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Color face recognition based on color image correlation similarity discriminant model

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Abstract

The focus of face recognition is a classifying problem based on similarity measurement. This paper presents a color image correlation similarity discriminant (CICSD) model after defining within-class correlation and between-class correlation for color face recognition. The CICSD model unifies the color face image representation and recognition into one framework. Thus classifying performance while representing a color face image can be considered. Therefore, the present model involves in two sets of variables: the color component combination coefficients for color face image presentation and the projection basis vectors for color face recognition. An iterative CICSD algorithm is designed to find the optimal color component combination coefficients and the optimal projection basis vectors. Experimental results on the FERET and AR color face database show the effectiveness of the present model and algorithm.

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Acknowledgments

This work has been granted by the National Natural Science Foundation of China (No. 61133003, 61171169) and Beijing Natural Science Foundation(No. 4132013, kz201310005006).

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Correspondence to Yanfeng Sun.

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Sun, Y., Jia, H., Hu, Y. et al. Color face recognition based on color image correlation similarity discriminant model. Multimed Tools Appl 73, 2063–2079 (2014). https://doi.org/10.1007/s11042-013-1638-y

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  • DOI: https://doi.org/10.1007/s11042-013-1638-y

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