Latent Fingerprint Matching Using Descriptor-Based Hough Transform

Paulino, Alessandra A.; Feng, Jianjiang; Jain, Anil K.

doi:10.1109/tifs.2012.2223678

Cited by 115 publications

(71 citation statements)

References 37 publications

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“…As a result, the implementation of the algorithms that requires the following features needs to be changed. Having discussed these Java Card features, it is common for most HT-based algorithms to require for example, multidimensional arrays [11] - [15]. Therefore, the research presented in analyses each algorithm based on how many does it require.…”

Section: Defining Problem Statementmentioning

confidence: 99%

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Analysis of Computational Complexity for HT-Based Fingerprint Alignment Algorithms on Java Card Environment

Mlambo¹,

Shabalala²,

Nelwamondo³

2015

Computer Science &Amp; Information Technology ( CS &Amp; IT )

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In this paper, implementations of three Hough Transform based fingerprint alignment algorithms are analyzed with respect to time complexity on Java Card environment. Three algorithms are: Local Match Based Approach (LMBA), Discretized Rotation Based Approach (DRBA), and All Possible to Match Based Approach (APMBA). The aim of this paper is to present the complexity and implementations of existing work of one of the mostly used method of fingerprint alignment, in order that the complexity can be simplified or find the best algorithm with efficient complexity and implementation that can be easily implemented on Java

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Section: Defining Problem Statementmentioning

confidence: 99%

“…In the DRBA approach, it is common to consider all given points from I and T as possible corresponding points [11]. In addition, by checking if the direction difference of minutiae orientation is less than a defined threshold [12].…”

Section: Discretized Rotation Based Approachmentioning

confidence: 99%

Analysis of Computational Complexity for HT-Based Fingerprint Alignment Algorithms on Java Card Environment

Mlambo¹,

Shabalala²,

Nelwamondo³

2015

Computer Science &Amp; Information Technology ( CS &Amp; IT )

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“…In this section, we review related work in four areas: published research on full fingerprint matching 1 , published research on latent fingerprint matching, evaluation of latent fingerprint technologies (ELFT), and evaluation of latent examiners.…”

Section: Related Workmentioning

confidence: 99%

“…9 shows the histograms of NFIQ quality [37] of the rolled prints which have corresponding latents in NIST SD27 and in WVU databases (258 and 449 rolled prints, respectively). NFIQ defines five quality levels in the range [1,5] with 1 indicating the highest quality.…”

Section: ) West Virginia University Latent Database (Wvu Lfd)mentioning

confidence: 99%

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Latent fingerprint matching using descriptor-based hough transform

Paulino

Feng

Jain

2011

2011 International Joint Conference on Biometrics (IJCB)

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Abstract-Identifying suspects based on impressions of fingers lifted from crime scenes (latent prints) is a routine procedure that is extremely important to forensics and law enforcement agencies. Latents are partial fingerprints that are usually smudgy, with small area and containing large distortion. Due to these characteristics, latents have a significantly smaller number of minutiae points compared to full (rolled or plain) fingerprints. The small number of minutiae and the noise characteristic of latents make it extremely difficult to automatically match latents to their mated full prints that are stored in law enforcement databases. Although a number of algorithms for matching full to full fingerprints have been published in the literature, they do not perform well on the latent to full matching problem. Further, they often rely on features that are not easy to extract from poor quality latents. In this paper, we propose a new fingerprint matching algorithm which is especially designed for matching latents. The proposed algorithm uses a robust alignment algorithm (descriptor-based Hough transform) to align fingerprints and measures similarity between fingerprints by considering both minutiae and orientation field information. To be consistent with the common practice in latent matching (i.e. only minutiae are marked by latent examiners), the orientation field is reconstructed from minutiae. Since the proposed algorithm relies only on manually marked minutiae, it can be easily used in the law enforcement applications. Experimental results on two different latent databases (NIST SD27 and WVU latent databases) show that the proposed algorithm outperforms two well optimized commercial fingerprint matchers. Further, a fusion of the proposed algorithm and commercial fingerprint matchers leads to improved matching accuracy.

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