基于颜色空间归一化和四元数矩阵表示的彩色人脸识别

Huajie Jia, Lichun Wang, Yanfeng Sun, Yongli Hu
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引用次数: 6

摘要

基于四元数矩阵表示的彩色人脸识别方法是基于RGB色彩空间的,RGB色彩空间是一种基础且应用广泛的空间。然而,由于三个颜色通道之间的相关性很强,RGB颜色空间对于人脸识别来说是一个相对较弱的颜色空间。一种称为色彩空间归一化(CSN)的技术可以降低RGB色彩空间三个通道之间的相关性,增强归一化后的色彩空间RGB- n的识别能力。因此,本文首先提出了一种基于归一化色彩空间RGB-N和四元数矩阵表示的方法。该方法不仅具有四元数矩阵表示模型的优点,而且由于CSN的存在,具有较强的判别能力。本文的实验是在FERET彩色人脸数据库上进行的。与基于RGB色彩空间和四元数矩阵表示的方法相比,该方法可以提高图像的识别率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Color Face Recognition Based on Color Space Normalization and Quaternion Matrix Representation
The color face recognition method using quaternion matrix representation is based on RGB color space which is a fundamental and widely used space. However, the RGB color space is a relatively weak color space for face recognition due to the strong correlation between the three color channels. A technique named color space normalization (CSN) technique can reduce the correlation between the three channels of the RGB color space, and enhance the discriminating power of the normalized color space RGB-N. Therefore, in this paper, a method based on normalized color space RGB-N and quaternion matrix representation is firstly proposed. The proposed method not only has the advantage of quaternion matrix representation model, but also has the strong discriminating power due to CSN. The experiments in this paper are performed on the FERET color face database. Compared with the method based on RGB color space and quaternion matrix representation, the proposed approach in this paper can enhance the recognition rate.
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