Search results for "Fingerprint classification"

showing 6 items of 6 documents

Resource-efficient hardware implementation of a neural-based node for automatic fingerprint classification

2017

Modern mobile communication networks and Internet of Things are paving the way to ubiquitous and mobile computing. On the other hand, several new computing paradigms, such as edge computing, demand for high computational capabilities on specific network nodes. Ubiquitous environments require a large number of distributed user identification nodes enabling a secure platform for resources, services and information management. Biometric systems represent a useful option to the typical identification systems. An accurate automatic fingerprint classification module provides a valuable indexing scheme that allows for effective matching in large fingerprint databases. In this work, an efficient em…

Fingerprint classificationField programmable gate array (FPGA)INF/01 - INFORMATICAWeightless neural networkWeightless neural networksMobile and ubiquitous ComputingField programmable gate array (FPGA); Fingerprint classification; Mobile and ubiquitous Computing; Virtual neuron; Weightless neural networksVirtual neuronMobile and Ubiquitous Computing Fingerprint Classification Weightless Neural Net- works Virtual Neuron Field Programmable Gate Array (FPGA)
researchProduct

Fast Fingerprints Classification only using the Directional Image

2007

The classification phase is an important step of an automatic fingerprint identification system, where the goal is to restrict only to a subset of the whole database the search time. The proposed system classifies fingerprint images in four classes using only directional image information. This approach, unlike the literature approaches, uses the acquired fingerprint image without enhancement phases application. The system extracts only directional image and uses three concurrent decisional modules to classify the fingerprint. The proposed system has a high classification speed and a very low computational cost. The experimental results show a classification rate of 87.27%.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniBayesian networkc-means algorithmDecision networkFingerprint classificationNeural network
researchProduct

Fingerprint classification based on deep learning approaches: Experimental findings and comparisons

2021

Biometric classification plays a key role in fingerprint characterization, especially in the identification process. In fact, reducing the number of comparisons in biometric recognition systems is essential when dealing with large-scale databases. The classification of fingerprints aims to achieve this target by splitting fingerprints into different categories. The general approach of fingerprint classification requires pre-processing techniques that are usually computationally expensive. Deep Learning is emerging as the leading field that has been successfully applied to many areas, such as image processing. This work shows the performance of pre-trained Convolutional Neural Networks (CNNs…

Physics and Astronomy (miscellaneous)BiometricsComputer scienceGeneral Mathematicsfingerprint featuresfingerprint classification; deep learning; convolutional neural networks; fingerprint featuresConvolutional neural networks Deep learning Fingerprint classification Fingerprint featuresImage processing02 engineering and technologyConvolutional neural networkField (computer science)fingerprint classification020204 information systemsconvolutional neural networksQA1-9390202 electrical engineering electronic engineering information engineeringComputer Science (miscellaneous)Reliability (statistics)business.industryDeep learningFingerprint (computing)deep learningPattern recognitionIdentification (information)Chemistry (miscellaneous)Convolutional neural networks; Deep learning; Fingerprint classification; Fingerprint features020201 artificial intelligence & image processingArtificial intelligencebusinessMathematics
researchProduct

An Heuristic Approach for the Training Dataset Selection in Fingerprint Classification Tasks

2015

Fingerprint classification is a key issue in automatic fingerprint identification systems. It aims to reduce the item search time within the fingerprint database without affecting the accuracy rate. In this paper an heuristic approach using only the directional image information for the training dataset selection in fingerprint classification tasks is described. The method combines a Fuzzy C-Means clustering method and a Naive Bayes Classifier and it is composed of three modules: the first module builds the working datasets, the second module extracts the training images dataset and, finally, the third module classifies fingerprint images in four classes. Unlike literature approaches using …

Directional imageFingerprint classificationComputer sciencebusiness.industryHeuristicNaive bayes classifierTraining dataset optimizationPattern recognitionBayes classifiercomputer.software_genreClass (biology)Fuzzy logicNaive Bayes classifierComputingMethodologies_PATTERNRECOGNITIONFingerprintArtificial intelligenceData miningCluster analysisbusinesscomputerSelection (genetic algorithm)Fuzzy C-Mean
researchProduct

A Novel Technique for Fingerprint Classification based on Fuzzy C-Means and Naive Bayes Classifier

2014

Fingerprint classification is a key issue in automatic fingerprint identification systems. One of the main goals is to reduce the item search time within the fingerprint database without affecting the accuracy rate. In this paper, a novel technique, based on topological information, for efficient fingerprint classification is described. The proposed system is composed of two independent modules: the former module, based on Fuzzy C-Means, extracts the best set of training images, the latter module, based on Fuzzy C-Means and Naive Bayes classifier, assigns a class to each processed fingerprint using only directional image information. The proposed approach does not require any image enhancem…

Novel techniqueSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industryPattern recognitioncomputer.software_genreClass (biology)Fuzzy logicImage (mathematics)Set (abstract data type)Naive Bayes classifierFingerprintKey (cryptography)Artificial intelligenceData miningbusinessFingerprint Classification Directional Images Fuzzy C-Means Naive Bayes Classifiercomputer
researchProduct

An Embedded Fingerprints Classification System based on Weightless Neural Networks

2009

Automatic fingerprint classification provides an important indexing scheme to facilitate efficient matching in large-scale fingerprint databases in Automatic Fingerprint Identification Systems (AFISs). The paper presents a new fast fingerprint classification module implementing on embedded Weightless Neural Network (RAM-based neural network). The proposed WNN architecture uses directional maps to classify fingerprint images in the five NIST classes (Left Loop, Right Loop, Whorl, Arch and Tented Arch) without anyone enhancement phase. Starting from the directional map, the WNN architecture computes the fingerprint classification rate. The proposed architecture is implemented on Celoxica RC20…

Embedded Fingerprint Classification Weightless Neural Network RAM based Neural Networks Directional Map FPGA.
researchProduct