Literatura académica sobre el tema "MINUTIA MATCHING"
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Artículos de revistas sobre el tema "MINUTIA MATCHING"
BHOWMICK, PARTHA, ARIJIT BISHNU, BHARGAB BIKRAM BHATTACHARYA, MALAY KUMAR KUNDU, C. A. MURTHY y TINKU ACHARYA. "DETERMINATION OF MINUTIAE SCORES FOR FINGERPRINT IMAGE APPLICATIONS". International Journal of Image and Graphics 05, n.º 03 (julio de 2005): 537–71. http://dx.doi.org/10.1142/s0219467805001896.
Texto completoLoyola-González, Octavio, Emilio Francisco Ferreira Mehnert, Aythami Morales, Julian Fierrez, Miguel Angel Medina-Pérez y Raúl Monroy. "Impact of Minutiae Errors in Latent Fingerprint Identification: Assessment and Prediction". Applied Sciences 11, n.º 9 (4 de mayo de 2021): 4187. http://dx.doi.org/10.3390/app11094187.
Texto completoBENHAMMADI, FARID y KADDA BEGHDAD BEY. "EMBEDDED FINGERPRINT MATCHING ON SMART CARD". International Journal of Pattern Recognition and Artificial Intelligence 27, n.º 02 (marzo de 2013): 1350006. http://dx.doi.org/10.1142/s0218001413500067.
Texto completoGao, Qinghai. "Toward Constructing Cancellable Templates using K-Nearest Neighbour Method". International Journal of Computer Network and Information Security 9, n.º 5 (8 de mayo de 2017): 1–10. http://dx.doi.org/10.5815/ijcnis.2017.05.01.
Texto completoZHU, EN, JIAN-PING YIN, GUO-MIN ZHANG y CHUN-FENG HU. "FINGERPRINT MINUTIAE RELATIONSHIP REPRESENTATION AND MATCHING BASED ON CURVE COORDINATE SYSTEM". International Journal of Image and Graphics 05, n.º 04 (octubre de 2005): 729–44. http://dx.doi.org/10.1142/s0219467805001987.
Texto completoSoetarmono, Anggya N. D. "IDENTIFIKASI SIDIK JARI DENGAN MENGGUNAKAN STRUKTUR MINUTIA". Teknika 1, n.º 1 (1 de julio de 2012): 36–46. http://dx.doi.org/10.34148/teknika.v1i1.5.
Texto completoCao, Kai, Xin Yang, Xinjian Chen, Xunqiang Tao, Yali Zang, Jimin Liang y Jie Tian. "Minutia handedness: A novel global feature for minutiae-based fingerprint matching". Pattern Recognition Letters 33, n.º 10 (julio de 2012): 1411–21. http://dx.doi.org/10.1016/j.patrec.2012.03.007.
Texto completoSoleimani, Hossein y Mohsen Ahmadi. "Fast and efficient minutia‐based palmprint matching". IET Biometrics 7, n.º 6 (11 de abril de 2018): 573–80. http://dx.doi.org/10.1049/iet-bmt.2017.0128.
Texto completoTico, M. y P. Kuosmanen. "Fingerprint matching using an orientation-based minutia descriptor". IEEE Transactions on Pattern Analysis and Machine Intelligence 25, n.º 8 (agosto de 2003): 1009–14. http://dx.doi.org/10.1109/tpami.2003.1217604.
Texto completoSelvarani, P. y N. Malarvizhi. "Multibiometric authentication with MATLAB simulation". International Journal of Engineering & Technology 7, n.º 1.7 (5 de febrero de 2018): 47. http://dx.doi.org/10.14419/ijet.v7i1.7.9389.
Texto completoTesis sobre el tema "MINUTIA MATCHING"
Li, Tuo. "Fingerprint Identification by Improved Method of Minutiae Matching". Miami University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=miami1484672769912832.
Texto completoNoor, Azad. "A new algorithm for minutiae extraction and matching in fingerprint". Thesis, Brunel University, 2012. http://bura.brunel.ac.uk/handle/2438/7473.
Texto completoHenriksson, Marcus. "Analys av fingeravtryck". Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1219.
Texto completoThis report describes a system for verification of fingerprints against a previous created template. It describes how and why a fingerprint image must be processed before it can be used to either identify or verify a person. The method is based on special features of a fingerprint, called minutiae points. The whole process from image to matching is described, every step in the process with image enhancement, binarization, thinning and how to find the minutiae points. Also what false minutiae points are, how they arise, why they deteriorate the result, and how to handle them, is discussed.
Finally a test of the system with a large number of fingerprints is presented, to see how good the system is according to security and reliability about not accepting prints from other fingers or reject the fingerprints, which are from the same finger as the template. Many proposals about how the performance and the security of the system can be improved are also presented.
Filla, David. "Biometrie otisku prstu". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-219256.
Texto completoBlommé, Johan. "Evaluation of biometric security systems against artificial fingers". Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1145.
Texto completoVerification of users’ identities are normally carried out via PIN-codes or ID- cards. Biometric identification, identification of unique body features, offers an alternative solution to these methods.
Fingerprint scanning is the most common biometric identification method used today. It uses a simple and quick method of identification and has therefore been favored instead of other biometric identification methods such as retina scan or signature verification.
In this report biometric security systems have been evaluated based on fingerprint scanners. The evaluation method focuses on copies of real fingers, artificial fingers, as intrusion method but it also mentions currently used algorithms for identification and strengths and weaknesses in hardware solutions used.
The artificial fingers used in the evaluation were made of gelatin, as it resembles the surface of human skin in ways of moisture, electric resistance and texture. Artificial fingers were based on ten subjects whose real fingers and artificial counterpart were tested on three different fingerprint scanners. All scanners tested accepted artificial fingers as substitutes for real fingers. Results varied between users and scanners but the artificial fingers were accepted between about one forth and half of the times.
Techniques used in image enhancement, minutiae analysis and pattern matching are analyzed. Normalization, binarization, quality markup and low pass filtering are described within image enhancement. In minutiae analysis connectivity numbers, point identification and skeletonization (thinning algorithms) are analyzed. Within pattern matching, direction field analysis and principal component analysis are described. Finally combinations of both minutiae analysis and pattern matching, hybrid models, are mentioned.
Based on experiments made and analysis of used techniques a recommendation for future use and development of fingerprint scanners is made.
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.
Texto completoKUMAR, AJAY. "FINGERPRINT RECOGNITION". Thesis, 2011. http://dspace.dtu.ac.in:8080/jspui/handle/repository/13880.
Texto completoThe popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person’s life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. Automatic minutiae detection is an extremely critical process, especially in low-quality fingerprints where noise and contrast deficiency can originate pixel configurations similar to minutiae or hide real minutiae. The technique describe here, is consists of minutiae extraction and minutiae matching. the minutia extraction algorithm proposed here, is much faster and more reliable and implemented for extracting features from an input fingerprint image. For minutia matching, an alignment-based elastic matching algorithm has been developed. The proposed algorithm results in an efficient, robust and fast representation of fingerprints which accurately retains the fidelity in minutiae (ridge endings and bifurcations).
TIEN, SHAO-HUA y 田韶華. "Fingerprint Recognition Method Based on Fusion of Spatial Statistical Features and Minutia Matching". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/x98wy4.
Texto completo國立中央大學
資訊工程學系在職專班
103
Product get smaller and technological improve every day, relatively small area of the fingerprint sensor to capture the DPI is also getting smaller and smaller, resolution or image complexity will affect the image of the fingerprint identification result, the traditional approach has been to identify a single one inadequate use of feature points presented in this recognition and non-recognition feature points plus two kinds of identification method to fusion, non-feature point identification method uses a statistical and probability neural network, coupled with training through fingerprint classification to achieve their goals in decision fusion experiments on the max and two-stage and other fusion methods, and finally decision fusion experiment error rate lower than the previous two individual identification party.
Chen, Guan-you y 陳冠佑. "Fingerprint Minutiae Matching with LBP Texture". Thesis, 2015. http://ndltd.ncl.edu.tw/handle/86076627486817221560.
Texto completo國立中央大學
資訊工程學系
103
The minutiae-based matching is the main stream method in fingerprint recognition which is an algorithm tries to find out the matched minutiae between two fingerprints. According to the amount of matched Minutiae, we can determine whether these two fingerprints are same or not. Due to the noise in the fingerprint images, image pre-processing has to be proceeded in order to reduce the noises, otherwise those extracted spurious Minutiae will influence the correctness of results. Therefore, recently, there are plenty of methods proposing the combination of multiple fingerprint features to identify two fingerprints. In this paper, we propose an improved minutiae matching method by integrating the Local Binary Pattern (LBP) feature, which compares LBP texture features in the adjacent region of Minutiae in order to select the reference points we want and guarantee the precision of identification. The experiment results show that our method can outperform the traditional Minutiae-based method. In FVC2000 and the fingerprint database we build, both Error Equal Rate (EER) of the outcomes are better than the traditional way.
Gwo-Cheng, Chao y 趙國成. "A Fingerprint Verification System based on Minutiae Matching". Thesis, 2004. http://ndltd.ncl.edu.tw/handle/69420330587510232317.
Texto completo國立臺灣科技大學
資訊工程系
93
Fingerprint based identification has been known and used for a long time. Owing to the uniqueness and immutability, fingerprints are today the most widely used biometric features. Fingerprint verification is based on the minutiae of the fingerprints. Extracting minutiae from fingerprint patterns is one of the most important steps in automatic system for fingerprint identification. This model, adopted in most automatic systems, is based on a two-class minutiae classification: endpoint and bifurcation .The accuracy of the minutiae will affect the correctness of the fingerprint matching; therefore the fingerprint enhancement will be done to reduce the false minutiae. In this thesis, an effective fingerprint verification system is implemented by passing the image pre/post-processing, feature extraction and matching processes. We describe an improved method on fingerprint enhancement and post-processing. We directly enhance the fingerprint on gray-scale image and reduce the most false minutiae in the post-processing step. For minutiae matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the corresponding point pairs between input and template minutiae. It also has the ability to adaptively compensate for the nonlinear deformations between fingerprints.
Libros sobre el tema "MINUTIA MATCHING"
Michael, McCabe R. y National Institute of Standards and Technology (U.S.), eds. Fingerprint minutiae from latent and matching tenprint images. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 2000.
Buscar texto completoFail Safe Employment Techniques (Firm), ed. Fail safe employment techniques: A guide to the world of work : matching skills to more than 20,000 jobs : an unbeatable method to scan thousands of potential careers in minutes. Bellevue, Wash: Fail Safe Employment Techniques, 1985.
Buscar texto completoNIST SPECIAL DATABASE 27 FINGERPRINT MINUTIAE FROM LATENT MATCHING TENPRINT IMAGES... NISTIR 6534... U.S. DEPARTMENT OF COMMERCE. [S.l: s.n., 2001.
Buscar texto completoRush, David N. y Peter W. Nickerson. Rejection. Editado por Jeremy R. Chapman. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0283_update_001.
Texto completoSciences, Planet of. 100 Days of Telling the Time - Practice Worksheets Workbook with Answers ,fill in the-Blank, Drawing Hands on a Clock Face : Ages 7-9: Hours, Quarter Hours, Five Minutes, Minutes, Matching Times. Independently Published, 2020.
Buscar texto completoMuders, Thomas y Christian Putensen. Pressure-controlled mechanical ventilation. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0096.
Texto completoCapítulos de libros sobre el tema "MINUTIA MATCHING"
Sarier, Neyire Deniz. "Private Minutia-Based Fingerprint Matching". En Information Security Theory and Practice, 52–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24018-3_4.
Texto completoQi, Jin, Yangsheng Wang, Zhongchao Shi, Ke Xu y Xuying Zhao. "Fingerprint Matching Integrating the Global Orientation Field with Minutia". En Biometric Authentication, 337–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_47.
Texto completoMedina-Pérez, Miguel Angel, Andrés Gutiérrez-Rodríguez y Milton García-Borroto. "Improving Fingerprint Matching Using an Orientation-Based Minutia Descriptor". En Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 121–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10268-4_14.
Texto completoCappelli, Raffaele, Matteo Ferrara y Davide Maltoni. "Minutiae-Based Fingerprint Matching". En Intelligent Systems Reference Library, 117–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28457-1_7.
Texto completoAsha, S. y C. Chellappan. "Partial Fingerprint Matching Using Minutiae Subset". En Intelligent Computing, Networking, and Informatics, 445–52. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1665-0_42.
Texto completoRatha, Nalini K., Jonathan H. Connell y Ruud M. Bolle. "An Analysis of Minutiae Matching Strength". En Lecture Notes in Computer Science, 223–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45344-x_32.
Texto completoParziale, Giuseppe y Albert Niel. "A Fingerprint Matching Using Minutiae Triangulation". En Biometric Authentication, 241–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_34.
Texto completoBenhammadi, Farid, Hamid Hentous, Kadda Bey-Beghdad y Mohamed Aissani. "Fingerprint Matching Using Minutiae Coordinate Systems". En Pattern Recognition and Image Analysis, 529–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11492542_65.
Texto completoChen, Jiali y Zhenhua Guo. "Palmprint Matching by Minutiae and Ridge Distance". En Cloud Computing and Security, 371–82. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48674-1_33.
Texto completoPatel, Ronakkumar B., Dilendra Hiran y Jayeshbhai Patel. "Biometric Fingerprint Recognition Using Minutiae Score Matching". En Lecture Notes on Data Engineering and Communications Technologies, 463–78. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4474-3_52.
Texto completoActas de conferencias sobre el tema "MINUTIA MATCHING"
Xuefeng Liang y T. Asano. "Fingerprint Matching Using Minutia Polygons". En 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.571.
Texto completoCzovny, Raphael K., Olga R. P. Bellon, Luciano Silva y Henrique S. G. Costa. "Minutia Matching using 3D Pore Clouds". En 2018 24th International Conference on Pattern Recognition (ICPR). IEEE, 2018. http://dx.doi.org/10.1109/icpr.2018.8546036.
Texto completoBaig, Wajih Ullah, Umar Munir, Adeel Ejaz y Kashif Sardar. "Minutia Texture Cylinder Codes for Fingerprint Matching". En 2019 International Conference on Frontiers of Information Technology (FIT). IEEE, 2019. http://dx.doi.org/10.1109/fit47737.2019.00024.
Texto completoLuo, Yuxuan, Jianjiang Feng y Jie Zhou. "Fingerprint matching based on global minutia cylinder code". En 2014 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2014. http://dx.doi.org/10.1109/btas.2014.6996231.
Texto completoLahby, Mohamed, Yassine Ismaili, Abdelbaki Attioui y Abderrahim Sekkaki. "Performance analysis of minutia-based fingerprint matching algorithms". En 2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA). IEEE, 2016. http://dx.doi.org/10.1109/sita.2016.7772324.
Texto completoWu, Chunsheng, Liu Zhigang y Feng Caigang. "Palmprint Minutia Point Matching Algorithm and GPU Application". En The 5th International Conference on Computer Engineering and Networks. Trieste, Italy: Sissa Medialab, 2015. http://dx.doi.org/10.22323/1.259.0030.
Texto completoWen, Wen, Zhi Qi, Zhi Li, Junhao Zhang, Yu Gong y Peng Cao. "A Robust and Efficient Minutia-Based Fingerprint Matching Algorithm". En 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR). IEEE, 2013. http://dx.doi.org/10.1109/acpr.2013.43.
Texto completoSutarno, Muhamad Visat y Achmad Imam Kistijantoro. "Minutia cylinder code-based fingerprint matching optimization using GPU". En 2017 International Conference on Data and Software Engineering (ICoDSE). IEEE, 2017. http://dx.doi.org/10.1109/icodse.2017.8285880.
Texto completoJIN, SHENGPING, MEILAN ZENG y DINGFANG CHEN. "THE FINGERPRINT IMAGE NOISE REDUCING AND MINUTIA MATCHING IN VERIFICATION". En Proceedings of the Third International Conference on WAA. World Scientific Publishing Company, 2003. http://dx.doi.org/10.1142/9789812796769_0120.
Texto completoZang, Jiong, Jie Yuan, Fei Shi y Si-dan Du. "A Fingerprint Matching Algorithm of Minutia Based on Local Characteristic". En 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.710.
Texto completoInformes sobre el tema "MINUTIA MATCHING"
Williams, Thomas. Microbial Mating-type Matching memory Game. University of Dundee, 2023. http://dx.doi.org/10.20933/100001286.
Texto completoMathew, Jijo K., Christopher M. Day, Howell Li y Darcy M. Bullock. Curating Automatic Vehicle Location Data to Compare the Performance of Outlier Filtering Methods. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317435.
Texto completoDorna, Guadalupe y Gastón Gertner. Argentina: Lessons Learned from a Remote Tutoring Pilot. Inter-American Development Bank, septiembre de 2023. http://dx.doi.org/10.18235/0005110.
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