A line feature approach to finger knuckle image recognition

References

• Jain, A.K. and Kumar, A., 2010. Biometrics of next generation: An overview. Second Generation Biometrics, 12(1), pp.2-3.
   Google Scholar
• Wang, Y., Hu, J. and Phillips, D., 2007. A fingerprint orientation model based on 2D Fourier expansion (FOMFE) and its application to singular-point detection and fingerprint indexing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(4), pp.573-585. doi: 10.1109/TPAMI.2007.1003
   PubMed Web of Science ®Google Scholar
• Wang, Y. and Hu, J., 2010. Global ridge orientation modeling for partial fingerprint identification. IEEE transactions on pattern analysis and machine intelligence, 33(1), pp.72-87. doi: 10.1109/TPAMI.2010.73
   Web of Science ®Google Scholar
• Xie, S.J., Yoon, S., Yang, J., Lu, Y., Park, D.S. and Zhou, B., 2014. Feature component-based extreme learning machines for finger vein recognition. Cognitive Computation, 6(3), pp.446-461. doi: 10.1007/s12559-014-9254-3
   Web of Science ®Google Scholar
• Kumar, A. and Prathyusha, K.V., 2009. Personal authentication using hand vein triangulation and knuckle shape. IEEE Transactions on Image processing, 18(9), pp.2127-2136. doi: 10.1109/TIP.2009.2023153
   PubMed Web of Science ®Google Scholar
• Ross, A., Jain, A. and Pankati, S., 1999, March. A prototype hand geometry-based verification system. In Proceedings of 2nd conference on audio and video based biometric person authentication (pp. 166-171).
   Google Scholar
• Fabregas, J. and Faundez-Zanuy, M., 2009. Biometric recognition performing in a bioinspired system. Cognitive Computation, 1(3), pp.257-267. doi: 10.1007/s12559-009-9018-7
   Web of Science ®Google Scholar
• Hu, H. and Gu, J., 2016. Multi-manifolds discriminative canonical correlation analysis for image set-based face recognition. Cognitive Computation, 8(5), pp.900-909. doi: 10.1007/s12559-016-9403-y
   Web of Science ®Google Scholar
• Mi, J.X., Li, C., Li, C., Liu, T. and Liu, Y., 2016. A human visual experience-inspired similarity metric for face recognition under occlusion. Cognitive Computation, 8(5), pp.818-827. doi: 10.1007/s12559-016-9420-x
   Web of Science ®Google Scholar
• Sanderson, S. and Erbetta, J.H., 2000. Authentication for secure environments based on iris scanning technology.
   Google Scholar
• Xu, X., Jin, Q., Zhou, L., Qin, J., Wong, T.T. and Han, G., 2015. Illumination-invariant and deformation-tolerant inner knuckle print recognition using portable devices. Sensors, 15(2), pp.4326-4352. doi: 10.3390/s150204326
   PubMed Web of Science ®Google Scholar
• Kumar, R., 2018. A Robust Biometrics System Using Finger Knuckle Print. In Handbook of Research on Network Forensics and Analysis Techniques (pp. 416-446). IGI Global.
   Google Scholar
• Zhang, D., Kong, W.K., You, J. and Wong, M., 2003. Online palmprint identification. IEEE Transactions on pattern analysis and machine intelligence, 25(9), pp.1041-1050. doi: 10.1109/TPAMI.2003.1227981
   Web of Science ®Google Scholar
• Darini, M. & Doumari, H. A. 2015. Personal Authentication Using Palm-Print Features–A SURVEY. International Journal of Innovative Research in Science, Engineering and Technology, 4(9), pp. 21-25.
   Google Scholar
• Jain, A.K., Ross, A. and Prabhakar, S., 2004. An introduction to biometric recognition. IEEE Transactions on circuits and systems for video technology, 14(1), pp.4-20. doi: 10.1109/TCSVT.2003.818349
   Web of Science ®Google Scholar
• Zhang, L., Zhang, L., Zhang, D. and Zhu, H., 2010. Online finger-knuckle-print verification for personal authentication. Pattern recognition, 43(7), pp.2560-2571. doi: 10.1016/j.patcog.2010.01.020
   Web of Science ®Google Scholar
• Chikkerur, S., Cartwright, A.N. and Govindaraju, V., 2006, January. K-plet and coupled BFS: a graph based fingerprint representation and matching algorithm. In International Conference on Biometrics (pp. 309-315). Springer, Berlin, Heidelberg.
   Google Scholar
• Shi, Z. and Govindaraju, V., 2009, June. Robust fingerprint matching using spiral partitioning scheme. In International Conference on Biometrics (pp. 647-655). Springer, Berlin, Heidelberg.
   Google Scholar
• Abraham, J., Kwan, P. and Gao, J., 2011. Fingerprint matching using a hybrid shape and orientation descriptor. State of the art in Biometrics, pp.25-56.
   Google Scholar
• Cappelli, R., Ferrara, M. and Maltoni, D., 2010. Minutia cylinder-code: A new representation and matching technique for fingerprint recognition. IEEE transactions on pattern analysis and machine intelligence, 32(12), pp.2128-2141. doi: 10.1109/TPAMI.2010.52
   PubMed Web of Science ®Google Scholar
• Kumar, A. and Zhou, Y., 2009, September. Human identification using knucklecodes. In 2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems (pp. 1-6). IEEE.
   Google Scholar
• El-Tarhouni, W., Shaikh, M.K., Boubchir, L. and Bouridane, A., 2014, December. Multi-scale shift local binary pattern based-descriptor for finger-knuckle-print recognition. In 2014 26th International Conference on Microelectronics (ICM) (pp. 184-187). IEEE.
   Google Scholar
• Nigam, A., Tiwari, K. and Gupta, P., 2016. Multiple texture information fusion for finger-knuckle-print authentication system. Neurocomputing, 188, pp.190-205.
   Web of Science ®Google Scholar
• Kim, J., Oh, K., Oh, B.S., Lin, Z. and Toh, K.A., 2019. A line feature extraction method for finger-knuckle-print verification. Cognitive Computation, 11(1), pp.50-70. doi: 10.1007/s12559-018-9593-6
   Web of Science ®Google Scholar
• Eckhardt, U., 1988. A note on Rutovitz’method for parallel thinning. Pattern recognition letters, 8(1), pp.35-38. doi: 10.1016/0167-8655(88)90021-9
   Web of Science ®Google Scholar