Search results for "Minutiae"

showing 10 items of 10 documents

A Novel Embedded Fingerprints Authentication System Based on Singularity Points

2008

In this paper a novel embedded fingerprints authentication system based on core and delta singularity points detection is proposed. Typical fingerprint recognition systems use core and delta singularity points for classification tasks. On the other hand, the available optical and photoelectric sensors give high quality fingerprint images with well defined core and delta points, if they are present. In the proposed system, fingerprint matching is based on singularity points position, orientation, and relative distance detection. As result, fingerprint matching involves the comparison between few features leading to a very fast system with recognition rates comparable to the standard minutiae…

MinutiaeAuthenticationPixelOrientation (computer vision)business.industryComputer scienceFingerprint recognitionfingerprints authenticationSingularityFingerprintComputer visionArtificial intelligenceField-programmable gate arraybusiness2008 International Conference on Complex, Intelligent and Software Intensive Systems
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A Novel Iris Recognition System based on Micro-Features

2007

In this paper a novel approach for iris recognition system based on iris micro-features is proposed. The proposed system follows the minutiae based approach developed for fingerprint recognition systems. The proposed system uses four iris microfeatures, considered as minutiae, for identification. The individualized characteristics are nucleus, collarette, valleys and radius. Iris recognition is divided in three main phases: image preprocessing, micro-features extraction and matching. The algorithm has been tested on CASIA v1.0 iris image database obtaining an high accuracy. The obtained experimental results have been analyzed and compared with the Daugman based approach.

MinutiaeMatching (graph theory)Biometricsbusiness.industryIris recognitionFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionFingerprint recognitionComputingMethodologies_PATTERNRECOGNITIONGeographyiris micro-characteristIcs recognition systemPreprocessorComputer visionIRIS (biosensor)Artificial intelligencebusiness
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Performance evaluation of simple fingerprint minutiae extraction algorithm using crossing number on valley structure

2008

In fingerprint recognition system, performance of fingerprint feature extraction algorithm is important. We use visual analysis to evaluate this performance. 100 respondents fill a questionnaire consisting of 30 images from fingerprint feature extraction process. We get 12,3 % minutiae points missed by this algorithm. With BOZORTH3 minutiae matching algorithm, the distribution of matching score of 80-fingerprint images are presented and we obtain EER 5.89 % at threshold value 180.

MinutiaeMatching (graph theory)Computer sciencebusiness.industryFeature extractionPattern recognitionImage segmentationFingerprint recognitionFingerprintComputer visionAlgorithm designArtificial intelligencebusinessBlossom algorithm2008 International Conference on Innovations in Information Technology
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Image enhancement in simple fingerprint minutiae extraction algorithm using crossing number on valley structure

2007

In fingerprint recognition system, fingerprint feature extraction algorithm requires good quality fingerprint images to produce good results. Therefore, one step in the preprocessing stage is image enhancement to improve the quality of poor fingerprint image, so the minutiae points can be detected with good results. In this paper, we present how this enhancement process in simple minutiae detection algorithm using crossing number on valley structure improves detection of true minutiae.

MinutiaePixelComputer sciencebusiness.industryFeature extractionNormalization (image processing)Pattern recognitionFingerprint recognitionImage enhancementComputingMethodologies_PATTERNRECOGNITIONFingerprintPreprocessorComputer visionArtificial intelligencebusiness2007 International Conference on Intelligent and Advanced Systems
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Simple Fingerprint Minutiae Extraction Algorithm Using Crossing Number On Valley Structure

2007

Most of the existing fingerprint extraction techniques currently available are based on ridge structure. The ridge usually has thicker structure than the valley, so that more processing time is needed to extract the ridge than extracting the valley. Taking the advantage of the thin structure of the valley, we proposed an algorithm that reduces the time needed for minutiae extraction. The algorithm was developed in Matlab environment using fingerprint images from FVC2004. In order to show the performance of the algorithm, numerical results are presented.

MinutiaePixelbusiness.industryFeature extractionPattern recognitionFingerprint recognitionRidge (differential geometry)Facial recognition systemComputingMethodologies_PATTERNRECOGNITIONGeographyFingerprintArtificial intelligenceMATLABbusinesscomputercomputer.programming_language2007 IEEE Workshop on Automatic Identification Advanced Technologies
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Fingerprint image enhancement using directional morphological filter

2005

Fingerprint images quality enhancement is a topic phase to ensure good performance in an automatic fingerprint identification system (AFIS) based on minutiae matching. In this paper a new fingerprint enhancement algorithm based on morphological filter is introduced. The algorithm is based on three steps: directional decomposition, morphological filter and composition. The performance of the proposed approach has been evaluated on two sets of images: the first one is DB3 database from Fingerprint Verification Competition (FVC) and the second one is self collected using an optical scanner

MinutiaeScannerMatching (graph theory)business.industryComputer scienceImage qualityComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPhase (waves)Fingerprint Verification CompetitionPattern recognitionImage segmentationFingerprintBiometrics | Algorithms | fingerprint orientationArtificial intelligencebusiness
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An Advanced Technique for User Identification Using Partial Fingerprint

2013

User identification is a very interesting and complex task. Invasive biometrics is based on traits uniqueness and immutability over time. In forensic field, fingerprints have always been considered an essential element for personal recognition. The traditional issue is focused on full fingerprint images matching. In this paper an advanced technique for personal recognition based on partial fingerprint is proposed. This system is based on fingerprint local analysis and micro-features, endpoints and bifurcations, extraction. The proposed approach starts from minutiae extraction from a partial fingerprint image and ends with the final matching score between fingerprint pairs. The computation o…

MinutiaeSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMatching (statistics)Biometricsbusiness.industryComputer scienceData_MISCELLANEOUSFeature extractionFingerprint Verification CompetitionPattern recognitionFingerprint recognitionIdentification (information)FingerprintComputer visionArtificial intelligenceUser identification Partial fingerprint Minutiae Roto-translation parametersbusiness
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A Multimodal Technique for an Embedded Fingerprint Recognizer in Mobile Payment Systems

2009

The development and the diffusion of distributed systems, directly connected to recent communication technologies, move people towards the era of mobile and ubiquitous systems. Distributed systems make merchant-customer relationships closer and more flexible, using reliable e-commerce technologies. These systems and environments need many distributed access points, for the creation and management of secure identities and for the secure recognition of users. Traditionally, these access points can be made possible by a software system with a main central server. This work proposes the study and implementation of a multimodal technique, based on biometric information, for identity management a…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMinutiaeAuthenticationUbiquitous authentication multimodal systems mobile payment systems biometric techniques and embedded systemsBiometricsComputer Networks and Communicationsbusiness.industryComputer scienceFingerprint (computing)Process (computing)TK5101-6720Identity managementComputer Science ApplicationsEmbedded systemTelecommunicationMobile paymentSoftware systembusinessComputer networkMobile Information Systems
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Design and Implementation of an Efficient Fingerprint Features Extractor

2014

Biometric recognition systems are rapidly evolving technologies and their use in embedded devices for accessing and managing data and resources is a very challenging issue. Usually, they are composed of three main modules: Acquisition, Features Extraction and Matching. In this paper the hardware design and implementation of an efficient fingerprint features extractor for embedded devices is described. The proposed architecture, designed for different acquisition sensors, is composed of four blocks: Image Pre-processor, Macro-Features Extractor, Micro- Features Extractor and Master Controller. The Image Pre- processor block increases the quality level of the input raw image and performs an a…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMinutiaeBiometricsComputer sciencebusiness.industryFingerprint (computing)Feature extractionFingerprint recognitionComputer visionArtificial intelligenceFPGA Fingerprint Features Extraction Adaptive ProcessingField-programmable gate arraybusinessImage resolutionBlock (data storage)2014 17th Euromicro Conference on Digital System Design
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Introducing Pseudo-Singularity Points for Efficient Fingerprints Classification and Recognition

2010

Fingerprint classification and matching are two key issues in automatic fingerprint recognition. Generally, fingerprint recognition is based on a set of relevant local characteristics, such as ridge ending and bifurcation (minutiae). Fingerprint classification is based on fingerprint global features, such as core and delta singularity points. Unfortunately, singularity points are not always present in a fingerprint image: the acquisition process is not ideal, so that the fingerprint is broken, or the fingerprint belongs to the arch class. In the above cases, pseudo-singularity-points will be detected and extracted to make possible fingerprint classification and matching. As result, fingerpr…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniMinutiaeContextual image classificationbusiness.industryComputer scienceData_MISCELLANEOUSFeature extractionFingerprint Verification CompetitionPattern recognitionFingerprint recognitionFingerprint singularity regions classification matching algorithm core and delta points fingerprint recognition systems.Statistical classificationFingerprintData_GENERALComputer visionArtificial intelligencebusinessBlossom algorithm2010 International Conference on Complex, Intelligent and Software Intensive Systems
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