Abstract
In this paper, two approaches to improve the illumination robustness of the face recognition algorithms are presented, that is, Symmetrical Image Correction (SIC) and Bit-Plan Feature Fusion (BPFF). SIC can reduce bright speckles and shadows caused by over lighting. BPFF constructs a new virtual face with Bit-Plan information of face images. Generalized PCA is then applied to the virtual faces to achieve face recognition. Experiments show that, the proposed combined method can reduce the sensitivity of face recognition to illuminations using fewer projection vectors than the compared approaches.
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© 2006 Springer-Verlag Berlin Heidelberg
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Wang, H., Leng, Y., Wang, Z., Wu, X. (2006). Generalized PCA Face Recognition by Image Correction and Bit Feature Fusion. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4233. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893257_25
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DOI: https://doi.org/10.1007/11893257_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46481-5
Online ISBN: 978-3-540-46482-2
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