Bibliographies thématiques / Knuckle prints

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Littérature scientifique sur le sujet « Knuckle prints »

Auteur : Grafiati
Publié le 7 juin 2025
Mis à jour le 2 août 2025

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Articles de revues sur le sujet "Knuckle prints"

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Ardra, Vijay V. R.*. "Comparative and Identify the Kunckle Prints in Right and Left Hand of Male and Female, On the Basis of Bifurcation and Ridge Ending." International Journal of Scientific Research and Technology 2, no. 5 (2025): 117–23. https://doi.org/10.5281/zenodo.15345253.

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Knuckle prints are unique patterns, it contains ridges and furrows on the dorsal surface of the hand. Knuckle prints are used biometric identifier. These prints contain biological features like minutiae.The objective of this research is to investigate, the comparative analysis of knuckle prints in both hands of male and female individual. The study emphasizes the variations in ridge endings and bifurcations between right and left hand. Data collection involves gathering knuckle patterns from individuals aged 20 and above, with a target of 100 samples from each gender. The analysis focuses on t
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Hegde, Chetana, P. Deepa Shenoy, K. R. Venugopal, and L. M. Patnaik. "Authentication using Finger Knuckle Prints." Signal, Image and Video Processing 7, no. 4 (2013): 633–45. http://dx.doi.org/10.1007/s11760-013-0469-7.

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Biswas, Prachi Sharma, and Swati Dubey Mishra. "Novel Approach For Personal Identification Using Dorsal Knuckle Crease Patterns: A Pilot Study." Mapana Journal of Sciences 23, no. 4 (2024): 83–97. https://doi.org/10.12723/mjs.71.5.

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Despite the availability of various identification methods, such as fingerprints, ridge density, palm prints, and vein patterns, forensic identification remains a complex challenge. While substantial research has been conducted on the palmar surface of the hand, there has been limited focus on the dorsal surface for identification purposes. The dorsal surface, like fingerprints, contains minutiae and skin crease patterns believed to be permanent. The crease patterns present on the dorsal side of the proximal interphalangeal joints are known as knuckle crease patterns. This research aimed to cl
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Grover, J., and M. Hanmandlu. "Personal identification using the rank level fusion of finger-knuckle-prints." Pattern Recognition and Image Analysis 27, no. 1 (2017): 82–93. http://dx.doi.org/10.1134/s1054661817010059.

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Maheshwari, Uma, and Kalpana Kalpana. "Multimodal Image Fusion in Biometric Authentication." Fusion: Practice and Applications 1, no. 2 (2020): 79–91. http://dx.doi.org/10.54216/fpa.010203.

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During this study, a unique multimodal biometric system was constructed. This system incorporated a variety of unimodal biometric inputs, including fingerprints, palmprints, knuckle prints, and retina images. The multimodal system generated the fused template via feature-level fusion, which combined several different biometric characteristics. The Gabor filter extracted the features from the various biometric aspects. The fusion of the extracted information from the fingerprint, knuckle print, palmprint, and retina into a single template, which was then saved in the database for authentication
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Eaker, Adam. "The Art of Marring a Face: Exhibiting Boxers in Georgian London." Huntington Library Quarterly 87, no. 2 (2024): 165–82. https://doi.org/10.1353/hlq.2024.a964270.

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ABSTRACT: Bare-knuckle boxing matches provided some of the most ambivalent experiences of spectatorship in late Georgian England. Brutally violent and banned by law, prizefights nonetheless enjoyed an ardent following. Artists attended bouts, reveling in the opportunity to study musclebound athletes who seemed to reincarnate classical perfection. Pugilists in turn borrowed the language of artistic display, terming their training grounds “academies” and their bouts “exhibitions.” They also inspired a proliferation of images, ranging from grand painted portraits to popular prints that both celeb
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Goh, Michael K. O., Connie Tee, and Andrew B. J. Teoh. "BI-MODAL PALM PRINT AND KNUCKLE PRINT RECOGNITION SYSTEM." Journal of IT in Asia 3, no. 1 (2016): 85–106. http://dx.doi.org/10.33736/jita.37.2010.

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This paper proposed an innovative contact-less palm print and knuckle print recognition system. Palm print is referred to as line textures, which contains principal lines, wrinkles and ridges on the inner surface of the palm. On the other hand, knuckle print is denoted as the flexion lines on the inner skin of the knuckles of the fingers. These line patterns are unique and stable, and they offer abundance of useful information for personal recognition. We present a novel palm print and knuckle print tracking approach to automatically detect and capture these features from low resolution video
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Yadav, Vandana, Vinayak Bharadi, and Sunil K. Yadav. "Texture Feature Extraction Using Hybrid Wavelet Type I & II for Finger Knuckle Prints for Multi-algorithmic Feature Fusion." Procedia Computer Science 79 (2016): 359–66. http://dx.doi.org/10.1016/j.procs.2016.03.047.

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Yadav, Vandana, Vinayak Bharadi, and Sunil K. Yadav. "Feature Vector Extraction based Texture Feature using Hybrid Wavelet Type I & II for Finger Knuckle Prints for Multi-Instance Feature Fusion." Procedia Computer Science 79 (2016): 351–58. http://dx.doi.org/10.1016/j.procs.2016.03.046.

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Abdullahi, Umar, and Hambali Moshood Abiola. "Survey of Finger Knuckle Print Recognition and Authentication." Kwaghe International Journal of Sciences and Technology 1, no. 1 (2024): 383–402. https://doi.org/10.58578/kijst.v1i1.3611.

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Background: Finger knuckle (FK) has gained significant attention as a biometric characteristic in recent years. Its unique features, such as visible lines, wrinkles, and ridges on the external surface of finger knuckles, make it an economically viable option for human identification. FK serves as the foundation for many biometric systems. Aim: This report presents a comprehensive analysis of relevant FK research. The typical FK identification system consists of four steps: image acquisition, image preprocessing, feature extraction, and matching. Various methods have been employed at each stage
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Thèses sur le sujet "Knuckle prints"

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El-Tarhouni, Wafa. "Finger knuckle print and palmprint for efficient person recognition." Thesis, Northumbria University, 2017. http://nrl.northumbria.ac.uk/36145/.

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Biometric person recognition systems are increasingly being used to enhance the security of physical and logical security systems. Palmprint and finger knuckle print recognition have gained attention in research and practical domains, providing a means of identification for security system access and personal recognition and presenting an interesting and challenging research problem. The overall aim of this work is to investigate biometric systems able to recognise people using their palmprints and finger knuckle prints. The work investigates the theoretical concepts behind palmprint and finge
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Livres sur le sujet "Knuckle prints"

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Premalatha, K., and N. B. Mahesh Kumar. Finger Knuckle-Print Authentication Using Fast Discrete Orthonormal Stockwell Transform. Anchor Academic Publishing. ein Imprint der Diplomica Verlag GmbH, 2017.

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Premalatha, K., and N. B. Mahesh Kumar. Certain Investigations on Transform Based Techniques in Palmprint and Finger Knuckle-Print Biometrics for Personal Authentification. GRIN Verlag GmbH, 2017.

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Chapitres de livres sur le sujet "Knuckle prints"

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Lai, Xinbo, Yimin Xue, Tayir Tursun, Nurbiya Yadikarl, and Kurban Ubul. "Multimodal Finger Recognition Based on Feature Fusion Attention for Fingerprints, Finger-Veins, and Finger-Knuckle-Prints." In Lecture Notes in Computer Science. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-8499-8_31.

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Zhang, David, Guangming Lu, and Lei Zhang. "Finger-Knuckle-Print Verification." In Advanced Biometrics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61545-5_5.

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Zhai, Yikui, Cuilin Yu, and Vincenzo Piuri. "Finger Knuckle Print Recognition." In Encyclopedia of Cryptography, Security and Privacy. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-642-27739-9_1516-1.

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Zhai, Yikui, Cuilin Yu, and Vincenzo Piuri. "Finger Knuckle Print Recognition." In Encyclopedia of Cryptography, Security and Privacy. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-030-71522-9_1516.

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Xiong, Ming, Wankou Yang, and Changyin Sun. "Finger-Knuckle-Print Recognition Using LGBP." In Advances in Neural Networks – ISNN 2011. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21090-7_32.

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Zhang, David, Guangming Lu, and Lei Zhang. "Local Features for Finger-Knuckle-Print Recognition." In Advanced Biometrics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61545-5_6.

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Zhang, David, Guangming Lu, and Lei Zhang. "Global Information for Finger-Knuckle-Print Recognition." In Advanced Biometrics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61545-5_7.

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Liu, Ming, Yongmei Tian, and Yinghui Ma. "Inner-Knuckle-Print Recognition Based on Improved LBP." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34531-9_66.

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Gao, Guangwei, and Jian Yang. "Weight Competitive Coding for Finger-Knuckle-Print Verification." In Biometric Recognition. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02961-0_23.

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Wang, Yuqi, Bob Zhang, Shuyi Li, and Hao Yang. "A Generative Method for Finger Knuckle Print Recognition." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-78104-9_20.

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Actes de conférences sur le sujet "Knuckle prints"

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Singh, Indu, Suraj Kakaralapudi, Nihal Jaychandran, and Neil Roy. "Hybrid Honey Badger-Grey Wolf Optimized Siamese Network for Multimodal of Finger Vein and Finger Knuckle Print." In 2024 IEEE International Conference on Smart Power Control and Renewable Energy (ICSPCRE). IEEE, 2024. http://dx.doi.org/10.1109/icspcre62303.2024.10675202.

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Makul, Ozge, and Murat Ekinci. "Biyometric identification based on knuckle prints." In 2014 22nd Signal Processing and Communications Applications Conference (SIU). IEEE, 2014. http://dx.doi.org/10.1109/siu.2014.6830621.

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Sadik, Mona A., Maryam N. Al-Berry, and Mohamed Roushdy. "A survey on the finger knuckle prints biometrie." In 2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS). IEEE, 2017. http://dx.doi.org/10.1109/intelcis.2017.8260036.

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Belguechi, R., E. Cherrier, M. El Abed, and C. Rosenberger. "Evaluation of Cancelable Biometric Systems: Application to Finger-Knuckle-Prints." In 2011 International Conference on Hand-Based Biometrics (ICHB). IEEE, 2011. http://dx.doi.org/10.1109/ichb.2011.6094326.

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Sadik, Mona A., Maryam N. Al-Berry, and Mohamed Roushdy. "A robust alignment-based personal recognition using center inner Knuckle prints." In 2017 Eighth International Conference on Intelligent Computing and Information Systems (ICICIS). IEEE, 2017. http://dx.doi.org/10.1109/intelcis.2017.8260037.

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Chaa, Mourad, Naceur-Eddine Boukezzoula, Abdallah Meraoumia, and Maarouf Korichi. "An efficient biometric based personal authentication system using Finger Knuckle Prints features." In 2016 International Conference on Information Technology for Organizations' Development (IT4OD). IEEE, 2016. http://dx.doi.org/10.1109/it4od.2016.7479314.

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Rodrigues, E. O., T. M. Porcino, Aura Conci, and Aristofanes C. Silvah. "A simple approach for biometrics: Finger-knuckle prints recognition based on a Sobel filter and similarity measures." In 2016 International Conference on Systems, Signals and Image Processing (IWSSIP). IEEE, 2016. http://dx.doi.org/10.1109/iwssip.2016.7502723.

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Fei, Lunke, Bob Zhang, Shaohua Teng, An Zeng, Chunwei Tian, and Wei Zhang. "Learning Discriminative Finger-knuckle-print Descriptor." In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8683156.

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Hegde, Chetana, J. Phanindra, P. Deepa Shenoy, K. R. Venugopal, and L. M. Patnaik. "Human authentication using finger knuckle print." In the Fourth Annual ACM Bangalore Conference. ACM Press, 2011. http://dx.doi.org/10.1145/1980422.1980431.

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Bhattacharya, Nivedita, and Deepak Kumar Dewangan. "Fusion technique for finger knuckle print recognition." In 2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO). IEEE, 2015. http://dx.doi.org/10.1109/eesco.2015.7253990.

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