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A Novel Algorithm to Tackle Eyeglasses and Beard Issues in Facial IR Recognition

机译:解决面部红外识别中眼镜和胡须问题的新算法

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Face recognition via thermal infrared (IR) images is a modern recognition method that has found so interesting for many researchers during last decade. This method which operates via thermal features and the situation of human face vessels has much more benefits than visual-based methods. In these images, the changes of environmental light, which is one of the most important problems of face recognition via visual images, are completely eliminated. The most important face recognition problem via thermal IR images is the existence of diffusion obstacles like glasses, which blocks an accurate extraction of the face vessels situation. Using the proposed algorithm, this problem has been completely removed. In this article face recognition is performed through face vessels. In fact, the proposed method solves the issues of face recognition (like glasses wearing) in the thermal infrared domain suggested by Pavlidis et al in [5]. For extraction of the face features, the situation of vessel branches is used. Also, by choosing appropriate classification, fake vessels and false branches are removed. On the other hand, the best feature is extracted by using Dynamic Time Wrapping (DTW) algorithm which is resistant to nonlinear changes. The simulation on UTK-IRIS gallery set shows the accurate recognition rate 95% on the images with glasses. Thus, the proposed method has improved the recognition rate about 10% on same gallery set compared to the best other methods.
机译:通过热红外(IR)图像进行人脸识别是一种现代的识别方法,在过去的十年中,这种方法对许多研究人员来说非常有趣。这种通过热特征和人脸血管状况运行的方法比基于视觉的方法具有更多的好处。在这些图像中,完全消除了环境光的变化,环境光的变化是通过视觉图像进行人脸识别的最重要问题之一。通过热红外图像最重要的面部识别问题是像玻璃这样的扩散障碍物的存在,这阻碍了对面部血管状况的准确提取。使用提出的算法,此问题已被完全消除。在本文中,人脸识别是通过人脸血管进行的。实际上,所提出的方法解决了Pavlidis等人在文献[5]中提出的在热红外领域的人脸识别(如戴眼镜)问题。为了提取面部特征,使用了血管分支的情况。同样,通过选择适当的分类,可以删除假船只和假分支。另一方面,最好的特征是使用动态时间包装(DTW)算法提取的,该算法可以抵抗非线性变化。在UTK-IRIS画廊上进行的仿真显示,戴着眼镜的图像的准确识别率达到95%。因此,与最佳的其他方法相比,该方法在同一图库集上的识别率提高了约10%。

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