Fingerprint image enhancement using CNN Gabor-Type filters

Author

Saatci, Ertugrul ; Tavsanoglu, Vedat

Author_Institution

South Bank Univ., London, UK

fYear

2002

fDate

22-24 Jul 2002

Firstpage

377

Lastpage

382

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/CNNA.2002.1035073

Filename

1035073