Search results for "fingerprint features"

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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
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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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