DocumentCode :
3278241
Title :
Combination recognition of face and ear based on two-dimensional fisher linear discriminant
Author :
Yahong Li ; Weiqi Yuan ; Haifeng Sang ; Xin Li
Author_Institution :
Comput. Vision Inst., Shenyang Univ. of Technol., Shenyang, China
fYear :
2013
fDate :
23-25 May 2013
Firstpage :
922
Lastpage :
925
Abstract :
Due to the impact of the factors such as age, cosmetics, beard and facial expressions, the performance of face recognition drops, while ear has rich and stable physiological features. A biometrics method combining face and ear is presented. Two-Dimensional Fisher Linear Discriminant (2DFLD) is applied respectively to recognition combining of facial and otic images and recognition combining of facial and otic features. On USTB ear database and ORL face database, the experimental results have shown that the recognition rate of combining facial and otic images reaches 97.5%, and is increased respectively 12.5% and 5% higher than that of face or ear; the recognition rate of combining facial and otic features is 95%, and is increased 10% and 2.5% higher than that of face or ear. The recognition of combination based on the 2DFLD method has a good recognition performance compared with PCA or 2DPCA. This indicates that the combined recognition of multi-biological features is an effective method of biometrics.
Keywords :
ear; face recognition; feature extraction; physiology; visual databases; 2DFLD method; ORL face database; USTB ear database; ear recognition; face recognition; multibiological features; otic features; otic images; physiological features; two-dimensional Fisher linear discriminant; Ear; Face; Face recognition; Feature extraction; Image recognition; Principal component analysis; Vectors; Two-Dimensional FLD; ear recognition; face recognition; multi-biological features recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2013 4th IEEE International Conference on
Conference_Location :
Beijing
ISSN :
2327-0586
Print_ISBN :
978-1-4673-4997-0
Type :
conf
DOI :
10.1109/ICSESS.2013.6615456
Filename :
6615456
Link To Document :
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