Face–iris multi‐modal biometric system using multi‐resolution Log‐Gabor filter with spectral regression kernel discriminant analysis

2018 ◽  
Vol 7 (5) ◽  
pp. 482-489 ◽  
Author(s):  
Basma Ammour ◽  
Toufik Bouden ◽  
Larbi Boubchir
Keyword(s):  
Discriminant Analysis ◽  
Gabor Filter ◽  
Biometric System ◽  
Kernel Discriminant Analysis ◽  
Spectral Regression ◽  
Log Gabor

A Robust and Scalable Visual Category and Action Recognition System Using Kernel Discriminant Analysis With Spectral Regression

2013 ◽  
Vol 15 (7) ◽  
pp. 1653-1664 ◽  
Author(s):  
Muhammad Atif Tahir ◽  
Fei Yan ◽  
Peter Koniusz ◽  
Muhammad Awais ◽  
Mark Barnard ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Action Recognition ◽  
Recognition System ◽  
Kernel Discriminant Analysis ◽  
Spectral Regression

Human Ear Recognition Based on Phase Congruency and Kernel Discriminant Analysis

2012 ◽  
Vol 241-244 ◽  
pp. 1614-1617
Author(s):  
Song Ze Lei ◽  
Qiang Zhu
Keyword(s):  
Discriminant Analysis ◽  
Gabor Filter ◽  
Recognition Rate ◽  
High Dimensional ◽  
Dimensional Vector ◽  
Phase Congruency ◽  
Kernel Discriminant Analysis ◽  
Ear Recognition ◽  
Novel Method ◽  
Human Ear

To solve the multi-pose ear recognition problem under the different illumination condition, a novel method which combines phase congruency with kernel discriminant analysis (KDA) is proposed. The phase congruency of ear image is first calculated using Log-Gabor filter with 5 scales and 8 orientations, and then the phase congruency of different orientation is constructed as high dimensional vector including ample information. The high dimensional vector is mapped to kernel space to acquire discriminant feature. Experimental results show that the proposed method obtains higher recognition rate compared with the other related methods. The method of the phase congruency can eliminate the influence of illumination and phase congruency with KDA is effective to multi-pose ear recognition.

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