Results 21 - 30
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219
Learning Fingerprint Minutiae Location and Type
- Pattern Recognition
, 2003
"... For simplicity of pattern recognition system design, a sequential approach consisting of sensing, feature extraction and classification/matching is conventionally adopted, where each stage transforms its input relatively independently. In practice, the interaction between these modules is limited. S ..."
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Cited by 17 (0 self)
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For simplicity of pattern recognition system design, a sequential approach consisting of sensing, feature extraction and classification/matching is conventionally adopted, where each stage transforms its input relatively independently. In practice, the interaction between these modules is limited. Some of the errors in this end-to-end sequential processing can be eliminated, especially for the feature extraction stage, by revisiting the input pattern. We propose a feature refinement stage followed by a feedforward of the original grayscale image data to a feature verification stage in the context of a minutiae-based fingerprint verification system. We show that a feature refinement stage that assigns one of two class labels to each detected minutia (ridge ending and ridge bifurcation) can improve the matching performance by 1%. Further, we show that a minutia verification stage based on reexamining the grayscale profile in a detected minutia's spatial neighborhood in the sensed image can further improve the matching performance by 2.2% on our fingerprint database.
Fingerprint verification using spectral minutiae representations
- IEEE Trans. Inf. Forensics Secur. 2009
"... Abstract—Most fingerprint recognition systems are based on the use of a minutiae set, which is an unordered collection of minutiae locations and orientations suffering from various deformations such as translation, rotation, and scaling. The spectral minutiae representation introduced in this paper ..."
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Cited by 17 (6 self)
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Abstract—Most fingerprint recognition systems are based on the use of a minutiae set, which is an unordered collection of minutiae locations and orientations suffering from various deformations such as translation, rotation, and scaling. The spectral minutiae representation introduced in this paper is a novel method to represent a minutiae set as a fixed-length feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. These characteristics enable the combination of fingerprint recognition systems with template protection schemes that require a fixed-length feature vector. This paper introduces the concept of algorithms for two representation methods: the location-based spectral minutiae representation and the orientation-based spectral minutiae representation. Both algorithms are evaluated using two correlation-based spectral minutiae matching algorithms. We present the performance of our algorithms on three fingerprint databases. We also show how the performance can be improved by using a fusion scheme and singular points. Index Terms—Biometrics, fingerprint recognition, minutiae matching, template protection. I.
Multispectral Palmprint Recognition using Wavelet-based Image Fusion
- In Proceedings of the 9th International Conference on Signal Processing (ICSP 2008
, 2008
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Privacy Preserving Multi-Factor Authentication with Biometrics
- Journal of Computer Security
, 2007
"... An emerging approach to the problem of reducing the identity theft is represented by the adoption of biometric authentication systems. Such systems however present however several challenges, related to privacy, reliability, security of the biometric data. Inter-operability is also required among th ..."
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Cited by 16 (1 self)
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An emerging approach to the problem of reducing the identity theft is represented by the adoption of biometric authentication systems. Such systems however present however several challenges, related to privacy, reliability, security of the biometric data. Inter-operability is also required among the devices used for the authentication. More-over, very often biometric authentication in itself is not sufficient as a conclusive proof of identity and has to be complemented with multiple other proofs of identity like passwords, SSN, or other user identifiers. Multi-factor authentication mechanisms are thus re-quired to enforce strong authentication based on the biometric and identifiers of other nature. In this paper we provide a two-phase authentication mechanism for federated identity management systems. The first phase consists of a two-factor biometric authentication based on zero knowledge proofs. We employ techniques from vector-space model to gener-ate cryptographic biometric keys. These keys are kept secret, thus preserving the confidentiality of the biometric data, and at the same time exploit the advantages of a biometric authentication. The sec-ond authentication combines several authentication factors in con-junction with the biometric to provide a strong authentication. A key advantage of our approach is that any unanticipated combina-tion of factors can be used. Such authentication system leverages the information of the user that are available from the federated identity management system.
Fingerprint Verification by Fusion of Optical and Capacitive Sensors
- Pattern Recognition Letters
, 2004
"... A few works have been presented so far on information fusion for fingerprint verification. None, however, have explicitly investigated the use of multi-sensor fusion, in other words, the integration of the information provided by multiple devices to capture fingerprint images. In this paper, a multi ..."
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Cited by 15 (2 self)
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A few works have been presented so far on information fusion for fingerprint verification. None, however, have explicitly investigated the use of multi-sensor fusion, in other words, the integration of the information provided by multiple devices to capture fingerprint images. In this paper, a multi-sensor fingerprint verification system based on the fusion of optical and capacitive sensors is presented. Reported results show that such a multi-sensor system can perform better than traditional fingerprint matchers based on a single sensor.
Feature Level Fusion of Face and Fingerprint
"... Abstract- The aim of this paper is to study the fusion at feature extraction level for face and fingerprint biometrics. The proposed approach is based on the fusion of the two traits by extracting independent feature pointsets from the two modalities, and making the two pointsets compatible for conc ..."
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Abstract- The aim of this paper is to study the fusion at feature extraction level for face and fingerprint biometrics. The proposed approach is based on the fusion of the two traits by extracting independent feature pointsets from the two modalities, and making the two pointsets compatible for concatenation. Moreover, to handle the 'problem of curse of dimensionality', the feature pointsets are properly reduced in dimension. Different feature reduction techniques are implemented, prior and after the feature pointsets fusion, and the results are duly recorded. The fused feature pointset for the database and the query face and fingerprint images are matched using techniques based on either the point pattern matching, or the Delaunay triangulation. Comparative experiments are conducted on chimeric and real databases, to assess the actual advantage of the fusion performed at the feature extraction level, in comparison to the matching score level.
Impact of image quality on performance: Comparison of young and elderly fingerprints
- THE 6TH INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN SOFT COMPUTING (RASC
, 2006
"... Performance of fingerprint recognition systems is heavily influenced by the quality of fingerprints provided by the user. Image quality analysis is traditionally performed using local and global structures of fingerprint images like ridge flow, analysis of ridge-valley structures, contrast ratios et ..."
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Cited by 14 (2 self)
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Performance of fingerprint recognition systems is heavily influenced by the quality of fingerprints provided by the user. Image quality analysis is traditionally performed using local and global structures of fingerprint images like ridge flow, analysis of ridge-valley structures, contrast ratios etc. With large scale deployment of fingerprint recognition in systems like US VISIT program, image quality issues of fingerprint images from extreme age groups becomes even a more important issue. The impact of image quality on performance of fingerprint recognition systems should be a positive one i.e. higher image quality should lead to better overall performance of the system, and removal of lower quality images should improve performance of the system. This research study studied the impact of fingerprint image quality of two different age groups: 18-25, and 62 and above on overall performance using two different matchers. The difference in image quality between the two age groups was analyzed, and then the impact of image quality on performance of fingerprint matchers between the two groups was analyzed. Image quality analysis was performed using NFIQ which is part of NIST Fingerprint Image Software (NFIS). Neurotechnologija VeriFinger and bozorth3 (NFIS) matchers were used to assess overall performance. For the purposes of the research study, overall performance was measured using False Non Matches.
Fingerprint matching by genetic algorithms
, 2006
"... Fingerprint matching is still a challenging problem for reliable person authentication because of the complex distortions involved in two impressions of the same finger. In this paper, we propose a fingerprint-matching approach based on genetic algorithms (GA), which tries to find the optimal transf ..."
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Cited by 14 (0 self)
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Fingerprint matching is still a challenging problem for reliable person authentication because of the complex distortions involved in two impressions of the same finger. In this paper, we propose a fingerprint-matching approach based on genetic algorithms (GA), which tries to find the optimal transformation between two different fingerprints. In order to deal with low-quality fingerprint images, which introduce significant occlusion and clutter of minutiae features, we design a fitness function based on the local properties of each triplet of minutiae. The experimental results on National Institute of Standards and Technology fingerprint database, NIST-4, not only show that the proposed approach can achieve good performance even when a large portion of fingerprints in the database are of poor quality, but also show that the proposed approach is better than another approach, which is based on mean-squared error estimation.
Direct Pore Matching for Fingerprint Recognition
- ICB
, 2009
"... Abstract. Sweat pores on fingerprints have proven to be useful features for personal identification. Several methods have been proposed for pore matching. The state-of-the-art method first matches minutiae on the fingerprints and then matches the pores based on the minutia matching results. A proble ..."
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Cited by 14 (6 self)
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Abstract. Sweat pores on fingerprints have proven to be useful features for personal identification. Several methods have been proposed for pore matching. The state-of-the-art method first matches minutiae on the fingerprints and then matches the pores based on the minutia matching results. A problem of such minutia-based pore matching method is that the pore matching is dependent on the minutia matching. Such dependency limits the pore matching performance and impairs the effectiveness of the fusion of minutia and pore match scores. In this paper, we propose a novel direct approach for matching fingerprint pores. It first determines the correspondences between pores based on their local features. It then uses the RANSAC (RANdom SAmple Consensus) algorithm to refine the pore correspondences obtained in the first step. A similarity score is finally calculated based on the pore matching results. The proposed pore matching method successfully avoids the dependency of pore matching on minutia matching results. Experiments have shown that the fingerprint recognition accuracy can be greatly improved by using the method proposed in this paper.
Image Versus Feature Mosaicing: A Case Study in Fingerprints
- in Proceedings of SPIE Conference on Biometric Technology for Human Identification
, 2006
"... Fingerprint mosaicing entails the reconciliation of information presented by two or more impressions of a finger in order to generate composite information. It can be accomplished by blending these impressions into a single mosaic, or by integrating the feature sets (viz., minutiae information) pert ..."
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Cited by 13 (4 self)
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Fingerprint mosaicing entails the reconciliation of information presented by two or more impressions of a finger in order to generate composite information. It can be accomplished by blending these impressions into a single mosaic, or by integrating the feature sets (viz., minutiae information) pertaining to these impressions. In this work, we use Thin-plate Splines (TPS) to model the relative transformation between two impressions of a finger thereby accounting for the non-linear distortion present between them. The estimated deformation is used (a) to register the two images and blend them into a single entity before extracting minutiae from the resulting mosaic (image mosaicing); and (b) to register the minutiae point sets corresponding to the two images and integrate them into a single master minutiae set (feature mosaicing). Experiments conducted on the FVC 2002 DB1 database indicate that both mosaicing schemes result in improved matching performance although feature mosaicing is observed to outperform image mosaicing. Keywords: Image mosaicing; Feature mosaicing; Sum rule; Thin-plate splines (TPS); Elasticity; Correlation. 1.
