Fingerprint image enhancement using CNN Gabor-Type filters

Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications

Volumn 2002-January, Issue , 2002, Pages 377-382

  Saatci, E ^a   Tavsanoglu, V ^a  

^a LONDON SOUTH BANK UNIVERSITY   (United Kingdom)

Author keywords

Bridges; Cellular neural networks; Fingerprint recognition; Gabor filters; Image matching; Image recognition; Image segmentation; Ink; Matched filters; Pattern recognition

Indexed keywords

BIOMETRICS; BRIDGES; CELLULAR NEURAL NETWORKS; GABOR FILTERS; IMAGE ENHANCEMENT; IMAGE MATCHING; IMAGE RECOGNITION; IMAGE SEGMENTATION; INK; MATCHED FILTERS; PALMPRINT RECOGNITION;

DIRECTIONAL FILTERS; FILTER PARAMETER; FINGERPRINT IMAGE ENHANCEMENT; FINGERPRINT IMAGES; FINGERPRINT PATTERN; FINGERPRINT RECOGNITION; FINGERPRINT RIDGES; MATCHING ERROR;

PATTERN RECOGNITION;

EID: 1242304220     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CNNA.2002.1035073     Document Type: Conference Paper

References (10)

1. H.C. Lee and R.E. Gaensslen, Advances in Fingerprint Technology. New York: Elsevier (1991).
2. L. Hong, Y. Wan and A.K. Jain, Fingerprint Image Enhancement: Algorithm and Performance Evaluation. IEEE Transaction on Pattern Analysis And Machine Intelligence, Vol.20, No.8, 777-789 (1998).
3. L.O. Chua and L. Yang, Cellular Neural Networks: Theory. IEEE Trans. Circuits and Systems, Vol.35, 1257-1272 (1988).
4. L.O. Chua and L. Yang, Cellular Neural Networks: Applications. IEEE Trans. Circuits and Systems, Vol.35, 1273-1289 (1988).
5. B.E. Shi, Gabor-Type Filtering in Space and Time with Cellular Neural Networs. IEEE Trans. on CAS-I, Vol.45, No.2, 121-132 (1998).
6. T. Kamei and M. Mizoguchi, Image Filter Design For Fingerprint Enhancement. Proceedings of ISCV'95, 109-114 (1995).
7. M. Csapodi and T. Roska, Adaptive Histogram Equalization with Cellular Neural Networks. Proceedings of CNNA'96, 81-86 (1996).
8. J.G. Daugman, Uncertainty Relation for Resolution in Space, Spatial-Frequency, and Orientation Optimized by Two-Dimensional Visual Cortical Filters. J. Optical Soc. Am., Vol.2, 1160-1169 (1985).
9. C. Rekeczky, Dynamic Spatio-Temporal Nonlinear Filtering And Detection On CNN Architecture - Theory, Modeling And Applications. Ph.D. thesis, Analogical and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences, Budapest, Hungary (1999).
10. Analogic Computers Ltd., CNN Software Library (Templates And Algorithms) Version 1.1. Analogical and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences, Budapest, Hungary (2000).