose to combine the reconstructed global feature and local minutiae triplet features to improve the performance of partial fingerprint indexing. Specifically, the minutiae triplet-based indexing scheme and the FOMFE coefficients-based indexing scheme are applied separately to generate two candidate lists; then, a fuzzy-based fusion scheme is designed to generate the final candidate list for matching. Experiments carried out on the public database NIST SD 14 show that the proposed approach can improve the performance that has been achieved by individual partial fingerprint indexing algorithms before fusion. SPECIAL ISSUE ON SECURITY AND PRIVACY IN BIG DATA: SPBD2014 2941 investigating partial fingerprint indexing is very important, which is the focus of this paper. We emphasize on the indexing performance in terms of partialness aspect rather than other aspects such as noise removal or texture separation.To facilitate the description, storage, and exchange of fingerprint information, the American National Standards Institute/National Institute of Standards and Technology (NIST) standard committee has recommended to describe fingerprints by a complete fingerprint feature set in three incremental levels. Level 1 features the following: friction ridge flows, pattern type, and general morphological information. These features can describe the fingerprint in a global view, such as the orientation field (OF). Level 2 features individual friction ridge paths and associated events, including bifurcations or endings (namely, minutiae). Minutiae are local features and are generally stable and highly distinctive. Level 3 features are friction ridge dimensional attributes, such as width, edge shapes, and pores. Currently, some level 3 features, such as pores, are only detectable on high quality and high resolution fingerprint images, and they are not major features that are used in today...

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Fingerprint Indexing Based on Combination of Novel Minutiae Triplet Features

Zhou

Wang

et al. 2014

Network and System Security

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Fingerprint retrieval approach based on novel minutiae triplet features

Cited by 14 publications

References 11 publications

Latent fingerprint indexing: Fusion of level 1 and level 2 features

Latent fingerprint indexing: Fusion of level 1 and level 2 features

Partial fingerprint indexing: a combination of local and reconstructed global features

Fingerprint Indexing Based on Combination of Novel Minutiae Triplet Features

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