Face Recognition in Low-resolution Images by Using Local Zernike Moments
نویسندگان
چکیده
In this paper, we propose a method that uses Local Zernike Moments (LZM) for face recognition in low-resolution face images. Global Zernike Moments produce one moment value for whole image, whereas LZM are based on the evaluation of the moments for each pixel. LZM are shown to achieve significant success and robustness in face recognition. In order to further increase the robustness of LZM against low resolution and blurred face images, we use a scale space representation similar to scale-invariant feature transform (SIFT) algorithm. The performance of LZM in low-resolution face images is tested on FERET database. Then a face recognition framework is formed according to these tests and results show that the proposed framework is promising for real world applications.
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