Direct Gray-Scale Minutiae Detection In Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Core-Based Structure Matching Algorithm of Fingerprint Verification
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
Combination of Gabor wavelets and circular Gabor filter for finger-vein extraction
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
A novel finger-vein recognition method with feature combination
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A finger-vein verification system using mean curvature
Pattern Recognition Letters
Personal identification based on finger-vein features
Computers in Human Behavior
Finger-Vein recognition based on a bank of gabor filters
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
Feature extraction from vein images using spatial information and chain codes
Information Security Tech. Report
Finger-vein ROI localization and vein ridge enhancement
Pattern Recognition Letters
Vein pattern extraction based on vectorgrams of maximal intra-neighbor difference
Pattern Recognition Letters
Biometric identification system's performance enhancement by improving registration progress
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
Deblurring vein images and removing skin wrinkle patterns by using tri-band illumination
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
Information Sciences: an International Journal
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A biometrics system for identifying individuals using the pattern of veins in a finger was previously proposed. The system has the advantage of being resistant to forgery because the pattern is inside a finger. Infrared light is used to capture an image of a finger that shows the vein patterns, which have various widths and brightnesses that change temporally as a result of fluctuations in the amount of blood in the vein, depending on temperature, physical conditions, etc. To robustly extract the precise details of the depicted veins, we developed a method of calculating local maximum curvatures in cross-sectional profiles of a vein image. This method can extract the centerlines of the veins consistently without being affected by the fluctuations in vein width and brightness, so its pattern matching is highly accurate. Experimental results show that our method extracted patterns robustly when vein width and brightness fluctuated, and that the equal error rate for personal identification was 0.0009%, which is much better than that of conventional methods.