Paper Info
Title
Texture Modeling for Synthetic Fingerprint Generation
Abstract
The development of biometric recognition technologies often requires large sets of biometric data for training and evaluation purposes. The use of synthetically generated biometric samples has been explored as a means of avoiding the challenges of large scale data collection. Our paper builds on previous work in synthetic fingerprint generation research through the modeling and synthesis of texture characteristics for synthetic fingerprint generation. The proposed texture characterizing features can be modeled from real fingerprint images to generate synthetic fingerprint texture statistically representative of a particular real fingerprint database. The texture characterizing features include ridge intensity along the ridge center-lines with seven frequency components, ridge width, ridge cross-sectional slope, ridge noise, and valley noise. A comparison of these feature densities from real and synthetic fingerprints is shown, which demonstrates the effectiveness of this method of modeling and generating synthetic fingerprint textures.
Year
DOI
Venue
2013
10.1109/CVPRW.2013.30
Computer Vision and Pattern Recognition Workshops
Keywords
Field
DocType
texture modeling,synthetic fingerprint generation,real fingerprint image,ridge cross-sectional slope,synthetic fingerprint generation research,particular real fingerprint database,ridge noise,ridge center-lines,synthetic fingerprint texture,ridge intensity,synthetic fingerprint,image texture,image segmentation,noise,feature extraction,fingerprint identification,databases,fingerprint recognition
Data collection,Computer vision,Pattern recognition,Image texture,Computer science,Ridge,Texture modeling,Fingerprint,Artificial intelligence,Biometrics,Biometric data,Fingerprint database
Conference
Volume
Issue
ISSN
2013
1
2160-7508
Citations 
PageRank 
References 
4
0.58
12
Authors
3
Name
Order
Citations
PageRank
Peter Johnson1101.12
Fang Hua251.29
Stephanie A. C. Schuckers369566.09