Color face recognition using quaternion PCA
Color face recognition using quaternion PCA
Recently, biometric systems have attracted the attention of both academic and industrial communities. Advances in hardware and software technologies have paved the way to such growing interest. Nowadays, efficient and cost-effective biometric solutions are continuously emerging. Fingerprint-based biometric systems have emerged as pioneering commercial applications of biometric systems. Face and iris traits have proven to be reliable candidates. Until recently, face recognition research literally followed the research undertaken in the field of fingerprint recognition which is inherently gray-scale. In this paper, efforts are restricted to the investigation of face representations in the color domain. The concept of principal component analysis (PCA) is carried over into the hypercomplex domain (i.e., quaternionic) to define quaternionic PCA (Q-PCA) where color faces are compactly represented. Unlike the existing approaches for handling the color information, the proposed algorithm implicitly accounts for the correlation that exists between the face color components (i.e., red, green and blue, respectively).
Jaha, Emad Sami
cc715fee-cbbf-4c20-a48a-a22a02d60387
Lahouari, Ghouti
5c92ee4c-3481-41e4-9e8b-e450494df96c
November 2011
Jaha, Emad Sami
cc715fee-cbbf-4c20-a48a-a22a02d60387
Lahouari, Ghouti
5c92ee4c-3481-41e4-9e8b-e450494df96c
Jaha, Emad Sami and Lahouari, Ghouti
(2011)
Color face recognition using quaternion PCA.
4th International Conference on Imaging for Crime Detection and Prevention 2011 (ICDP 2011), Kingston, United Kingdom.
03 - 04 Nov 2011.
6 pp
.
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Conference or Workshop Item
(Paper)
Abstract
Recently, biometric systems have attracted the attention of both academic and industrial communities. Advances in hardware and software technologies have paved the way to such growing interest. Nowadays, efficient and cost-effective biometric solutions are continuously emerging. Fingerprint-based biometric systems have emerged as pioneering commercial applications of biometric systems. Face and iris traits have proven to be reliable candidates. Until recently, face recognition research literally followed the research undertaken in the field of fingerprint recognition which is inherently gray-scale. In this paper, efforts are restricted to the investigation of face representations in the color domain. The concept of principal component analysis (PCA) is carried over into the hypercomplex domain (i.e., quaternionic) to define quaternionic PCA (Q-PCA) where color faces are compactly represented. Unlike the existing approaches for handling the color information, the proposed algorithm implicitly accounts for the correlation that exists between the face color components (i.e., red, green and blue, respectively).
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eprint-Emad_Jaha_ICDP11_Color_Face_Recognition_using_Q-PCA.pdf
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Published date: November 2011
Venue - Dates:
4th International Conference on Imaging for Crime Detection and Prevention 2011 (ICDP 2011), Kingston, United Kingdom, 2011-11-03 - 2011-11-04
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Local EPrints ID: 372296
URI: http://eprints.soton.ac.uk/id/eprint/372296
PURE UUID: b904bf48-e75a-481f-a466-9a4aa5c19df5
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Date deposited: 08 Dec 2014 12:23
Last modified: 14 Mar 2024 18:34
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Contributors
Author:
Emad Sami Jaha
Author:
Ghouti Lahouari
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