Title :
Fingerprint image enhancement using CNN Gabor-Type filters
Author :
Saatci, Ertugrul ; Tavsanoglu, Vedat
Author_Institution :
South Bank Univ., London, UK
Abstract :
Fingerprint images are usually worsened by various kinds of noise causing cracks, scratches and bridges in the ridges as well as ink blurs. These cause matching errors in fingerprint recognition. For effective recognition the correct ridge pattern is essential, requiring the enhancement of fingerprint images. A fingerprint pattern consists of ridges. Segment by segment analysis of the pattern yields various ridge directions and frequencies. By selecting a directional filter with correct filter parameters to match ridge features at each point, we can effectively enhance fingerprint ridges. This paper proposes fingerprint image enhancement based on CNN Gabor-type filters.
Keywords :
cellular neural nets; digital filters; fingerprint identification; image denoising; image enhancement; image segmentation; CNN Gabor-type filters; bridges; cracks; directional filter; fingerprint image enhancement; noise; ridge directions; ridge frequencies; ridge pattern; scratches; segment by segment analysis; Bridges; Cellular neural networks; Fingerprint recognition; Gabor filters; Image matching; Image recognition; Image segmentation; Ink; Matched filters; Pattern recognition;
Conference_Titel :
Cellular Neural Networks and Their Applications, 2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on
Print_ISBN :
981-238-121-X
DOI :
10.1109/CNNA.2002.1035073
