Proceedings ArticleDOI
Quality Induced Fingerprint Identification using Extended Feature Set
Mayank Vatsa,Richa Singh,Afzel Noore,Sanjay Singh +3 more
- pp 1-6
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TLDR
Experiments conducted on a high resolution fingerprint database containing rolled, slap and latent images indicate that the novel algorithm presented offers significant benefits for fast fingerprint identification.Abstract:
Automatic fingerprint identification systems use level-1 and level-2 features for fingerprint identification. However, forensic examiners utilize inherent level-3 details along with level-2 features. Existing level-3 feature extraction algorithms are computationally expensive to be used for identification. This paper presents a novel algorithm for fast level-3 feature extraction and identification. The algorithm starts with computing local image quality score using redundant discrete wavelet transform. A fast curve evolution algorithm is then used to extract four level-3 features namely, pores, ridge contours, dots, and incipient ridges. Along with level-1 and level-2 features, these level-3 features are used in a Delaunay triangulation based indexing algorithm. Finally, quality-based likelihood ratio is used to further improve the identification performance. Experiments conducted on a high resolution fingerprint database containing rolled, slap and latent images indicate that the algorithm offers significant benefits for fast fingerprint identification.read more
Citations
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Journal ArticleDOI
Improving Automated Latent Fingerprint Identification using Extended Minutia Types
TL;DR: This work explores ways to improve rank identification accuracies of AFIS when only a partial latent fingerprint is available and proposes a method that exploits extended fingerprint features (unusual/rare minutiae) not commonly considered in AFIS.
Proceedings ArticleDOI
Towards touchless pore fingerprint biometrics: A neural approach
TL;DR: This paper proposes the first innovative method in the literature able to extract Level 3 features, in particular sweat pores, from fingerprint images captured with a touchless acquisition using a commercial off-the-shelf camera.
Journal ArticleDOI
Improving Automated Latent Fingerprint Identification Using Extended Minutia Types
TL;DR: In this article, the authors proposed a method that exploits extended fingerprint features (unusual/rare minutiae) not commonly considered in AFIS to improve rank identification accuracies.
Journal ArticleDOI
Simultaneous latent fingerprint recognition
TL;DR: A semi-automatic approach to process and analyze simultaneous latent fingerprints that demonstrates that comparisons can be made from a database of ten-prints for a more comprehensive search instead of the time consuming manual approach used by latent fingerprint examiners.
Journal ArticleDOI
Bio-medical and latent fingerprint enhancement and matching using advanced scalable soft computing models
Adhiyaman Manickam,Ezhilmaran Devarasan,Gunasekaran Manogaran,Naveen Chilamkurti,Vijayarajan Vijayan,Shubham Saraff,R. D. Jackson Samuel,Raja Krishnamoorthy +7 more
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.
References
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Active contours without edges
Tony F. Chan,Luminita A. Vese +1 more
TL;DR: A new model for active contours to detect objects in a given image, based on techniques of curve evolution, Mumford-Shah (1989) functional for segmentation and level sets is proposed, which can detect objects whose boundaries are not necessarily defined by the gradient.
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Handbook of Fingerprint Recognition
TL;DR: This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.
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Algorithms for Graphics and Image Processing
TL;DR: This chapter discusses Graphics, Image Processing, and Pattern Recognition, and the Reconstruction techniques used in this program, as well as some of the problems faced in implementing this program.
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Handbook of Multibiometrics
TL;DR: Details multi-modal biometrics and its exceptional utility for increasingly reliable human recognition systems and the substantial advantages of multimodal systems over conventional identification methods.