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首页> 外文期刊>Advances in Distributed Computing And Artificial Intelligence Journal >A Comparison of the YCBCR Color Space with Gray Scale for Face Recognition for Surveillance Applications
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A Comparison of the YCBCR Color Space with Gray Scale for Face Recognition for Surveillance Applications

机译:YCBCR色彩空间与灰度的比较,用于监视应用中的人脸识别

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摘要

Face recognition is an important biometric method because of its potential applications in many fields, such as access control and surveillance. In this paper, the performance of the individual channels from the YCBCR colour space on face recognition for surveillance applications is investigated and compared with the performance of the grayscale. In addition, the performance of fusing two or more colour channels is also compared with that of the grayscale. Three cases with a different number of training images per persons were used as a test bed. It was found out that, the grayscale always outperforms the individual channel. However, the fusion of CBxCR with any other channel outperforms the grayscale when three images of the same class from the same database are used for training. Regardless of the cases used, the CBxCR channel always gave the best performance for the individual colour channels. It was found that, in general, increasing the number of fused channels increases the performance of the system. It was also found that the grayscale channel is the better choice for face recognition since it contains better quality edges and visual features which are essential for face recognition.
机译:人脸识别是一种重要的生物识别方法,因为它在许多领域(如访问控制和监视)中都有潜在的应用。本文研究了YCBCR色彩空间中各个通道在监视应用中的人脸识别性能,并将其与灰度性能进行了比较。此外,融合两个或更多颜色通道的性能也与灰度进行了比较。使用每人具有不同数量训练图像的三个案例作为测试床。发现,灰度总是优于单个通道。但是,当使用来自同一数据库的相同类别的三幅图像进行训练时,CBxCR与其他任何通道的融合均优于灰度。无论使用哪种情况,CBxCR通道始终为各个颜色通道提供最佳性能。已经发现,一般而言,增加融合通道的数量可以提高系统的性能。还发现,灰度通道是人脸识别的更好选择,因为它包含质量更好的边缘和视觉特征,这对于人脸识别至关重要。

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