Double Linear Discriminate Analysis for Face Recognition
نویسندگان
چکیده
In this paper we propose a new algorithm for face recognition named as Double Linear Discriminate Analysis (DLDA) in which we combine two linear discriminate methods: 2D-LDA and Fisher-face sequentially. Experimental results on benchmark face datasets show that DLDA not only achieves the best performance when the number of training samples is appropriate, but also its speed is the fastest among three of them. Though the proposed method can operate on both gray and colour images, the performance is significantly better while operating on colour face datasets in comparison to 2D-LDA, Fisher-face and the Discriminate Colour Space method proposed specifically for colour face recognition recently.
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