Literatura académica sobre el tema "PALM PRINT RECOGNITION"
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Artículos de revistas sobre el tema "PALM PRINT RECOGNITION"
Goh, Michael K. O., Connie Tee y Andrew B. J. Teoh. "BI-MODAL PALM PRINT AND KNUCKLE PRINT RECOGNITION SYSTEM". Journal of IT in Asia 3, n.º 1 (20 de abril de 2016): 85–106. http://dx.doi.org/10.33736/jita.37.2010.
Texto completoAlShemmary, Ebtesam. "Siamese Network-Based Palm Print Recognition". Journal of Kufa for Mathematics and Computer 10, n.º 1 (31 de marzo de 2023): 108–18. http://dx.doi.org/10.31642/jokmc/2018/100116.
Texto completoPushpa, N. B. y N. B. Prajwala. "A Scientific Analysis to Observe Uniqueness in Lip Print Pattern". International Journal of Innovative Technology and Exploring Engineering 10, n.º 4 (28 de febrero de 2021): 196–98. http://dx.doi.org/10.35940/ijitee.d8571.0210421.
Texto completoKarar, Subhajit y Ranjan Parekh. "Palm Print Recognition using Zernike Moments". International Journal of Computer Applications 55, n.º 16 (20 de octubre de 2012): 15–19. http://dx.doi.org/10.5120/8839-3069.
Texto completoSu, Ching-Liang. "Palm-print recognition by matrix discriminator". Expert Systems with Applications 36, n.º 7 (septiembre de 2009): 10259–65. http://dx.doi.org/10.1016/j.eswa.2009.01.052.
Texto completoBadrinath, G. S. y Phalguni Gupta. "Stockwell transform based palm-print recognition". Applied Soft Computing 11, n.º 7 (octubre de 2011): 4267–81. http://dx.doi.org/10.1016/j.asoc.2010.05.031.
Texto completoATTAR SHAGUSTHA BANU y N VINOD KUMAR. "IMPLEMENTATION OF ACCURATE PERSONAL IDENTIFICATION BY USING PALM PRINT IMAGE PROCESSING". international journal of engineering technology and management sciences 7, n.º 1 (28 de febrero de 2023): 120–30. http://dx.doi.org/10.46647/ijetms.2023.v07i01.020.
Texto completoMustafa, Raniah Ali, Haitham Salman Chyad y Rafid Aedan Haleot. "Palm print recognition based on harmony search algorithm". International Journal of Electrical and Computer Engineering (IJECE) 11, n.º 5 (1 de octubre de 2021): 4113. http://dx.doi.org/10.11591/ijece.v11i5.pp4113-4124.
Texto completoJaafar, Haryati, Salwani Ibrahim y Dzati Athiar Ramli. "A Robust and Fast Computation Touchless Palm Print Recognition System Using LHEAT and the IFkNCN Classifier". Computational Intelligence and Neuroscience 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/360217.
Texto completoMichael, Goh Kah Ong, Tee Connie y Andrew Teoh Beng Jin. "An innovative contactless palm print and knuckle print recognition system". Pattern Recognition Letters 31, n.º 12 (septiembre de 2010): 1708–19. http://dx.doi.org/10.1016/j.patrec.2010.05.021.
Texto completoTesis sobre el tema "PALM PRINT RECOGNITION"
GUPTA, AMIT. "IMPROVED PALM PRINT RECOGNITION". Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15794.
Texto completoLi, Tzung-Ru y 李宗儒. "Palm-Print Recognition Based on Principal Line Features using Hough Palm-Print Recognition Based on Principal Line Features using Hough Transform". Thesis, 2008. http://ndltd.ncl.edu.tw/handle/03587807640224762650.
Texto completo國立暨南國際大學
通訊工程研究所
96
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 image using digital camera, then uses some image processing algorithms to localize the region of the interest of palmprint from the hand image via image pre-processing module. The feature extraction module segments the region of interest image, and adopts its discriminating texture features calculated by Hough transform form each block. The system applies these feature vectors for matching in recognition module. Experimental results show that the system has an encouraging performance on the VIP-CC Lab. Database (Including 678 images from 113 classes) . The proposed system adopts Hough transform to extract principal line feature of palmprint. When we separate palmprint image into 8×8 blocks, adopting principal line segment length as our features in each block can attain an equal error rate (EER) of 3.55%. When we separate palmprint image into 10×10 blocks, and use binary coding to generate the feature codes that we can attain an EER of 1.9071%. This thesis analyzes the experimented results and verifies the related inferences of the proposed system for providing useful information for further research.
楊子毅. "The study of pattern extraction and recognition based on finger-vein and palm-print". Thesis, 2006. http://ndltd.ncl.edu.tw/handle/09751773561597304903.
Texto completoChiang, Yao-Shan y 江樂山. "Palm-Print and Hand-Shape Biometric Recognition System Based on Wavelet Transform and Statistical Moments". Thesis, 2005. http://ndltd.ncl.edu.tw/handle/65358393795776210022.
Texto completo國立暨南國際大學
電機工程學系
93
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 and hand-shape 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. First, the system captures a hand image using digital camera, then uses some image processing algorithms to localize the region of the interest of palm-print and hand-geometry from the hand image via image pre-processing module. The feature extraction module adopts the gradient direction (i.e., angle) of the two different wavelet transforms in the palm-print phase, and adopts the statistical moments in the hand-shape to extract the discriminating texture features. The system encodes the feature to generate its palm-print codes by binary gray coding, and uses invariant moment vector in hand-geometry phase. Finally, the system applies these feature codes and vector for matching in recognition module. Experimental results show that the system has an encouraging performance on the VIP-CC Lab. database(including 210 images from 30 classes). The proposed system adopts two different wavelet transform and statistical moments to extract palm-print and hand-shape features, then uses the gradient direction coding to generate the feature codes. We attain the recognition rates up to 95.00% and 98.33%(according to equal error rate, EER), respectively. Even under the circumstance of false acceptance rate(FAR) 0%, the system still approaches the recognition rate above 89.17%(acceptance of authentic, AA). This thesis analyzes the experimented results and verifies the related inferences of the proposed system for providing useful information for further research.
Capítulos de libros sobre el tema "PALM PRINT RECOGNITION"
Poonia, Poonam y Pawan K. Ajmera. "Robust Multi-Spectral Palm-Print Recognition". En Lecture Notes in Networks and Systems, 285–93. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0483-9_25.
Texto completoMod, Mayank, Amit Mishra, Kusha Bhatt, Sonal Shah, Shivali Shah y Urvashi Sanadhya. "An Exploration of Miscellaneous Palm Print Recognition Modalities". En Communications in Computer and Information Science, 69–76. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-3433-6_9.
Texto completoRane, Milind y Umesh Bhadade. "Dual Palm Print-Based Human Recognition Using Fusion". En Algorithms for Intelligent Systems, 101–9. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0873-5_9.
Texto completoBadrinath, G. S. y Phalguni Gupta. "A Novel Representation of Palm-Print for Recognition". En Computer Vision – ACCV 2010, 321–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19309-5_25.
Texto completoHan, Chin-Chuan. "Personal Authentication Using the Fusion of Multiple Palm-Print Features". En Computer-Aided Intelligent Recognition Techniques and Applications, 131–43. Chichester, UK: John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470094168.ch9.
Texto completoManoj, M. Sowmiya y S. Arulselvi. "Artificial Neural Network Based Biometric Palm Print Recognition System for Security Analysis". En Lecture Notes in Electrical Engineering, 808–19. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1677-9_70.
Texto completoDai, Gui-Ping. "Palm Print Feature Extraction and Recognition Based on BEMD-ICAII and LS-SVM". En Intelligent Computing Theories, 368–75. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39479-9_44.
Texto completoDastidar, Jayati Ghosh, Debangshu Chakraborty, Soumen Mukherjee y Arup Kumar Bhattacharjee. "Analysis of Human Gait for Designing a Recognition and Classification System". En Intelligent Innovations in Multimedia Data Engineering and Management, 186–200. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7107-0.ch008.
Texto completoActas de conferencias sobre el tema "PALM PRINT RECOGNITION"
Harb, Ahmad, Mahmoud Abbas, Ali Cherry, Hussein Jaber y Mohamad Ayache. "Palm print recognition". En 2015 International Conference on Advances in Biomedical Engineering (ICABME). IEEE, 2015. http://dx.doi.org/10.1109/icabme.2015.7323239.
Texto completoAgarwal, Shalini, Vivek Sharma y Pawan Kumar Verma. "Palm Print Recognition Using CEDA". En 2019 3rd International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2019. http://dx.doi.org/10.1109/iccmc.2019.8819834.
Texto completoKaushik, Shivkant y Rajendra Singh. "A new hybrid approch for palm print recognition in PCA based palm print recognition system". En 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). IEEE, 2016. http://dx.doi.org/10.1109/icrito.2016.7784958.
Texto completoRay, Kasturika B. y Rachita Misra. "Palm Print Recognition Using Hough Transforms". En 2015 International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2015. http://dx.doi.org/10.1109/cicn.2015.88.
Texto completoRajawat, A., M. Hanmandlu y S. Pani. "Fuzzy modeling based palm print recognition system". En 2009 International Conference on Emerging Trends in Electronic and Photonic Devices & Systems (ELECTRO-2009). IEEE, 2009. http://dx.doi.org/10.1109/electro.2009.5441141.
Texto completoSwarnkar, Priyanshi y P. K. Jain. "Palm print Recognition Using Neighboring Direction Indicator". En 2019 Sixteenth International Conference on Wireless and Optical Communication Networks (WOCN). IEEE, 2019. http://dx.doi.org/10.1109/wocn45266.2019.8995053.
Texto completoJavidnia, Hossein, Adrian Ungureanu y Peter Corcoran. "Palm-print recognition for authentication on smartphones". En 2015 IEEE International Symposium on Technology and Society (ISTAS). IEEE, 2015. http://dx.doi.org/10.1109/istas.2015.7439441.
Texto completoAishwarya, D., M. Gowri y R. K. Saranya. "Palm print recognition using liveness detection technique". En 2016 Second International Conference on Science Technology Engineering And Management (ICONSTEM). IEEE, 2016. http://dx.doi.org/10.1109/iconstem.2016.7560933.
Texto completoYang, Jun y Xianhong Zhao. "Palm print image processing with PCNN". En International Conference on Image Processing and Pattern Recognition in Industrial Engineering, editado por Zhengyu Du y Bin Liu. SPIE, 2010. http://dx.doi.org/10.1117/12.867026.
Texto completoCui, Yuan y Bo-nian Li. "A Palm-Print Recognition System Based on OMAP3530". En 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2010. http://dx.doi.org/10.1109/wicom.2010.5600686.
Texto completoInformes sobre el tema "PALM PRINT RECOGNITION"
Varastehpour, Soheil, Hamid Sharifzadeh, Iman Ardekani y Abdolhossein Sarrafzadeh. Human Biometric Traits: A Systematic Review Focusing on Vascular Patterns. Unitec ePress, diciembre de 2020. http://dx.doi.org/10.34074/ocds.086.
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