Abstract
Illumination variations is one of the factors that causes the degradation of face recognition systems performance. The representation of face image features using the structure of quaternion numbers is a novel way to alleviate the illumination effects on face images. In this paper a comparison of different quaternion representations, based on verification and identification experiments, is presented. Four different face features approaches are used to construct quaternion representations. A quaternion correlation filter is used as similarity measure, allowing to process together all the information encapsulated in quaternion components. The experiment results confirms that using quaternion algebra together with existing face recognition techniques permits to obtain more discriminative and illumination invariant methods.
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Rizo-Rodriguez, D., Méndez-Vázquez, H., García, E., Martín, C.S., Meza, P. (2011). Quaternion Correlation Filters for Illumination Invariant Face Recognition. In: San Martin, C., Kim, SW. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2011. Lecture Notes in Computer Science, vol 7042. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25085-9_55
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DOI: https://doi.org/10.1007/978-3-642-25085-9_55
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