Bibliografie tematiche / Fingerprint Verification

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Letteratura scientifica selezionata sul tema "Fingerprint Verification"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 25 luglio 2025

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Articoli di riviste sul tema "Fingerprint Verification"

1

Bercelin, Rose Mary W., N. Subbulakshmi, and Tofflin R. Bini. "Fingerprint Combination of Privacy Preservation is Improved by Delaunay Triangulation Method." Applied Mechanics and Materials 573 (June 2014): 437–41. http://dx.doi.org/10.4028/www.scientific.net/amm.573.437.

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Abstract (sommario):
Fingerprints are graphical ridge and valley patterns on the tips of human fingers. Owing to their uniqueness and permanence, the use of fingerprints is considered to be one of the most reliable methods of personal verification. Fingerprints are today among the most popularly used biometric modalities in automatic verification systems. At the same time, Protecting the privacy of Fingerprint is an important one, here a novel system propose protecting fingerprint by combining two different fingerprints. In the enrolment stage, fingerprints will be captured from two different fingers. Minutiae pos
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Melyani Melyani. "Test Data Algoritma Kromosom Pada Sidik Jari Menggunakan Jaringan Syaraf." JURNAL PENELITIAN SISTEM INFORMASI (JPSI) 2, no. 1 (2024): 138–62. http://dx.doi.org/10.54066/jpsi.v2i1.1550.

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Abstract (sommario):
Biometric features that can be used for identification include iris, voice, DNA and fingerprints. Fingerprints are the most widely used biometric feature because of their uniqueness, universality and stability. Fingerprint recognition can be grouped into two different forms of problems, namely verification and identification. Verification is comparing one fingerprint with another fingerprint. Meanwhile, identification is matching an input fingerprint with fingerprint data in the database. Thus, identification can be interpreted as an extension of verification carried out by comparing one finge
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Hemanth, Gannamani, Maddipati Vikas, Sai Nisarg D. Mehta, and Gaurav Varshney. "Fingerprint Voting System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43165.

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Fingerprint voting systems offer a robust mechanism for ensuring secure and reliable electoral processes. This paper proposes a comprehensive approach to government verification and voter authentication within fingerprint voting systems. Beginning with the initial voter registration process, government authorities authenticate individuals by capturing their fingerprints and verifying their identities against national databases. Upon successful verification, voters are enrolled in the system and provided with unique biometric identifiers. During elections, voters undergo authentication using th
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Priati, Assiroj, L. H. S. Warnars H., Abdurrachman E., I. Kistijantoro A., and Doucet A. "Measuring memetic algorithm performance on image fingerprints dataset." TELKOMNIKA Telecommunication, Computing, Electronics and Control 19, no. 1 (2021): pp. 96~104. https://doi.org/10.12928/TELKOMNIKA.v19i1.16418.

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Abstract (sommario):
Personal identification has become one of the most important terms in our society regarding access control, crime and forensic identification, banking and also computer system. The fingerprint is the most used biometric feature caused by its unique, universality and stability. The fingerprint is widely used as a security feature for forensic recognition, building access, automatic teller machine (ATM) authentication or payment. Fingerprint recognition could be grouped in two various forms, verification and identification. Verification compares one on one fingerprint data. Identification is mat
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QIN, WEI, and YILONG YIN. "A NOVEL METHOD USING VIDEOS FOR FINGERPRINT VERIFICATION." International Journal of Pattern Recognition and Artificial Intelligence 26, no. 01 (2012): 1256002. http://dx.doi.org/10.1142/s0218001412560022.

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Abstract (sommario):
Traditional fingerprint verifications use single image for matching. However, the verification accuracy cannot meet the need of some application domains. In this paper, we propose to use videos for fingerprint verification. To take full use of the information contained in fingerprint videos, we present a novel method to use the dynamic as well as the static information in fingerprint videos. After preprocessing and aligning processes, the Inclusion Ratio of two matching fingerprint videos is calculated and used to represent the similarity between these two videos. Experimental results show tha
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Djara, Tahirou, Marc Kokou Assogba, and Antoine Vianou. "A Contactless Fingerprint Verification Method using a Minutiae Matching Technique." International Journal of Computer Vision and Image Processing 6, no. 1 (2016): 12–27. http://dx.doi.org/10.4018/ijcvip.2016010102.

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Abstract (sommario):
Most of matching or verification phases of fingerprint systems use minutiae types and orientation angle to find matched minutiae pairs from the input and template fingerprints. Unfortunately, due to some non-linear distortions, like excessive pressure and fingers twisting during enrollment, this process can cause the minutiae features to be distorted from the original. The authors are then interested in a fingerprint matching method using contactless images for fingerprint verification. After features extraction, they compute Euclidean distances between template minutiae (bifurcation and endin
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J, Nandhakumar. "IoT Based Voting Machine with Fingerprint Verification." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 1490–96. http://dx.doi.org/10.22214/ijraset.2022.42573.

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Abstract: In a democratic country, like India voting is an important way where the citizen can cast their vote. Usually voting is done by casting their vote in polling booth. As the technology increases, nowadays electronic voting machine is used for casting vote. This paper is about an IoT based voting machine with fingerprint verification. The main aim of this project is to make voting secure using fingerprint verification and also to reduce malpractices. The details of the voter along with their fingerprint in stored in database. If the fingerprint matches with the stored fingerprint, the s
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G. Nancharaiah, G. Sai Teja Kumari, K. Lakshmi, J. Harika, and B. Srinu. "Fingerprint Recognition and Verification using Fourier Domain Filtering and Histogram Equalization Techniques." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 2 (2024): 698–704. http://dx.doi.org/10.32628/cseit24102100.

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Abstract (sommario):
Fingerprint Recognition is a vital method in biometric identification and verification of human beings in various domains like Security, Digital Forensics, Internet of Things (IoT), and many more. Each individual human is having distinct fingerprint pattern than others, hence it is one of the most prominent and widely used method to distinguish individuals. Many research studies and solutions have been developed in biometric domain since a decade, which influences now in making the process of fingerprint recognition more optimized, faster and efficient. However, present fingerprint acquisition
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Pan, Ming-Sie, Chao-Hsing Fan, Ching-Chao Yang, et al. "Fingerprint preprocessing using FCN and U-net methods." Journal of Information and Optimization Sciences 45, no. 5 (2024): 1421–34. http://dx.doi.org/10.47974/jios-1731.

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Abstract (sommario):
This paper analyzes the importance of optimizing fingerprint images from the perspective of front-line forensics personnel. Due to defects such as fingerprint ridge blurring and fingerprint image overlap, it may cause delays in fingerprint identification and lead to misjudgments (false positives, false negatives) and other consequences. This paper simulated common fingerprint images (fuzzy feature points) at criminal cases, and captured, segmented, and reconstructed fingerprints. Two deep learning model architectures, U-net [1] and FCN [2], were applied to realize image segmentation and image
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‘Aisyah Sa’dan, Siti, Rajeswari Raju, Nursuriati Jamil, and . "Clonal Selection Algorithm for Low Quality Fingerprint Image Verification." International Journal of Engineering & Technology 7, no. 4.42 (2018): 157–60. http://dx.doi.org/10.14419/ijet.v7i4.42.25702.

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Abstract (sommario):
Fingerprint verification has drawn a lot of attention to its approach in biometric since it is one of the most important biometric technologies nowadays and is widely used in several different applications and areas. It is applied in the forensic science area in order to identify people who were involved in criminal scenes such as the victims and the suspects. A human’s fingerprint is unique and usually has its own patterns and ridges, which differs them from other’s fingerprints. However, there are some drawbacks that can cause low accuracy and low performance of the verification. This oc
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Tesi sul tema "Fingerprint Verification"

1

Yager, Neil Gordon Computer Science &amp Engineering Faculty of Engineering UNSW. "Hierarchical fingerprint verification." Awarded by:University of New South Wales. Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/27008.

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Abstract (sommario):
Fingerprints have been an invaluable tool for law enforcement and forensics for over a century, motivating research into automated fingerprint based identification in the early 1960's. More recently, fingerprints have found an application in the emerging industry of biometric systems. Biometrics is the automatic identification of an individual based on physiological or behavioral characteristics. Due to its security related applications and the current world political climate, biometrics is presently the subject of intense research by private and academic institutions. Fingerprints are emerg
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2

Deng, Huimin. "Robust minutia-based fingerprint verification." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37036427.

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Deng, Huimin, and 鄧惠民. "Robust minutia-based fingerprint verification." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37036427.

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Yan, Weiwei. "Software-hardware Cooperative Embedded Verification System Fusing Fingerprint Verification and Shared-key Authentication." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-66677.

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Abstract (sommario):
In order to protect the security of the commercial information, personnel information, military information, governmental information on the Internet, the claimed identity should be authenticated. Now there are three main security authentication methods: first: using user PIN, such as password; second: using physical key, such as USBKey; third: using biological authentication technology, such as fingerprint, iris, voice and palm prints, etc. Because of the uniqueness, invariance, and ubiquity properties of biometric authentication, biometric authentication is becoming popular, especially finge
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Sandström, Marie. "Liveness Detection in Fingerprint Recognition Systems." Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2397.

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Abstract (sommario):
<p>Biometrics deals with identifying individuals with help of their biological data. Fingerprint scanning is the most common method of the biometric methods available today. The security of fingerprint scanners has however been questioned and previous studies have shown that fingerprint scanners can be fooled with artificial fingerprints, i.e. copies of real fingerprints. The fingerprint recognition systems are evolving and this study will discuss the situation of today. </p><p>Two approaches have been used to find out how good fingerprint recognition systems are in distinguishing between live
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Fransson, Linda, and Therese Jeansson. "Biometric methods and mobile access control." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5023.

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Abstract (sommario):
Our purpose with this thesis was to find biometric methods that can be used in access control of mobile access. The access control has two parts. Firstly, to validate the identity of the caller and, secondly, to ensure the validated user is not changed during the session that follows. Any solution to the access control problem is not available today, which means that anyone can get access to the mobile phone and the Internet. Therefore we have researched after a solution that can solve this problem but also on how to secure that no one else can take over an already validated session. We began
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Sun, Wei [Verfasser], Thomas [Akademischer Betreuer] Sikora, Thomas [Gutachter] Sikora, Atta [Gutachter] Badii, and Ivo [Gutachter] Keller. "Low complexity embedded fingerprint verification and identification system / Wei Sun ; Gutachter: Thomas Sikora, Atta Badii, Ivo Keller ; Betreuer: Thomas Sikora." Berlin : Technische Universität Berlin, 2016. http://d-nb.info/1156181704/34.

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Dimitrov, Emanuil. "Fingerprints recognition." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-5522.

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Abstract (sommario):
<p>Nowadays biometric identification is used in a variety of applications-administration, business and even home. Although there are a lot of biometric identifiers, fingerprints are the most widely spread due to their acceptance from the people and the cheap price of the hardware equipment. Fingerprint recognition is a complex image recognition problem and includes algorithms and procedures for image enhancement and binarization, extracting and matching features and sometimes classification. In this work the main approaches in the research area are discussed, demonstrated and tested in a sampl
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Falade, Joannes Chiderlos. "Identification rapide d'empreintes digitales, robuste à la dissimulation d'identité." Thesis, Normandie, 2020. http://www.theses.fr/2020NORMC231.

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Abstract (sommario):
La biométrie est de plus en plus utilisée à des fins d’identification compte tenu de la relation étroite entre la personne et son identifiant (comme une empreinte digitale). Nous positionnons cette thèse sur la problématique de l’identification d’individus à partir de ses empreintes digitales. L’empreinte digitale est une donnée biométrique largement utilisée pour son efficacité, sa simplicité et son coût d’acquisition modeste. Les algorithmes de comparaison d’empreintes digitales sont matures et permettent d’obtenir en moins de 500 ms un score de similarité entre un gabarit de référence (stoc
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Bartoň, Jaroslav. "Podpora pro autentizaci pomocí otisků prstu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2009. http://www.nusl.cz/ntk/nusl-235492.

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Abstract (sommario):
The goal of the thesis is the finger-print authentication support within the Linux operating system and the K Desktop Environment (KDE). Theoretical part of the thesis firstly explains main IT security terms and ways to proof the identity. Secondly it describes biometric systems and types of processed biometric characteristics. Lastly the features of finger-prints, their markants as well as types of scanners used in scanning the finger-prints and ways to analyze the scanned material have been elaborated. Practical solution part of the thesis develops and establishes finger-print management app
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Libri sul tema "Fingerprint Verification"

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1942-, Wilson C. L., and National Institute of Standards and Technology (U.S.), eds. Studies of fingerprint matching using the NIST verification test bed (VTB). U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 2003.

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Zürich, Eidgenössische Technische Hochschule, ed. Fingerprint verification using cellular neural networks. 2003.

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Capitoli di libri sul tema "Fingerprint Verification"

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Jain, Anil K., Sharath Pankanti, Salil Prabhakar, and Arun Ross. "Recent Advances in Fingerprint Verification." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45344-x_26.

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Udup U., Raghavendra, Gaurav Garg, and Pramod Sharma. "Fast and Accurate Fingerprint Verification." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45344-x_27.

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Maio, Dario, Davide Maltoni, Raffaele Cappelli, Jim L. Wayman, and Anil K. Jain. "FVC2004: Third Fingerprint Verification Competition." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_1.

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Venkataramani, Krithika, and B. V. K. Vijaya Kumar. "Fingerprint Verification Using Correlation Filters." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44887-x_103.

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Gil, Younhee, Daesung Moon, Sungbum Pan, and Yongwha Chung. "Fingerprint Verification System Involving Smart Card." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36552-4_35.

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Gao, Q., and G. S. Moschytz. "A CNN-based Fingerprint Verification System." In Springer Proceedings in Physics. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-30636-6_27.

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Kerschbaum, Florian, Mikhail J. Atallah, David M’Raïhi, and John R. Rice. "Private Fingerprint Verification without Local Storage." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_54.

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Ceguerra, Anna, and Irena Koprinska. "Automatic Fingerprint Verification Using Neural Networks." In Artificial Neural Networks — ICANN 2002. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-46084-5_207.

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Prabhakar, Salil, and Anil K. Jain. "Decision-Level Fusion in Fingerprint Verification." In Multiple Classifier Systems. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-48219-9_9.

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Lee, Kangrok, Kang Ryoung Park, Jain Jang, Sanghoon Lee, and Jaihie Kim. "A Study on Multi-unit Fingerprint Verification." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11527923_15.

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Atti di convegni sul tema "Fingerprint Verification"

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Bahy, Ramy M., Jafar Ababneh, Hani Attar, Mohammad Al-Hihi, Mohamed Hafez, and Ahmed Solyman. "Fingerprint Authentication Method using Two Steps Verification Algorithm." In 2024 25th International Arab Conference on Information Technology (ACIT). IEEE, 2024. https://doi.org/10.1109/acit62805.2024.10877179.

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Khare, Pranav, Sahil Arora, and Sandeep Gupta. "Recognition of Fingerprint Biometric Verification System Using Deep Learning Model." In 2024 International Conference on Data Science and Network Security (ICDSNS). IEEE, 2024. http://dx.doi.org/10.1109/icdsns62112.2024.10691020.

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Khalil, Mohammed S., Dzulkifli Muhammad, Muhammad Khurram Khan, and Qais AL-Nuzaili. "Fingerprint verification using fingerprint texture." In 2009 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2009. http://dx.doi.org/10.1109/isspit.2009.5407549.

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Wenzl, Matthias, and Daniel Kluka. "Adding Channel Security to a Fingerprint Verification Chain." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67356.

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Abstract (sommario):
Authenticating persons using fingerprints is a widely accepted method in the field of access control, border control, prosecution and many others. Today, fingerprint modules with customizable firmware can be bought commercially off the shelf by hobbyists and small companies to be used in their applications and are usually locally separated from a controller implementing the feature extraction and comparison algorithms. As a matter of fact, the communication channel between the sensor and the controller module is susceptible to eavesdropping and man in the middle attacks. Nevertheless, adding c
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Qin, Wei, Yilong Yin, Chunxiao Ren, and Lili Liu. "Video-based fingerprint verification." In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495472.

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Baradarani, A., J. R. B. Taylor, F. Severin, and R. Gr Maev. "Advanced fingerprint verification software." In SPIE Defense + Security, edited by Edward M. Carapezza. SPIE, 2016. http://dx.doi.org/10.1117/12.2224244.

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Jain, A., and Lin Hong. "On-line fingerprint verification." In Proceedings of 13th International Conference on Pattern Recognition. IEEE, 1996. http://dx.doi.org/10.1109/icpr.1996.547016.

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Khalil, Mohammed S., Dzulkifli Muhammad, and Qais AL-Nuzaili. "Fingerprint Verification Using the Texture of Fingerprint Image." In 2009 Second International Conference on Machine Vision. IEEE, 2009. http://dx.doi.org/10.1109/icmv.2009.18.

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Noor, Fazal, and Majed Alhaisoni. "Fingerprint Verification through Cloud Computing." In International Conference. ACM Press, 2013. http://dx.doi.org/10.1145/2536853.2536902.

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Marupudi, Naveena, Eugene John, and Fred Hudson. "Fingerprint verification in multimodal biometrics." In 2006 IEEE Region 5 Conference. IEEE, 2006. http://dx.doi.org/10.1109/tpsd.2006.5507443.

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Rapporti di organizzazioni sul tema "Fingerprint Verification"

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Wilson, Charles L., Craig I. Watson, Michael D. Garris, and Austin Hicklin. Studies of fingerprint matching using the NIST verification test bed (VTB). National Institute of Standards and Technology, 2003. http://dx.doi.org/10.6028/nist.ir.7020.

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