Paper
22 May 2014 A color and texture based multi-level fusion scheme for ethnicity identification
Hongbo Du, Sheerko Hma Salah, Hawkar O. Ahmed
Author Affiliations +
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.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongbo Du, Sheerko Hma Salah, and Hawkar O. Ahmed "A color and texture based multi-level fusion scheme for ethnicity identification", Proc. SPIE 9120, Mobile Multimedia/Image Processing, Security, and Applications 2014, 91200B (22 May 2014); https://doi.org/10.1117/12.2057722
Lens.org Logo
CITATIONS
Cited by 5 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
RGB color model

Feature extraction

Databases

Facial recognition systems

Image fusion

Binary data

Light sources and illumination

Back to Top