Fingerprint ridge distance estimation: algorithms and the performance

Authors:
Xiaosi Zhan;Zhaocai Sun;Yilong Yin;Yayun Chu
Affiliations:
Computer Department, Fuyan Normal College, Fuyang, China;School of Computer Science & Technology, Shandong University, Jinan, China;School of Computer Science & Technology, Shandong University, Jinan, China;Computer Department, Fuyan Normal College, Fuyang, China
Venue:
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
Year:
2006

Citing 4
Cited 0

An approach to fingerprint filter design

Pattern Recognition
Fingerprint Image Enhancement: Algorithm and Performance Evaluation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Identity Authentication Using Fingerprints

AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Ridge-Line Density Estimation in Digital Images

ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1

Quantified Score

Hi-index	0.00

Visualization

Abstract

Ridge distance is one important attribute of the fingerprint image and it also is one important parameter in the fingerprint enhancement. It is important for improving the AFIS’s performance to estimate the ridge distance correctly. The paper discusses the representative fingerprint ridge distance estimation algorithms and the performance of these algorithms. The most common fingerprint ridge distance estimation algorithm is based on block-level and estimates the ridge distance by calculating the number of cycle pattern in the block fingerprint image. The traditional Fourier transform spectral analysis method has been also applied to estimate the fingerprint ridge distance. The next kind of method is based on the statistical window. Another novel fingerprint ridge distance estimation method is based on the region-level which regards the region with the consistent orientation as the statistical region. One new method obtains the fingerprint ridge distance from the continuous Fourier spectrum. After discussing the dominant algorithm thought, the paper analyzes the performance of each algorithm.