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Face recognition using separate layers of the RGB image

机译:面部识别使用RGB图像的单独层

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摘要

In many cases face recognition of still images is performed with greyscale images. These images are actually converted from a color image to greyscale before the analysis takes place. A consequence of such a conversion is obviously loss of information, which could influence the performance of the face recognition system. It would be interesting to see if using one of the three color layers of the RGB image could give better recognition performance compared to the greyscale converted image. We conducted two experiments and the results indeed support this idea. We found that the red layer of the RGB image gives the best recognition performance, especially in the cases where an extra light source is used to light up (part of) the face of the participants in the experiments. In the case that the participants were facing the camera we saw the Equal Error Rate drop from 3.3% for the greyscale images to 1.8% for the red layer of the RGB images in our initial experiment.
机译:在许多情况下,使用灰度图像来执行对静止图像的面部识别。在分析发生之前,这些图像实际上从彩色图像转换为灰度。这种转换的结果显然是信息损失,这可能影响面部识别系统的性能。有趣的是,与RGB图像的三个颜色层中的一个可以提供更好的识别性能,与灰度转换图像相比可以提供更好的识别性能。我们进行了两次实验,结果确实支持这个想法。我们发现RGB图像的红色层提供了最佳识别性能,尤其是在额外光源用于点亮(部分)在实验中的面部的情况下。在参与者面对相机的情况下,我们在初始实验中将灰度图像的3.3%的错误率下降到RGB图像的红色层的1.8%。

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