基于辐射能量和小波域子块DCT的红外人脸识别

Xiao-Wei Liu, Zhihua Xie, Cui-Qun He, Guodon Liu
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引用次数: 0

摘要

提出了一种新的红外人脸识别方法。该方法根据Stefan-Boltzmann定律,将原始热图像转换为辐射能量图像,并利用二尺度离散小波变换对其进行分解。将低频子带的分量划分成子块,然后进行DCT变换。在DCT域中,每个面由从子块中提取的系数表示。最后,根据DCT域中不同的子块的判别能力,分配不同的权重。实验结果表明,与其他方法相比,该方法具有较好的识别率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Infrared face recognition based on radiative energy and sub-block DCT in wavelet domain
A novel infrared face recognition method is proposed in this paper. In this method, according to Stefan-Boltzmann's law, the raw thermal images are transformed to the radiative energy images, and they are decomposed using two scales' discrete wavelet transform. The components of low frequency sub-bands are partitioned into sub-blocks, then, they are transformed by DCT. Each face is represented by the coefficients extracted from the sub-blocks in DCT domain. Finally, according to the discriminative power, different sub-blocks in DCT domain can be assigned different weights. Experiments demonstrate the method proposed perform very well on recognition rates as compared to other methods.
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