Face Classification Using Color Information
AbstractColor 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
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Sajjanhar, A.; Mohammed, A.A. Face Classification Using Color Information. Information 2017, 8, 155.
Sajjanhar A, Mohammed AA. Face Classification Using Color Information. Information. 2017; 8(4):155.Chicago/Turabian Style
Sajjanhar, Atul; Mohammed, Ahmed A. 2017. "Face Classification Using Color Information." Information 8, no. 4: 155.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.