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Information 2017, 8(4), 155; doi:10.3390/info8040155

Face Classification Using Color Information

School of Information Technology, Deakin University, Geelong, VIC 3216, Australia
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Received: 29 September 2017 / Revised: 26 October 2017 / Accepted: 23 November 2017 / Published: 26 November 2017
(This article belongs to the Section Information and Communications Technology)
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Abstract

Color models are widely used in image recognition because they represent significant information. On the other hand, texture analysis techniques have been extensively used for facial feature extraction. In this paper; we extract discriminative features related to facial attributes by utilizing different color models and texture analysis techniques. Specifically, we propose novel methods for texture analysis to improve classification performance of race and gender. The proposed methods for texture analysis are based on Local Binary Pattern and its derivatives. These texture analysis methods are evaluated for six color models (hue, saturation and intensity value (HSV); L*a*b*; RGB; YCbCr; YIQ; YUV) to investigate the effect of each color model. Further, we configure two combinations of color channels to represent color information suitable for gender and race classification of face images. We perform experiments on publicly available face databases. Experimental results show that the proposed approaches are effective for the classification of gender and race. View Full-Text
Keywords: gender classification; race classification; texture analysis; color models gender classification; race classification; texture analysis; color models
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Sajjanhar, A.; Mohammed, A.A. Face Classification Using Color Information. Information 2017, 8, 155.

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