Ear Recognition Based on Gabor Features and KFDA
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-05
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
We propose an ear recognition system based on 2D ear images which includes three stages: ear enrollment, feature extraction, and ear recognition.
Ear enrollment includes ear detection and ear normalization.
The ear detection approach based on improved Adaboost algorithm detects the ear part under complex background using two steps: offline cascaded classifier training and online ear detection.
Then Active Shape Model is applied to segment the ear part and normalize all the ear images to the same size.
For its eminent characteristics in spatial local feature extraction and orientation selection, Gabor filter based ear feature extraction is presented in this paper.
Kernel Fisher Discriminant Analysis (KFDA) is then applied for dimension reduction of the high-dimensional Gabor features.
Finally distance based classifier is applied for ear recognition.
Experimental results of ear recognition on two datasets (USTB and UND datasets) and the performance of the ear authentication system show the feasibility and effectiveness of the proposed approach.
American Psychological Association (APA)
Yuan, L.& Mu, Zhichun. 2014. Ear Recognition Based on Gabor Features and KFDA. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1050670
Modern Language Association (MLA)
Yuan, L.& Mu, Zhichun. Ear Recognition Based on Gabor Features and KFDA. The Scientific World Journal No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1050670
American Medical Association (AMA)
Yuan, L.& Mu, Zhichun. Ear Recognition Based on Gabor Features and KFDA. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1050670
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050670