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Relevant bibliographies by topics / Fingerprint biometric

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Academic literature on the topic 'Fingerprint biometric'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Fingerprint biometric"

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K., Krishna Prasad. "A Conceptual Study on Image Enhancement Techniques for Fingerprint Images." International Journal of Applied Engineering and Management Letters (IJAEML) 1, no. 1 (2017): 63–72. https://doi.org/10.5281/zenodo.831678.

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Biometrics is an emerging field of research in recent years and has been devoted to the identification of individuals using one or more intrinsic physical or behavioral traits. Fingerprints are the prominent and widely acceptable biometric features compared to face, speech, iris, and other types of biometrics. Fingerprint characteristic or features are unique for everyone and which cannot change throughout the lifetime. Fingerprint biometrics is having applications in diverse fields like attendance system, criminology, mobile applications and logical access control system. This is the purpose

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Tyagi, S., M. Kumar, D. Singh, and H. Tyagi. "Biometric Cryptosystem Based On Fingerprint Authentication And Cryptography Technique." International Research Journal of Parroha Multiple Campus (IRJPMC) 1, no. 1 (2023): 26–39. https://doi.org/10.5281/zenodo.10258787.

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<i>Biometric systems are one of the most reliable and popular techniques today and fingerprint authentication is one of the most reliable and robust biometric techniques due to its nature. The characteristics of fingerprints play a big and important role in the authentication of people. In this research, fingerprint authentication scheme consists of many stages: image enhancement, binarization, segmentation, spine thinning, detail extraction. In this authentication we use Gaussian filter for better result. Hybrid protection is created through a combination of biometrics and cryptography, such

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Madhav, Yagnasri, Dr S. China Venkateshwarlu, and Dr V. Siva Nagaraju. "Advanced Fingerprint Alteration Detection: A Comparative Analysis of Real and Synthetic Modifications Using InceptionV3 on the SOCOFing Dataset." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 07 (2025): 1–9. https://doi.org/10.55041/ijsrem51223.

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This study investigates the efficacy of fingerprint alteration detection using advanced deep learning techniques, specifically focusing on both real and synthetically altered fingerprint images. Utilizing the Sokoto Coventry Fingerprint Dataset (SOCOFing), which comprises over 55,000 fingerprint images from 600 African subjects, we employed the Google InceptionV3 model to classify real and altered images under varying degrees of alteration complexity. Our experimental results demonstrate a robust performance of the model, achieving an accuracy of 91.04% for detecting alterations with easy alte

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Yu, Yirong, Qiming Niu, Xuyang Li, Jianshe Xue, Weiguo Liu, and Dabin Lin. "A Review of Fingerprint Sensors: Mechanism, Characteristics, and Applications." Micromachines 14, no. 6 (2023): 1253. http://dx.doi.org/10.3390/mi14061253.

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Identification technology based on biometrics is a branch of research that employs the unique individual traits of humans to authenticate identity, which is the most secure method of identification based on its exceptional high dependability and stability of human biometrics. Common biometric identifiers include fingerprints, irises, and facial sounds, among others. In the realm of biometric recognition, fingerprint recognition has gained success with its convenient operation and fast identif ication speed. Different fingerprint collecting techniques, which supply fingerprint information for f

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Fatamatuz, Ayasa Khan. "Improvement of Biometric Authentication System Applying Fingerprint." International Journal of Engineering Research & Science 4, no. 12 (2018): 19–26. https://doi.org/10.5281/zenodo.2529363.

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<strong><em>Abstract</em></strong><strong>—</strong><em>.</em><em>The biometric system plays an important role in everyone life. To identify one identity, the finger is one of many forms of the biometrics are generally used. The fingerprint is the verified function to identify a match between two person’s fingerprints. </em><em>Here a simple and effective system for biometric fingerprint based voter identity system has been proposed that is based on image enhancement and correct minutiae extraction. Automatic and reliable extraction of minutiae from fingerprint images is a critical

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Tyagi, Shivani, Manish Kumar, Dharambeer Singh, and Hariom Tyagi. "Biometric Cryptosystem Based On Fingerprint Authentication And Cryptography Technique." International Research Journal of Parroha Multiple Campus 1, no. 1 (2022): 26–39. http://dx.doi.org/10.61916/prmn.2023.v0101.004.

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Biometric systems are one of the most reliable and popular techniques today and fingerprint authentication is one of the most reliable and robust biometric techniques due to its nature. The characteristics of fingerprints play a big and important role in the authentication of people. In this research, fingerprint authentication scheme consists of many stages: image enhancement, binarization, segmentation, spine thinning, detail extraction. In this authentication we use Gaussian filter for better result. Hybrid protection is created through a combination of biometrics and cryptography, such as

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Jadaan Abed, Abdulrasool, and Dhahir Abdulhadi Abdullah. "An Automated Fingerprint Image Detection and Localization Approach-based Unsupervised Learning Algorithms using Low-quality Biometrics Plam Data." JOIV : International Journal on Informatics Visualization 8, no. 3-2 (2024): 1635. https://doi.org/10.62527/joiv.8.3-2.1665.

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In this study, fingerprint identification and classification of low-quality fingerprints have been analyzed accordingly. As technology advances and methodologies evolve, staying at the forefront of research and innovation is imperative. The challenges addressed in this paper provide a foundation for future investigations and underscore the importance of developing resilient and adaptable biometric systems for real-world applications. The quest for accurate, efficient, and robust fingerprint identification in adverse conditions is a testament to the continuous evolution and refinement of machin

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Bhatti, Kamran Ali, Dr Sajida Parveen, Nadeem Naeem Bhatti, Kamran Ali Larik, and Qurat-ul-ain Soomro. "Fingerprint liveness detection using dynamic local ternary pattern (DLTP)." VFAST Transactions on Software Engineering 12, no. 2 (2024): 123–31. http://dx.doi.org/10.21015/vtse.v12i2.1842.

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Nowadays, biometric confirmation systems are utilized for security applications such as verification and identification. There are various biometric modalities such as fingerprints, face recognition, and iris scans. Biometric systems are superior to PIN and password-based systems because the latter can be easily stolen or forgotten, whereas biometric traits are unique and difficult to replicate or forget. Among biometric modalities, fingerprint recognition is widely employed for security purposes due to the distinctiveness of each individual's fingerprint. However, fingerprint biometric system

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Abdulsattar, M. Ibrahim, K. Eesee Abdulrahman, and Rafi Omar Al-Nima Raid. "Deep fingerprint classification network." TELKOMNIKA (Telecommunication, Computing, Electronics and Control) 19, no. 3 (2021): 893–901. https://doi.org/10.12928/telkomnika.v19i3.18771.

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Fingerprint is one of the most well-known biometrics that has been used for personal recognition. However, faked fingerprints have become the major enemy where they threat the security of this biometric. This paper proposes an efficient deep fingerprint classification network (DFCN) model to achieve accurate performances of classifying between real and fake fingerprints. This model has extensively evaluated or examined parameters. Total of 512 images from the ATVS-FFp_DB dataset are employed. The proposed DFCN achieved high classification performance of 99.22%, where fingerprint images are suc

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Fatema, A. Shaikh*, and Prof.S.O.Rajankar. "BIOMETRIC AUTHENTICATION SYSTEM USING RPI." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 4 (2016): 839–44. https://doi.org/10.5281/zenodo.50420.

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A biometric authentication system acquires biometric sample such as fingerprint. The fingerprint signifies physiological features of an individual.This is a system which maintains the attendance records of students automatically. In this  designing of an efficient module that comprises of a fingerprint sensor to manage the attendance records of students. This module enrolls the student’s as well as staff’s fingerprints. This enrolling is a onetime process and their fingerprints will be stored in the fingerprint sensor. During enrolling of fingerprints alone requires a system s

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Dissertations / Theses on the topic "Fingerprint biometric"

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Ferrara, Matteo <1979&gt. "Biometric Fingerprint Recognition Systems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1234/1/TesiFinale_-_Matteo_Ferrara.pdf.

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Ferrara, Matteo <1979&gt. "Biometric Fingerprint Recognition Systems." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1234/.

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Green, Nathan Alan. "Establishing Public Confidence in the Viability of Fingerprint Biometric Technology." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd919.pdf.

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Diefenderfer, Graig T. "Fingerprint recognition." Thesis, Monterey California. Naval Postgraduate School, 2006. http://hdl.handle.net/10945/2761.

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The use of biometrics is an evolving component in today's society. Fingerprint recognition continues to be one of the most widely used biometric systems. This thesis explores the various steps present in a fingerprint recognition system. The study develops a working algorithm to extract fingerprint minutiae from an input fingerprint image. This stage incorporates a variety of image pre-processing steps necessary for accurate minutiae extraction and includes two different methods of ridge thinning. Next, it implements a procedure for matching sets of minutiae data. This process goes through all

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Tungala, Nikhil C. "Contextual biometric watermarking of fingerprint images." Morgantown, W. Va. : [West Virginia University Libraries], 2004. https://etd.wvu.edu/etd/controller.jsp?moduleName=documentdata&jsp%5FetdId=3686.

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Thesis (M.S.)--West Virginia University, 2004.<br>Title from document title page. Document formatted into pages; contains viii, 69 p. : ill. Includes abstract. Includes bibliographical references (p. 62-69).

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Šmida, Vladimír. "Fingerprint Image Quality Assessment." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-237090.

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Kritickým prvkem biometrického systému pro rozpoznávání otisků prstů je proces snímání. Kvalita snímku totiž ovlivňuje všechny další části systému počínaje zpracováním obrazu, přes extrakci rysů až po samotné rozhodnutí. Přestože bylo navrženo několik metod určování kvality snímku, chybějící formální specifikace kvality otisku nedovoluje ověřit jejich přesnost. Tato diplomová práce se zabývá hodnocením metod určujících kvalitu biometrického signálu otisku prstu. Popisuje jednotlivé faktory ovlivňující kvalitu spolu se současnými přístupy používanými pro její odhad. V práci je rovněž vysvětlena

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Varadinov, Petr. "Účel a implementace snímání otisků prstů v osobních počítačích." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-162689.

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This diploma thesis deals with fingerprint recognition applied in personal computers. The topic is analyzed both chronologically in historical context and in connection with other biometric methods. The thesis provides a comprehensive survey of the topic. It starts with physical layer, goes through hardware parts and ends with software architecture. A special attention is paid to programming fingerprint recognition support into end-user applications. These are the aims of the thesis: to place the silicon fingerprint sensing technology into the historical context and describe its evolution in c

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Mokhled, Al Tarawneh. "Fingerprint image processing for generating biometric cryptographic key." Thesis, University of Newcastle Upon Tyne, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.514462.

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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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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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Gupta, Gaurav. "Models and protocols for evaluation of fingerprint sensors." Morgantown, W. Va. : [West Virginia University Libraries], 2005. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4361.

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Thesis (M.S.)--West Virginia University, 2005.<br>Title from document title page. Document formatted into pages; contains vi, 78 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 71-75).

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Books on the topic "Fingerprint biometric"

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Jain, L. C., U. Halici, I. Hayashi, S. B. Lee, and S. Tsutsui. INTELLIGENT BIOMETRIC TECHNIQUES in FINGERPRINT and FACE RECOGNITION. Routledge, 2022. http://dx.doi.org/10.1201/9780203750520.

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Bhanu, Bir. Computational algorithms for fingerprint recognition. Kluwer Academic Publishers, 2003.

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Sharma, Purushottam. Fingerprints biometrics: Cradle to coffin. Bright Law House, 2010.

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Sharma, Purushottam. Fingerprints biometrics: Cradle to coffin. Bright Law House, 2010.

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Asad, Ali. Biometrics: An investigation of fingerprint authentication systems. University of East London, 2001.

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Piuri, Vincenzo, Fabio Scotti, and Ruggero Donida Labati. Touchless Fingerprint Biometrics. Taylor & Francis Group, 2017.

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Touchless Fingerprint Biometrics. Taylor & Francis Group, 2015.

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Piuri, Vincenzo, Fabio Scotti, and Ruggero Donida Labati. Touchless Fingerprint Biometrics. Taylor & Francis Group, 2015.

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Piuri, Vincenzo, Fabio Scotti, and Ruggero Donida Labati. Touchless Fingerprint Biometrics. Taylor & Francis Group, 2015.

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Piuri, Vincenzo, Fabio Scotti, and Ruggero Donida Labati. Touchless Fingerprint Biometrics. Taylor & Francis Group, 2015.

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Book chapters on the topic "Fingerprint biometric"

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Zhang, Meng, Jianjiang Feng, and Jie Zhou. "Fingerprint Presentation Attack Detection via Analyzing Fingerprint Pairs." In Biometric Recognition. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31456-9_2.

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Ross, Arun, Sarat C. Dass, and Anil K. Jain. "Estimating Fingerprint Deformation." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_35.

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Barral, Claude, Jean-Sébastien Coron, and David Naccache. "Externalized Fingerprint Matching." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_43.

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Lorch, Henning, Peter Morguet, and Hartmut Schröder. "Fingerprint Distortion Measurement." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25976-3_11.

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Ratha, Nalini K., Jonathan H. Connell, and Ruud M. Bolle. "Secure Fingerprint Authentication." In Biometric Solutions. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1053-6_11.

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Smith, Marcus, and Seumas Miller. "The Rise of Biometric Identification: Fingerprints and Applied Ethics." In Biometric Identification, Law and Ethics. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-90256-8_1.

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AbstractIn the late nineteenth century, it became understood that the patterns on the skin of the fingers were unique and could be used for identification purposes, leading to the development of biometric identification (Smith M, Mann M, Urbas G. Biometrics, crime and security. Routledge, 2018). The ease with which fingerprints can be accessed and recorded, and the ease with which they transfer to surfaces and objects, made them ideal for law enforcement purposes. Today, in digital form, fingerprints and other biometric identification techniques, notably DNA profiles and facial recognition tec

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Chen, Fanglin, and Jie Zhou. "On the Influence of Fingerprint Area in Partial Fingerprint Recognition." In Biometric Recognition. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35136-5_13.

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Jia, Yuwei, Zhe Cui, and Fei Su. "Unsupervised Fingerprint Dense Registration." In Biometric Recognition. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-8565-4_1.

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Liu, Manhua, Xudong Jiang, and Alex Chichung Kot. "Fingerprint Reference Point Detection." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_38.

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Yau, Wei Yun, Tai Pang Chen, and Peter Morguet. "Benchmarking of Fingerprint Sensors." In Biometric Authentication. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25976-3_9.

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Conference papers on the topic "Fingerprint biometric"

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Juneja, Akshay, Priyanka Kumari, Monika Bharti, Himanshu Jindal, Girish Wadhwa, and Pirmohammad Khan. "Revival of Fingerprint Recognition-based Biometric Systems." In 2024 Eighth International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2024. https://doi.org/10.1109/pdgc64653.2024.10984054.

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Tomar, Raman, Himanshu Parshar, Dinesh Singh, and Indu. "IOT-Based Biometric Fingerprint Identification In Bank Locker." In 2024 1st International Conference on Advances in Computing, Communication and Networking (ICAC2N). IEEE, 2024. https://doi.org/10.1109/icac2n63387.2024.10895063.

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K, Mughunthan M., Nadarajan R, and P. Umamaheswari. "Biometric Breakthroughs : Improving Service And Security With Fingerprint Recognition." In 2025 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI). IEEE, 2025. https://doi.org/10.1109/icdsaai65575.2025.11011876.

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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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Adami, Banafsheh, MohammadReza Hosseinzadehketilateh, and Nima Karimian. "Contactless Fingerprint Biometric Anti-Spoofing: An Unsupervised Deep Learning Approach." In 2024 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2024. http://dx.doi.org/10.1109/ijcb62174.2024.10744434.

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Keerthana, N. V., and M. Parimala Devi. "A Comprehensive Analysis of Minutiae Point Extraction in Biometric FingerPrint." In 2024 13th International Conference on System Modeling & Advancement in Research Trends (SMART). IEEE, 2024. https://doi.org/10.1109/smart63812.2024.10882188.

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Sarangaraja, A. P., D. Rajagopalan, A. Vignesh, and P. Mohamed Fathimal. "Secret Sharing Scheme with Fingerprint Authentication." In International Research Conference on IOT, Cloud and Data Science. Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-u6em0l.

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Medical imaging is very important in medical diagnosis. X-rays, ultrasound images, CT scans, brain pictures, and patient mri images are examples of images that contain sensitive information. However, poor communication channels and loopholes in hospital and medical centre storage systems risk accessing these images by unauthorised individuals who utilise them for nefarious purposes other than diagnostics. Image encryption is a common strategy for enhancing the integrity of communication and storage channels for protecting medical images from unauthorized access. This task proposes a biometrics

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Aguilar, Gualberto, Gabriel Sanchez, Karina Toscano, Mariko Nakano, and Hector Perez. "Multimodal biometric system using fingerprint." In 2007 International Conference on Intelligent and Advanced Systems (ICIAS). IEEE, 2007. http://dx.doi.org/10.1109/icias.2007.4658364.

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Chao, Liwen, Thalita Nazaré, and Erivelton Nepomuceno. "Key Generation from Fingerprint Biometric." In 2023 15th IEEE International Conference on Industry Applications (INDUSCON). IEEE, 2023. http://dx.doi.org/10.1109/induscon58041.2023.10374712.

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Diniz, Elioenai M. F., João V. C. Mazzochin, Luiz A. Zanlorensi, et al. "A Mathematical Toolkit to improve the Similarity Analysis for Fingerprint Images." In Workshop de Sistemas de Informação. Sociedade Brasileira de Computação, 2024. https://doi.org/10.5753/wsis.2024.33664.

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While fingerprint biometrics are a mature technology, preprocessing steps such as image alignment and minutiae filtering still significantly impact their performance. To address these challenges, this paper introduces a comprehensive package of analytical methods designed to enhance fingerprint image similarity analysis. Initially, we present an alignment method based on partitioning and statistical image analysis, which does not rely on specific information, such as the location of singular points. Next, a minutiae filtering method is developed, focusing on detecting and removing edge minutia

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Reports on the topic "Fingerprint biometric"

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Varastehpour, Soheil, Hamid Sharifzadeh, Iman Ardekani, and Abdolhossein Sarrafzadeh. Human Biometric Traits: A Systematic Review Focusing on Vascular Patterns. Unitec ePress, 2020. http://dx.doi.org/10.34074/ocds.086.

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Authentication methods based on human traits, including fingerprint, face, iris, and palm print, have developed significantly, and currently they are mature enough to be reliably considered for human identification purposes. Recently, as a new research area, a few methods based on non-facial skin features such as vein patterns have been developed. This literature review paper explores some key biometric systems such as face recognition, iris recognition, fingerprint, and palm print, and discusses their respective advantages and disadvantages; then by providing a comprehensive analysis of these

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Wu, Jin Chu, and Charles L. Wilson. Using Chebyshev's inequality to determine sample size in biometric evaluation of fingerprint data. National Institute of Standards and Technology, 2005. http://dx.doi.org/10.6028/nist.ir.7273.

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Newton, Elaine, Gerry Coleman, and Patrice Yuh. Information systems-data format for the interchange of fingerprint, facial, & other biometric information- part 2 :. National Institute of Standards and Technology, 2008. http://dx.doi.org/10.6028/nist.sp.500-275.

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Podio, Fernando L., Dylan Yaga, and Christofer J. McGinnis, eds. Conformance Testing Methodology for ANSI/NIST-ITL 1-2011, Data Format for the Interchange of Fingerprint, Facial and Other Biometric Information (Release 1.0). National Institute of Standards and Technology, 2012. http://dx.doi.org/10.6028/nist.sp.500-295.

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Wing, Bradford J. Data Format for the Interchange of Fingerprint, Facial and Other Biometric Information ANSI/NIST-ITL 1-2011 NIST Special Publication 500-290 Edition 2. National Institute of Standards and Technology, 2013. http://dx.doi.org/10.6028/nist.sp.500-290e2.

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Mangold, Kevin C. Data Format for the Interchange of Fingerprint, Facial and Other Biometric Information ANSI/NIST-ITL 1-2011 NIST Special Publication 500-290 Edition 3. National Institute of Standards and Technology, 2016. http://dx.doi.org/10.6028/nist.sp.500-290e3.

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McGinnis, Christofer J., Dylan J. Yaga, and Fernando L. Podio. Conformance Testing Methodology Framework for ANSI/NIST-ITL 1-2011 Update: 2013, Data Format for the Interchange of Fingerprint, Facial [and] Other Biometric Information. National Institute of Standards and Technology, 2015. http://dx.doi.org/10.6028/nist.sp.500-304.

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Harriss, Lydia, and Khalil Davis. Biometric Technologies. Parliamentary Office of Science and Technology, 2018. http://dx.doi.org/10.58248/pn578.

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Biometric technologies identify individuals based on their distinguishing physical and behavioural attributes, such as fingerprints, face, and voice. Unlike passwords or traditional identity documents, biometric attributes are inherently linked to a person and cannot usually be lost or forgotten, potentially providing greater security and convenience. This briefing focuses on how these technologies work, their applications, and the policy challenges raised by their use.

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