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Proceedings ArticleDOI

Fingerprint matching and similarity checking system using minutiae based technique

20 Mar 2015-pp 1-4
TL;DR: This proposed algorithm has been formulated based on minutiae points which examine n number of images and aims to monitor the matching and similarity for two or more fingerprint images simultaneously.
Abstract: Fingerprint matching is one of the most important problems in Automatic Fingerprint Identification System (AFIS). It has emerged as an effective tool for human recognition due to its uniqueness, universality and invariability. The significance of this work is to monitor the matching and similarity for two or more fingerprint images simultaneously. This proposed algorithm has been formulated based on minutiae points which examine n number of images.
Citations
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Journal ArticleDOI
TL;DR: The proposed model for enhancement of latent fingerprint and matching algorithm, which requires manually marked (ground-truth) ROI latent fingerprints, indicates that by fusing the proposed enhancement algorithm, the matching precision has fundamentally moved forward.
Abstract: Latent fingerprints are acquired from crime places which are utilized to distinguish suspects in crime inspection. In general, latent fingerprints contain mysterious ridge and valley structure with nonlinear distortion and complex background noise. These lead to fundamentally difficult problem for further analysis. Hence, the image quality is required for matching those latent fingerprints. In this work, we develop a model for enhancement of latent fingerprint and matching algorithm, which requires manually marked (ground-truth) ROI latent fingerprints. This proposed model includes two phases (i) Latent fingerprints contrast enhancement using type-2 intuitionistic fuzzy set (ii) Extract the minutiae and Scale Invariant Feature Transformation (SIFT) features from the latent fingerprint image. For matching, these algorithms have been figured based on minutiae and SIFT points which inspect n number of images and the scores are calculated by Euclidean distance. We tested our algorithm for matching, using some public domain fingerprint databases such as Fingerprint Verification Competition − 2004 (FVC-2004) and Indraprastha Institute of Information Technology (IIIT)-latent fingerprint which indicates that by fusing the proposed enhancement algorithm, the matching precision has fundamentally moved forward.

11 citations

Journal ArticleDOI
TL;DR: In this paper, a holistic cognitive conflict chain management framework (HCCCMF) is proposed to enhance quality customer service and supply chain management efficiency, which reduces interruption during the process and the cost of raw materials, labour, and energy.

10 citations

Journal ArticleDOI
TL;DR: Different accessible strategies and methods that have been utilized as a part of the past exploration concentrates on furthermore gives the bearing to further research in the different field of inactive unique finger impression application.
Abstract: Latent fingerprint has become more popular and attracted among the researchers in the recent days and it has been used widely in security such as India’s Aadhaar project, Department of Homeland Security’s US-VISIT program, the UK Border Agency, law enforcement and forensic applications. There have been different biometric traits that were used for matching to identify the person. While investigation a small number of accesses are recognized in latent fingerprint images because the fingerprint has own individuality. Latent fingerprint has been consisting some challenges in term of poor quality images, unclear texture and nonlinear distortion, appropriate matching algorithm and publicly available latent fingerprint database. Consequently, the study has considered and talked about different accessible strategies and methods that have been utilized as a part of the past exploration concentrates on furthermore gives the bearing to further research in the different field of inactive unique finger impres...

9 citations


Cites background from "Fingerprint matching and similarity..."

  • ...Adhiyaman and Ezhilmaran have extracted the local feature for fingerprint matching [4]....

    [...]

DissertationDOI
01 Jan 2017
TL;DR: Interoperability Analysis of Non-Contact Fingerprinting Devices vs. Contact-Based Fingerprints indicates that non-Contact fingerprinting devices are more compatible with contact-based fingerprinting systems.
Abstract: Interoperability Analysis of Non-Contact Fingerprinting Devices vs. Contact-Based Fingerprinting Devices

3 citations


Cites methods from "Fingerprint matching and similarity..."

  • ...There are a couple different methods of fingerprint matching but minutiae based fingerprint matching is the most popular method of fingerprint matching [65] [64] [66]...

    [...]

Proceedings ArticleDOI
01 Apr 2019
TL;DR: In this work, two publically available fingerprint datasets are utilized and the accuracy of fingerprint recognition is evaluated using the performance measures namely False Matching Ratio (FMR), False Non Matching ratio (FNMR) and Threshold.
Abstract: Recognition of human fingerprint verifies the match among two fingerprints in an automatic way and it is applied in various fields. The fingerprints are unique and its pattern will remain the same for the lifetime. The minutiae points represent the features of fingerprint that aids in the authentication of fingerprints. The main aim of this paper is to improve a scheme for verification of fingerprint by means of feature extraction and matching techniques. The initial step is preprocessing that involves image enhancement and binarization processes for the poor quality input fingerprint images. The fingerprint verification involves two main steps namely minutiae extraction and minutiae matching. The false minutiae points are to be removed and only efficient minutiae points are to be considered for further process. In this work, two publically available fingerprint datasets are utilized and the accuracy of fingerprint recognition is evaluated using the performance measures namely False Matching Ratio (FMR), False Non Matching Ratio (FNMR) and Threshold. From the results, it is clear that our work provides better results in fingerprint recognition.

2 citations


Cites background from "Fingerprint matching and similarity..."

  • ...Adhiyaman M and Ezhilmaran D [2] have proposed an advanced approach that involves minutiae and similarity checking technique for fingerprint matching....

    [...]

References
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Book
10 Mar 2005
TL;DR: This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.
Abstract: A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators

3,821 citations

Journal ArticleDOI
TL;DR: A filter-based fingerprint matching algorithm which uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode and is able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature.
Abstract: Biometrics-based verification, especially fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings of the traditional approaches to fingerprint representation. For a considerable fraction of population, the representations based on explicit detection of complete ridge structures in the fingerprint are difficult to extract automatically. The widely used minutiae-based representation does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Further, minutiae-based matching has difficulty in quickly matching two fingerprint images containing a different number of unregistered minutiae points. The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary (minutiae-based and filter-based) fingerprint information.

1,207 citations


"Fingerprint matching and similarity..." refers background or methods in this paper

  • ...[4], [3] and [12] these authors have described the performance of a minutiae based matching, verification and authentication using up to minutiae extraction step....

    [...]

  • ...LITERATURE SURVEY [3] improved the minutiae matching algorithm of Jain et al. (2000)....

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Proceedings ArticleDOI
01 Sep 2000
TL;DR: A minutiae matching algorithm which modified Jain et al.'s algorithm (1997) is proposed which can better distinguish two images from different fingers and is more robust to nonlinear deformation.
Abstract: Fingerprint matching is one of the most important problems in AFIS. In general, we use minutiae such as ridge endings and ridge bifurcation to represent a fingerprint and do fingerprint matching through minutiae matching. We propose a minutiae matching algorithm which modified Jain et al.'s algorithm (1997). Our algorithm can better distinguish two images from different fingers and is more robust to nonlinear deformation. Experiments done on a set of fingerprint images captured with an inkless scanner shows that our algorithm is fast and has high accuracy.

168 citations


"Fingerprint matching and similarity..." refers background or methods in this paper

  • ...[4], [3] and [12] these authors have described the performance of a minutiae based matching, verification and authentication using up to minutiae extraction step....

    [...]

  • ...[3] improved the minutiae matching algorithm of Jain et al....

    [...]

Proceedings ArticleDOI
01 Jul 2007
TL;DR: A novel method for Fingerprint recognition is considered using a combination of Fast Fourier Transform and Gabor Filters to enhancement the fingerprint image was captured using a UareU 4000 fingerprint reader of Digital Person, Inc.
Abstract: Fingerprint recognition is one of the most popular and successful methods used for person identification, which takes advantage of the fact that the fingerprint has some unique characteristics called minutiae; which are points where a curve track finishes, intersect with other track or branches off. Biometric identification systems using fingerprints patterns are called AFIS (Automatic Fingerprint Identification System). In this paper a novel method for Fingerprint recognition is considered using a combination of Fast Fourier Transform (FFT) and Gabor Filters to enhancement the fingerprint image was captured using a UareU 4000 fingerprint reader of Digital Person, Inc.

125 citations

Journal ArticleDOI
TL;DR: A new fingerprint matching algorithm which is especially designed for matching latents and 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.
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 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.

119 citations