Paper Info
Title
Iris feature extraction and matching based on multiscale and directional image representation
Abstract
This paper presents a new filterbank-based iris recognition method that effectively extracts the spatial and directional features of iris patterns on multiple scales, then performs matching. First, the proposed method localizes the iris area from an input image and establishes a region of interest (ROI) for feature extraction. Second, the iris features are extracted on multiple scales from the ROI and a feature vector generated using a band pass filter and directional filter bank (DFB), which decomposes the image into several directional subband outputs. Finally, iris pattern matching robust to various rotations of the input is performed based on finding the Hamming distance between the corresponding feature vectors. Experimental results demonstrate that the proposed method is both effective in extracting directional and multiresolutional features from iris patterns and robust to input image rotation due to head tilt.
Year
DOI
Venue
2003
10.1007/3-540-44935-3_40
Scale-Space
Keywords
Field
DocType
directional image representation,directional feature,multiple scale,new filterbank-based iris recognition,directional subband output,iris feature,iris feature extraction,directional filter bank,iris area,corresponding feature vector,iris pattern,hamming distance,band pass filter,pattern matching,region of interest,feature extraction,feature vector,iris recognition
Iris recognition,Computer vision,Feature vector,Computer science,Filter bank,Feature extraction,Hamming distance,Artificial intelligence,Haar wavelet,Region of interest,Pattern matching
Conference
Volume
ISSN
ISBN
2695
0302-9743
3-540-40368-X
Citations 
PageRank 
References 
8
0.62
7
Authors
6
Name
Order
Citations
PageRank
Chul-Hyun Park115012.36
Joon-Jae Lee210010.12
Sang-Keun Oh3494.01
Young-Chul Song4242.87
Doo-Hyun Choi56512.25
Kil-Houm Park615614.62