Fingerprint enhancement with dyadic scale-space

Authors:
Jiangang Cheng;Jie Tian
Affiliations:
Biometrics Research Group, Lab. of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, PR China;Biometrics Research Group, Lab. of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, PR China
Venue:
Pattern Recognition Letters
Year:
2004

Citing 14
Cited 12

An approach to fingerprint filter design

Pattern Recognition
A Real-Time Matching System for Large Fingerprint Databases

IEEE Transactions on Pattern Analysis and Machine Intelligence
On-Line Fingerprint Verification

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Image Enhancement: Algorithm and Performance Evaluation

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Fingerprint Verification System Based on Triangular Matching and Dynamic Time Warping

IEEE Transactions on Pattern Analysis and Machine Intelligence
FVC2000: Fingerprint Verification Competition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Direct Gray-Scale Minutiae Detection In Fingerprints

IEEE Transactions on Pattern Analysis and Machine Intelligence
Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Enhancement with Dyadic Scale-Space

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
FVC2002: Second Fingerprint Verification Competition

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Neural Network Based Minutiae Filtering in Fingerprints

ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Dyadic Scale Space

ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Orientation diffusions

IEEE Transactions on Image Processing
Fingerprint enhancement by shape adaptation of scale-space operators with automatic scale selection

IEEE Transactions on Image Processing

Fingerprint Matching Based on Global Comprehensive Similarity

IEEE Transactions on Pattern Analysis and Machine Intelligence
Preprocessing and postprocessing for skeleton-based fingerprint minutiae extraction

Pattern Recognition
Fingerprint verification using statistical descriptors

Digital Signal Processing
Fingerprint image processing and minutiae extraction for fuzzy vault

Proceedings of the 7th International Conference on Advances in Mobile Computing and Multimedia
Fingerprint image processing and fuzzy vault implementation

Journal of Mobile Multimedia
ATPDI: a computational definition of fingerprint singular points

International Journal of Information Technology and Management
FPGA-based Personal Authentication Using Fingerprints

Journal of Signal Processing Systems
Biometrics-based consumer applications driven by reconfigurable hardware architectures

Future Generation Computer Systems
Adaptive boosted spectral filtering for progressive fingerprint enhancement

Pattern Recognition
Unsharp masking using quadratic filter for the enhancement of fingerprints in noisy background

Pattern Recognition
Real-time embedded systems powered by FPGA dynamic partial self-reconfiguration: a case study oriented to biometric recognition applications

Journal of Real-Time Image Processing
A hardware solution for real-time intelligent fingerprint acquisition

Journal of Real-Time Image Processing

Quantified Score

Hi-index	0.10

Visualization

Abstract

Fingerprint enhancement is a critical step in automatic fingerprint verification system. Most of the existing enhancement uses a set of contextual filters to enhance fingerprint. The main drawback of these methods is these contextual filters based on the local information of the fingerprint, such as ridge width, orientation, curvature etc. This information is unreliable in the areas corrupted by the noise. This paper introduces the scale space theory in the computer vision to enhance the fingerprint. In the enhancement process, decompose fingerprint into a series of images and organize the images by courser to finer scheme. Thus a globe and integrate interpretation is available and it enables us to get rid of the influence of noise to the largest extent. Experiments show our algorithm is fast and improve the performance of fingerprint verification system.