Nonuniform Directional Filter Banks With Arbitrary Frequency Partitioning

2011 ◽  
Vol 20 (1) ◽  
pp. 283-288 ◽  
Author(s):  
Lili Liang ◽  
Guangming Shi ◽  
Xuemei Xie
Keyword(s):  
Filter Banks ◽  
Directional Filter ◽  
Directional Filter Banks ◽  
Arbitrary Frequency

TEXTURE-BASED FINGERPRINT RECOGNITION COMBINING DIRECTIONAL FILTER BANKS AND WAVELET

2012 ◽  
Vol 26 (04) ◽  
pp. 1256012 ◽  
Author(s):  
CHAORONG LI ◽  
BO FU ◽  
JIANPING LI ◽  
XINGCHUN YANG
Keyword(s):  
Energy Method ◽  
Filter Banks ◽  
Feature Matching ◽  
Region Of Interest ◽  
Fingerprint Recognition ◽  
Edge Information ◽  
Wavelet Method ◽  
Directional Filter ◽  
Open Issue ◽  
Directional Filter Banks

To design an effective and robust fingerprint recognition method is still an open issue. Some texture-based methods such as directional energy method and wavelet method are available nowadays. However, directional energy method is insufficient to capture the detail information of fingerprint and it is also improper to directly use wavelet method to extract the feature since the complex and rich edge information of fingerprint. In this work we propose a texture-based method called DFB-Wavelet for fingerprint recognition via combining directional filter banks (DFB) and wavelet. The region of interest (ROI) composed of nonoverlapping square blocks, is decomposed into eight directions by employing DFB. Wavelet signatures are calculated as the features of a fingerprint image from each directional subband of DFB. The feature matching is performed on the global normalized Euclidean distance between the input fingerprint features and the templates features. Experimental results show that DFB-Wavelet method has the higher accuracy compared to the traditional texture-based methods.

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