Abstract
This paper deals with the quality of the image itself as well as the algorithm used for evaluating the quality of the fingerprints to construct an effective algorithm for evaluating the quality of the fingerprints. The quality of the fingerprint is acquired by taking the regional quality of each fingerprint image. The regional quality is acquired by measuring the quality of the fingerprint in blocks in the enrollment stage. The amount of fingerprint varies according to the size of each block which makes the result unsteady. We concentrated on finding the right size for the block used to acquire the fingerprint image as a graphical element. Also, the quality distribution included in the fingerprint image was acquired when the optimal block size was adopted. The threshold value of this distribution rate is expected to be used to acquire a high classification.
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References
Jain, L.C., Halici, U., Hayashi, I., Lee, S.B., Tsutsui, S.: Intelligent Biometric Techiques in Fingerprint and Face Recognition, pp. 3–21. CRC Press LLC, Boca Raton (1999)
Yao, M.Y., Pankanti, S., Haas, N., Ratha, N.K., Bolle, R.M.: Quantifying Quality: A Case Study in Fingerprints (2002), http://www.research.ibm.com/ecvg/pubs/sharat-qqual.html
Hong, L., Jain, A.K., Pankanti, S., Bolle, R.M.: Fingerprint Enhancement. In: Proc. 1st IEEE Workshop on the Application of Computer Vision, Sarasota, FL, pp. 202–207 (1996)
Shen, L.L., Kot, A., Koo, W.M.: Quality Measures of Fingerprint Images. In: Proceedings of the Third International Conference on Audio and Video Based Biometric Person Authentication 2001, Halmstad, Sweden, pp. 266–271 (2001)
Ratha, N.K., Bolle, R.M.: Fingerprint Image Quality Estimation, IBM Computer Science Research Report RC 21622 (1999), http://www.research.ibm.com/ecvg/pubs/ratha-qual.html
Jang, W., et al.: Quality Check for fingerprint Recognition. In: CVPR Spring Workshop, KISS, pp. 69–72 (2001)
Coetzee, L., Botha, E.C.: Fingerprint Recognition In Low Quality Images. Pattern Recognition 26(10), 1441–1460 (1993)
Jain And, A.L., Pankanti, S.: Automated Fingerprint Identification and Imaging Systems. In: Lee, H.C., Gaensslen, R.E. (eds.) Advances in Fingerprint Technology, 2nd edn. CRC Press, Boca Raton (2001)
Zhang, Q., Huang, K., Yan, H.: Fingerprint Classification Based on Extraction and Analysis of Singularities and Pseudo-ridges (2001), http://www.jrpit.flinders.edu.au/confpapers/CRPITV11Zhang1.pdf
Kim, H., Ahn, D.S.: Statistical Fingerprint Recognition using Block-FFT. In: Proceedings of First Asian Conference on Control, pp. 953–956 (1994)
Hong, L., Wan, Y., Jain, A.: Fingerprint Image Enhancement: Algorithm and Performance Evaluation. IEEE Trans. on Pattern Analysis and Machine Intelligence 20(8), 777–789 (1998)
Hamamoto, Y., Uchimura, S., Watanabe, M.: A Gabor filter-based method for recognizing handwritten numerals. Pattern Recognition 21(4), 395–400 (1998)
Fingerprint Quality, http://www.hbs-jena.com/Dummy/QualityCheck/qualitycheck.html
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© 2004 Springer-Verlag Berlin Heidelberg
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Park, J., Kwon, YB. (2004). Image Quality Measure Using Sliced Block Distance as a Graphical Element. In: Lladós, J., Kwon, YB. (eds) Graphics Recognition. Recent Advances and Perspectives. GREC 2003. Lecture Notes in Computer Science, vol 3088. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25977-0_20
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DOI: https://doi.org/10.1007/978-3-540-25977-0_20
Publisher Name: Springer, Berlin, Heidelberg
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