Illumination Invariant Face Image Representation Using Quaternions
نویسندگان
چکیده
Variations in illumination is a well-known affecting factor on face recognition system performance. Features extraction is one of the principal steps on a face recognition framework, where it is possible to alleviate the illumination effects on face images. The aim of this work is to study the illumination invariant properties of an hypercomplex image representation. A quaternion description from the image is built using second order derivatives decomposition. This representation is transformed to quaternion frequency domain and its illumination invariant and discriminative properties are compared against complex frequency domain obtained from a complex representation constructed with first order derivative decomposition. The hypercomplex quaternion representation was found to be more discriminative than the complex one, when comparing on face recognition with images under varying lighting conditions.
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تاریخ انتشار 2010