Relevant bibliographies by topics / Palmprint Recognition

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Palmprint Recognition'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Palmprint Recognition"

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Kumar, Jayakrishnan S. "Palmprint Recognition in Uncontrolled and Unco-operative Environment." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (2021): 1711–18. http://dx.doi.org/10.22214/ijraset.2021.37646.

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Abstract: On-line palmprint recognition and latent palmprint identification unit two branches of palmprint studies. The previous uses middle-resolution footage collected by a camera in an exceedingly} very well-controlled or contact-based surroundings with user cooperation for industrial applications and so the latter uses high resolution latent palmprints collected in crime scenes for rhetorical investigation. However, these two branches do not cowl some palmprint footage that have the potential for rhetorical investigation. Attributable to the prevalence of smartphone and shopper camera, fur
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Zhao, Shuping, Lunke Fei, and Jie Wen. "Multiview-Learning-Based Generic Palmprint Recognition: A Literature Review." Mathematics 11, no. 5 (2023): 1261. http://dx.doi.org/10.3390/math11051261.

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Palmprint recognition has been widely applied to security authentication due to its rich characteristics, i.e., local direction, wrinkle, and texture. However, different types of palmprint images captured from different application scenarios usually contain a variety of dominant features. Specifically, the palmprint recognition performance will be degraded by the interference factors, i.e., noise, rotations, and shadows, while palmprint images are acquired in the open-set environments. Seeking to handle the long-standing interference information in the images, multiview palmprint feature learn
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Al-Taie, Sara A. Mohammed, and Baydaa I. Khaleel. "Palm Print Recognition Using Intelligent Techniques: A review." Jurnal Ilmiah Teknik Elektro Komputer dan Informatika 9, no. 1 (2023): 156–64. https://doi.org/10.26555/jiteki.v9i1.25777.

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Hand or Palm print recognition systems are one of the efficient people recognition and authentication systems that provide high-security levels by approving the entering and exiting of people such as employees in the work field or companies. The basis for using palmprints lies in the fact that no two individuals have exactly the same palmprint pattern, moreover palmprints remain more or less stablethroughout the lifetime and are easily obtainable using standard imaging techniques. Palm print recognition systems process picture data from a photograph of a person's palm and compare it to a recor
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Ma, Ye, and Zhenhua Guo. "Palmprint Translation Network for Cross-Spectral Palmprint Recognition." Electronics 11, no. 5 (2022): 736. http://dx.doi.org/10.3390/electronics11050736.

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Nowadays, palmprint recognition has been well developed since plenty of promising algorithms have emerged. Palmprints have also been applied under various authentication scenarios. However, these approaches are designed and tested only when the registration images and probe images are taken under the same illumination condition; thus, a cross-spectral performance degradation is speculated. Therefore, we test the cross-spectral performance of extended binary orientation co-occurrence vector (E-BOCV), which is unsatisfactory, illustrating the necessity of a specific algorithm. Trying to achieve
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Sen Lin, Sen Lin, Man Li Sen Lin, Meng-Zhao Liu Man Li, Xiang-Ji Fan Meng-Zhao Liu, and Peng Shang Xiang-Ji Fan. "LDBM-PFR: Local Directional Binary Pattern Mixed Filtering for 2D and 3D Palmprint Fusion Recognition." 電腦學刊 35, no. 2 (2024): 059–74. http://dx.doi.org/10.53106/199115992024043502004.

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<p>Single-dimensional palmprint images are susceptible to interference from noise, lighting, and various factors, leading to information loss and subpar recognition performance. To address the problem, a fusion recognition scheme of 2D and 3D palmprints based on Hybrid Filter Local Orientation Binary Pattern (HFLOBP) is proposed. Firstly, the HFLOBP algorithm is employed to extract 2D features and 3D Shape Index (SI) features respectively to improve the recognition effect. Secondly, Principal Component Analysis (PCA) is utilized to improve the recognition efficiency, to reduce the dimens
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Abdulhmid Mohamed Hussin ALBEERISH, Zwha, and Saedah Mohammed Omar ALBEERISH. "PALMPRINT RECOGNITION." MINAR International Journal of Applied Sciences and Technology 2, no. 3 (2020): 21–27. http://dx.doi.org/10.47832/2717-8234.3-2.4.

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Palmprint is an example of physiological characteristics of an individual, which can be easily captured by using some types of sensors and cameras. The palmprint has many nature compositions, which contain rich features that mainly used for distinguishing such as, wrinkles, ridges, principal lines, singular, and minutiae points. These make a palmprint as one of a unique biometric and reliable for human recognition. In this work have used multiple correlation filters per class for performing palmprint classification algorithm
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Taouche, Cherif, Hacene Belhadef, and Zakaria Laboudi. "Palmprint Recognition System Based on Multi-Block Local Line Directional Pattern and Feature Selection." International Journal of Information Technologies and Systems Approach 15, no. 1 (2022): 1–26. http://dx.doi.org/10.4018/ijitsa.292042.

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In this paper, we deal with multimodal biometric systems based on palmprint recognition. In this regard, several palmprint-based approaches have been already proposed. Although these approaches show interesting results, they have some limitations in terms of recognition rate, running time and storage space. To fill this gap, we propose a novel multimodal biometric system combining left and right palmprints. For building this multimodal system, two compact local descriptors for feature extraction are proposed, fusion of left and right palmprints is performed at feature-level, and feature select
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Harun, Nurzalina, Abd Rahman Wan Enyzarina Wan, Sitizaleha Zainal Abidin, and Puwira Jaya Othman. "MODIFIED ALGORITHM OF EXTRACTION OF REGION OF INTEREST (ROI) FOR PALMPRINT IDENTIFICATION." COMPUSOFT: An International Journal of Advanced Computer Technology 07, no. 11 (2018): 2909–15. https://doi.org/10.5281/zenodo.14810809.

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Palmprint trait has emerged as a means of new and practical biometric recognition system. Palmprint is divided into three regions known as interdigital, hypothenar and thenar. These regions contain a bundle of patterns such as creases, ridges, minutiae and pores that are believed to be unique and distinct in establishing the identity of a person. The process of extracting the palmprint ROI is a crucial and important initial process for personal identification. In obtaining palmprint ROI, there are numerous algorithms that have been proposed by past researchers. However, to the best of our know
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Kusban, Muhammad, Aris Budiman, and Bambang Hari Purwoto. "Image enhancement in palmprint recognition: a novel approach for improved biometric authentication." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1299. http://dx.doi.org/10.11591/ijece.v14i2.pp1299-1307.

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Several researchers have used image enhancement methods to reduce detection errors and increase verification accuracy in palmprint identification. Divergent opinions exist among experts regarding the best method of image filtering to improve image palmprint recognition. Because of the unique characteristics of palmprints and the difficulties in preventing counterfeiting, image-filtering techniques are the subject of this current research. Researchers hope to create the best biometric system possible by utilizing various techniques. These techniques include image enhancement, Gabor orientation
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Kusban, Muhammad, Aris Budiman, and Bambang Hari Purwoto. "Image enhancement in palmprint recognition: a novel approach for improved biometric authentication." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1299–307. https://doi.org/10.11591/ijece.v14i2.pp1299-1307.

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Several researchers have used image enhancement methods to reduce detection errors and increase verification accuracy in palmprint identification. Divergent opinions exist among experts regarding the best method of image filtering to improve image palmprint recognition. Because of the unique characteristics of palmprints and the difficulties in preventing counterfeiting, image-filtering techniques are the subject of this current research. Researchers hope to create the best biometric system possible by utilizing various techniques. These techniques include image enhancement, Gabor orientation
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Dissertations / Theses on the topic "Palmprint Recognition"

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Genovese, A. "CONTACTLESS AND LESS-CONSTRAINED PALMPRINT RECOGNITION." Doctoral thesis, Università degli Studi di Milano, 2014. http://hdl.handle.net/2434/233321.

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Biometric systems consist in the combination of devices, algorithms, and procedures used to recognize the individuals based on the characteristics, physical or behavioral, of their persons. These characteristics are called biometric traits. Nowadays, biometric technologies are becoming more and more widespread, and many people use biometric systems daily. However, in some cases the procedures used for the collection of the biometric traits need the cooperation of the user, controlled environments, illuminations perceived as unpleasant, too strong, or harmful, or the contact of the body with
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Konuk, Baris. "Palmprint Recognition Based On 2-d Gabor Filters." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608138/index.pdf.

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In this thesis work, a detailed analysis of biometric technologies has been done and a new palmprint recognition algorithm has been implemented. The proposed algorithm is based on 2-D Gabor filters. The developed algorithm is first tested on The Hong Kong Polytechnic University Palmprint Database in terms of accuracy, speed and template size. Then a scanner is integrated into the developed algorithm in order to acquire palm images<br>in this way an online palmprint recognition system has been developed. Then a small palmprint database is formed via this system in Middle East Technical Universi
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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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Mohamed, Abdul Cader Akmal Jahan. "Finger biometric system using bispectral invariants and information fusion techniques." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/134464/1/Akmal%20Jahan_Mohamed%20Abdul%20Cader_Thesis.pdf.

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Contactless hand biometric systems are better accepted than contact prints as they are hygienic and accelerate data acquisition. This research is one of the few investigating contactless biometrics of the full hand by proposing a novel algorithm based on ridge orientation information along lines connecting key points, higher order spectral features, and fusion. It was investigated with contactless finger images acquired from 81 users, and found to be robust to hand orientation and image size, and provide acceptable performance using two fingers with fusion. The algorithm has potential to use i
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Poinsot, Audrey. "Traitements pour la reconnaissance biométrique multimodale : algorithmes et architectures." Thesis, Dijon, 2011. http://www.theses.fr/2011DIJOS010.

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Combiner les sources d'information pour créer un système de reconnaissance biométrique multimodal permet d'atténuer les limitations de chaque caractéristique utilisée, et donne l'opportunité d'améliorer significativement les performances. Le travail présenté dans ce manuscrit a été réalisé dans le but de proposer un système de reconnaissance performant, qui réponde à des contraintes d'utilisation grand-public, et qui puisse être implanté sur un système matériel de faible coût. La solution choisie explore les possibilités apportées par la multimodalité, et en particulier par la fusion du visage
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Lee, Chia-Hsun, and 李佳勳. "PALMPRINT RECOGNITION BY SIMPLE LINEAR REGRESSION." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/94g8u6.

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碩士<br>大同大學<br>資訊工程學系(所)<br>95<br>This paper proposes a palmprint recognition method based on simple linear regressionto typical principal lines on a palm. By USAN line finder, the original palmprintimages are transformed into a three dimensional space, called “USAN area”, whichcan extract palmprint by threshold. Then, palmprint are classified into three typicalprincipal lines and several wrinkles.Finally, typical principal lines are fit into linefunctions respectively, which represent features of a palmprint image. Thus, we can usesix floating points to represent the global pattern of one palm
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Chang, Yi-Sheng, and 張軼勝. "A Design of Palmprint Recognition System." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/eahgs8.

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碩士<br>國立中山大學<br>電機工程學系研究所<br>102<br>“Palm-print” possesses a wide range of applications in Chinese chirology. It can construe numerology, foretell divination and determine character of a person. “Palm-print” is also one of the most important information sources for visual examination in traditional Chinese medicine. In the recent years, the advancement of information technology makes people rely heavily on the internet. However, convenience is also accompanied by unavoidable security problems. In order to alleviate this issue, user identification research becomes a global spotlight. In t
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Zheng, Yu-Xuan, and 鄭煜玄. "Palmprint Recognition Based on Minutiae Features." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/42365094469011258035.

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碩士<br>國立高雄海洋科技大學<br>電訊工程研究所<br>105<br>In recent years, biometrics recognition has been widely applied in daily life and specific occasions. Palmprint recognition is comparatively convenient and quicker than other biometric characteristics with respect to image acquisition and not restricted by age increasing. For this reason, this thesis proposed a reliable and stable algorithm with fast validation for palmprint recognition system application. In this thesis, the image preprocessing algorithm has been proposed to obtain rich palmprint characteristics of acquired images. In the aspect of featur
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YEH, TZU-HSUAN, and 葉子軒. "Palmprint Recognition Technology Base On CMFRAT." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/65832664238594403497.

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碩士<br>中華大學<br>資訊工程學系<br>104<br>This paper presents a contrasting palm print template, and combines the kernel area of palm print preprocess method to make a palm print recognition system. First, by using adaboost finger web detectors, the finger web and the kernel palm print range can be found, and then use CMFRAT to process the kernel palm print range image for the first stage. The first stage CMFRAT can find the palm print line and the energy of the line with each pixel. To eliminate the fine lines noise in palm print of the first stage CMFRAT, the CMFRAT has been used again with a more rigo
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Chang, Min-Chao, and 張閔超. "Palmprint Recognition based on GLCM and NGLDM." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/62196887108277311499.

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碩士<br>國立暨南國際大學<br>通訊工程研究所<br>97<br>With an increasing emphasis on security, personal authentication based on biometrics has been receiving extensive attention over the past decade. Among many different biometric technologies, this thesis examines palm-print technique for personal identification and develops a good performance recognition system based on human hand features. It is implemented and tested on VIP-CC Lab. hand image database. The proposed system includes four modules: image acquisition, image pre-processing, feature extraction, and recognition modules. The system captures a hand im
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Books on the topic "Palmprint Recognition"

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Genovese, Angelo, Vincenzo Piuri, and Fabio Scotti. Touchless Palmprint Recognition Systems. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10365-5.

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K, Kokula Krishna Hari, ed. Palmprint Recognition using Multimodal Biometrics and Generation of One Time Password. Association of Scientists, Developers and Faculties, 2016.

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Piuri, Vincenzo, Angelo Genovese, and Fabio Scotti. Touchless Palmprint Recognition Systems. Springer, 2014.

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Piuri, Vincenzo, Angelo Genovese, and Fabio Scotti. Touchless Palmprint Recognition Systems. Springer, 2016.

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Touchless Palmprint Recognition Systems. Springer, 2014.

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Book chapters on the topic "Palmprint Recognition"

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Zhang, David, Feng Yue, and Wangmeng Zuo. "Palmprint Recognition." In Encyclopedia of Cryptography and Security. Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-5906-5_744.

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Zhang, David, Feng Yue, Wangmeng Zuo, and Xu Liang. "Palmprint Recognition." In Encyclopedia of Cryptography, Security and Privacy. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-642-27739-9_744-2.

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Zhang, David, Feng Yue, Wangmeng Zuo, and Xu Liang. "Palmprint Recognition." In Encyclopedia of Cryptography, Security and Privacy. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-030-71522-9_744.

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Zhang, David, Dandan Fan, Xu Liang, and Bob Zhang. "Toward Next-Generation Palmprint Recognition." In Advanced Palmprint Authentication. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-7101-4_1.

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Zhang, David, Dandan Fan, Xu Liang, and Bob Zhang. "3D Gabor Templates for Touchless Palmprint Recognition." In Advanced Palmprint Authentication. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-7101-4_7.

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Zhang, David, Dandan Fan, Xu Liang, and Bob Zhang. "Complete Binary Representation for 3D Palmprint Recognition." In Advanced Palmprint Authentication. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-7101-4_13.

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Zhang, David, Dandan Fan, Xu Liang, and Bob Zhang. "Aligned Multilevel Gabor Convolution Network for Palmprint Recognition." In Advanced Palmprint Authentication. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-7101-4_8.

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Zhong, Dexing, Yuan Yang, and Xuefeng Du. "Palmprint Recognition Using Siamese Network." In Biometric Recognition. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97909-0_6.

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Zhang, David, Dandan Fan, Xu Liang, and Bob Zhang. "Multi-camera System for High-Speed Touchless Palm Recognition." In Advanced Palmprint Authentication. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-7101-4_10.

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Zhang, David, Dandan Fan, Xu Liang, and Bob Zhang. "Contactless Palmprint Recognition System Based on Dual-Camera Alignment." In Advanced Palmprint Authentication. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-7101-4_9.

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Conference papers on the topic "Palmprint Recognition"

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Li, Hengjian, Jiwen Dong, Jinping Li, and Lei Wang. "Novel palmprint representations for palmprint recognition." In Seventh International Conference on Machine Vision (ICMV 2014), edited by Antanas Verikas, Branislav Vuksanovic, Petia Radeva, and Jianhong Zhou. SPIE, 2015. http://dx.doi.org/10.1117/12.2181151.

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Laadjel, Moussa, Ahmed Bouridane, and Fatih Kurugollu. "Eigenspectra Palmprint Recognition." In 4th IEEE International Symposium on Electronic Design, Test and Applications (delta 2008). IEEE, 2008. http://dx.doi.org/10.1109/delta.2008.62.

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Methani, Chha, and Anoop M. Namboodiri. "Video Based Palmprint Recognition." In 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.334.

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Li, Wei, Lei Zhang, and David Zhang. "Three dimensional palmprint recognition." In 2009 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2009. http://dx.doi.org/10.1109/icsmc.2009.5346053.

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Xiang-Qian Wu, Kuan-Quan Wang, and Zhang. "Palmprint recognition using valley features." In Proceedings of 2005 International Conference on Machine Learning and Cybernetics. IEEE, 2005. http://dx.doi.org/10.1109/icmlc.2005.1527802.

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Moco, Nuno Freire, Instituto Superior Tecnico, Instituto de Telecomunicacoes, and Paulo Lobato Correia. "Smartphone-based palmprint recognition system." In 2014 21st International Conference on Telecommunications (ICT). IEEE, 2014. http://dx.doi.org/10.1109/ict.2014.6845158.

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Sang, Haifeng, and Fang Liu. "Defocused Palmprint Recognition Using 2DPCA." In 2009 International Conference on Artificial Intelligence and Computational Intelligence. IEEE, 2009. http://dx.doi.org/10.1109/aici.2009.106.

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Du, Xuefeng, Dexing Zhong, and Huikai Shao. "Continual Palmprint Recognition Without Forgetting." In 2019 IEEE International Conference on Image Processing (ICIP). IEEE, 2019. http://dx.doi.org/10.1109/icip.2019.8803748.

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Fang, Li, and Neera. "Mobile based palmprint recognition system." In 2015 International Conference on Control, Automation and Robotics (ICCAR). IEEE, 2015. http://dx.doi.org/10.1109/iccar.2015.7166038.

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Godbole, Akash, Steven A. Grosz, and Anil K. Jain. "Contactless Palmprint Recognition for Children." In 2023 International Conference of the Biometrics Special Interest Group (BIOSIG). IEEE, 2023. http://dx.doi.org/10.1109/biosig58226.2023.10345994.

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