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Proceedings Paper

A color and texture based multi-level fusion scheme for ethnicity identification
Author(s): Hongbo Du; Sheerko Hma Salah; Hawkar O. Ahmed
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Paper Abstract

Ethnicity identification of face images is of interest in many areas of application. Different from face recognition of individuals, ethnicity identification classifies faces according to the common features of a specific ethnic group. This paper presents a multi-level fusion scheme for ethnicity identification that combines texture features of local areas of a face using local binary patterns with color features using HSV binning. The scheme fuses the decisions from a k-nearest neighbor classifier and a support vector machine classifier into a final identification decision. We have tested the scheme on a collection of face images from a number of publicly available databases. The results demonstrate the effectiveness of the combined features and improvements on accuracy of identification by the fusion scheme over the identification using individual features and other state-of-art techniques.

Paper Details

Date Published: 22 May 2014
PDF: 12 pages
Proc. SPIE 9120, Mobile Multimedia/Image Processing, Security, and Applications 2014, 91200B (22 May 2014); doi: 10.1117/12.2057722
Show Author Affiliations
Hongbo Du, The Univ. of Buckingham (United Kingdom)
Sheerko Hma Salah, Koya Univ. (Iraq)
Hawkar O. Ahmed, Univ. of Sulaimani (Iraq)


Published in SPIE Proceedings Vol. 9120:
Mobile Multimedia/Image Processing, Security, and Applications 2014
Sos S. Agaian; Sabah A. Jassim; Eliza Yingzi Du, Editor(s)

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