Academic literature on the topic 'MINUTIA MATCHING'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'MINUTIA MATCHING.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "MINUTIA MATCHING"
BHOWMICK, PARTHA, ARIJIT BISHNU, BHARGAB BIKRAM BHATTACHARYA, MALAY KUMAR KUNDU, C. A. MURTHY, and TINKU ACHARYA. "DETERMINATION OF MINUTIAE SCORES FOR FINGERPRINT IMAGE APPLICATIONS." International Journal of Image and Graphics 05, no. 03 (July 2005): 537–71. http://dx.doi.org/10.1142/s0219467805001896.
Full textLoyola-González, Octavio, Emilio Francisco Ferreira Mehnert, Aythami Morales, Julian Fierrez, Miguel Angel Medina-Pérez, and Raúl Monroy. "Impact of Minutiae Errors in Latent Fingerprint Identification: Assessment and Prediction." Applied Sciences 11, no. 9 (May 4, 2021): 4187. http://dx.doi.org/10.3390/app11094187.
Full textBENHAMMADI, FARID, and KADDA BEGHDAD BEY. "EMBEDDED FINGERPRINT MATCHING ON SMART CARD." International Journal of Pattern Recognition and Artificial Intelligence 27, no. 02 (March 2013): 1350006. http://dx.doi.org/10.1142/s0218001413500067.
Full textGao, Qinghai. "Toward Constructing Cancellable Templates using K-Nearest Neighbour Method." International Journal of Computer Network and Information Security 9, no. 5 (May 8, 2017): 1–10. http://dx.doi.org/10.5815/ijcnis.2017.05.01.
Full textZHU, EN, JIAN-PING YIN, GUO-MIN ZHANG, and CHUN-FENG HU. "FINGERPRINT MINUTIAE RELATIONSHIP REPRESENTATION AND MATCHING BASED ON CURVE COORDINATE SYSTEM." International Journal of Image and Graphics 05, no. 04 (October 2005): 729–44. http://dx.doi.org/10.1142/s0219467805001987.
Full textSoetarmono, Anggya N. D. "IDENTIFIKASI SIDIK JARI DENGAN MENGGUNAKAN STRUKTUR MINUTIA." Teknika 1, no. 1 (July 1, 2012): 36–46. http://dx.doi.org/10.34148/teknika.v1i1.5.
Full textCao, Kai, Xin Yang, Xinjian Chen, Xunqiang Tao, Yali Zang, Jimin Liang, and Jie Tian. "Minutia handedness: A novel global feature for minutiae-based fingerprint matching." Pattern Recognition Letters 33, no. 10 (July 2012): 1411–21. http://dx.doi.org/10.1016/j.patrec.2012.03.007.
Full textSoleimani, Hossein, and Mohsen Ahmadi. "Fast and efficient minutia‐based palmprint matching." IET Biometrics 7, no. 6 (April 11, 2018): 573–80. http://dx.doi.org/10.1049/iet-bmt.2017.0128.
Full textTico, M., and P. Kuosmanen. "Fingerprint matching using an orientation-based minutia descriptor." IEEE Transactions on Pattern Analysis and Machine Intelligence 25, no. 8 (August 2003): 1009–14. http://dx.doi.org/10.1109/tpami.2003.1217604.
Full textSelvarani, P., and N. Malarvizhi. "Multibiometric authentication with MATLAB simulation." International Journal of Engineering & Technology 7, no. 1.7 (February 5, 2018): 47. http://dx.doi.org/10.14419/ijet.v7i1.7.9389.
Full textDissertations / Theses on the topic "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.
Full textNoor, Azad. "A new algorithm for minutiae extraction and matching in fingerprint." Thesis, Brunel University, 2012. http://bura.brunel.ac.uk/handle/2438/7473.
Full textHenriksson, Marcus. "Analys av fingeravtryck." Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1219.
Full textThis 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.
Full textBlommé, 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.
Full textVerification 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.
Full textKUMAR, AJAY. "FINGERPRINT RECOGNITION." Thesis, 2011. http://dspace.dtu.ac.in:8080/jspui/handle/repository/13880.
Full textThe 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, and 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.
Full text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, and 陳冠佑. "Fingerprint Minutiae Matching with LBP Texture." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/86076627486817221560.
Full text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, and 趙國成. "A Fingerprint Verification System based on Minutiae Matching." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/69420330587510232317.
Full text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.
Books on the topic "MINUTIA MATCHING"
Michael, McCabe R., and 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.
Find full textFail 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.
Find full textNIST SPECIAL DATABASE 27 FINGERPRINT MINUTIAE FROM LATENT MATCHING TENPRINT IMAGES... NISTIR 6534... U.S. DEPARTMENT OF COMMERCE. [S.l: s.n., 2001.
Find full textRush, David N., and Peter W. Nickerson. Rejection. Edited by Jeremy R. Chapman. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0283_update_001.
Full textSciences, 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.
Find full textMuders, Thomas, and Christian Putensen. Pressure-controlled mechanical ventilation. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0096.
Full textBook chapters on the topic "MINUTIA MATCHING"
Sarier, Neyire Deniz. "Private Minutia-Based Fingerprint Matching." In Information Security Theory and Practice, 52–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24018-3_4.
Full textQi, Jin, Yangsheng Wang, Zhongchao Shi, Ke Xu, and Xuying Zhao. "Fingerprint Matching Integrating the Global Orientation Field with Minutia." In Biometric Authentication, 337–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_47.
Full textMedina-Pérez, Miguel Angel, Andrés Gutiérrez-Rodríguez, and Milton García-Borroto. "Improving Fingerprint Matching Using an Orientation-Based Minutia Descriptor." In 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.
Full textCappelli, Raffaele, Matteo Ferrara, and Davide Maltoni. "Minutiae-Based Fingerprint Matching." In Intelligent Systems Reference Library, 117–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28457-1_7.
Full textAsha, S., and C. Chellappan. "Partial Fingerprint Matching Using Minutiae Subset." In Intelligent Computing, Networking, and Informatics, 445–52. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1665-0_42.
Full textRatha, Nalini K., Jonathan H. Connell, and Ruud M. Bolle. "An Analysis of Minutiae Matching Strength." In Lecture Notes in Computer Science, 223–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45344-x_32.
Full textParziale, Giuseppe, and Albert Niel. "A Fingerprint Matching Using Minutiae Triangulation." In Biometric Authentication, 241–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25948-0_34.
Full textBenhammadi, Farid, Hamid Hentous, Kadda Bey-Beghdad, and Mohamed Aissani. "Fingerprint Matching Using Minutiae Coordinate Systems." In Pattern Recognition and Image Analysis, 529–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11492542_65.
Full textChen, Jiali, and Zhenhua Guo. "Palmprint Matching by Minutiae and Ridge Distance." In Cloud Computing and Security, 371–82. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48674-1_33.
Full textPatel, Ronakkumar B., Dilendra Hiran, and Jayeshbhai Patel. "Biometric Fingerprint Recognition Using Minutiae Score Matching." In 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.
Full textConference papers on the topic "MINUTIA MATCHING"
Xuefeng Liang and T. Asano. "Fingerprint Matching Using Minutia Polygons." In 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.571.
Full textCzovny, Raphael K., Olga R. P. Bellon, Luciano Silva, and Henrique S. G. Costa. "Minutia Matching using 3D Pore Clouds." In 2018 24th International Conference on Pattern Recognition (ICPR). IEEE, 2018. http://dx.doi.org/10.1109/icpr.2018.8546036.
Full textBaig, Wajih Ullah, Umar Munir, Adeel Ejaz, and Kashif Sardar. "Minutia Texture Cylinder Codes for Fingerprint Matching." In 2019 International Conference on Frontiers of Information Technology (FIT). IEEE, 2019. http://dx.doi.org/10.1109/fit47737.2019.00024.
Full textLuo, Yuxuan, Jianjiang Feng, and Jie Zhou. "Fingerprint matching based on global minutia cylinder code." In 2014 IEEE International Joint Conference on Biometrics (IJCB). IEEE, 2014. http://dx.doi.org/10.1109/btas.2014.6996231.
Full textLahby, Mohamed, Yassine Ismaili, Abdelbaki Attioui, and Abderrahim Sekkaki. "Performance analysis of minutia-based fingerprint matching algorithms." In 2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA). IEEE, 2016. http://dx.doi.org/10.1109/sita.2016.7772324.
Full textWu, Chunsheng, Liu Zhigang, and Feng Caigang. "Palmprint Minutia Point Matching Algorithm and GPU Application." In The 5th International Conference on Computer Engineering and Networks. Trieste, Italy: Sissa Medialab, 2015. http://dx.doi.org/10.22323/1.259.0030.
Full textWen, Wen, Zhi Qi, Zhi Li, Junhao Zhang, Yu Gong, and Peng Cao. "A Robust and Efficient Minutia-Based Fingerprint Matching Algorithm." In 2013 2nd IAPR Asian Conference on Pattern Recognition (ACPR). IEEE, 2013. http://dx.doi.org/10.1109/acpr.2013.43.
Full textSutarno, Muhamad Visat, and Achmad Imam Kistijantoro. "Minutia cylinder code-based fingerprint matching optimization using GPU." In 2017 International Conference on Data and Software Engineering (ICoDSE). IEEE, 2017. http://dx.doi.org/10.1109/icodse.2017.8285880.
Full textJIN, SHENGPING, MEILAN ZENG, and DINGFANG CHEN. "THE FINGERPRINT IMAGE NOISE REDUCING AND MINUTIA MATCHING IN VERIFICATION." In Proceedings of the Third International Conference on WAA. World Scientific Publishing Company, 2003. http://dx.doi.org/10.1142/9789812796769_0120.
Full textZang, Jiong, Jie Yuan, Fei Shi, and Si-dan Du. "A Fingerprint Matching Algorithm of Minutia Based on Local Characteristic." In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.710.
Full textReports on the topic "MINUTIA MATCHING"
Williams, Thomas. Microbial Mating-type Matching memory Game. University of Dundee, 2023. http://dx.doi.org/10.20933/100001286.
Full textMathew, Jijo K., Christopher M. Day, Howell Li, and 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.
Full textDorna, Guadalupe, and Gastón Gertner. Argentina: Lessons Learned from a Remote Tutoring Pilot. Inter-American Development Bank, September 2023. http://dx.doi.org/10.18235/0005110.
Full text