Abstract
This paper proposes an image matching method that is robust to illumination variation and affine distortion. Our idea is to do image matching through establishing an imaging function that describes the functional relationship relating intensity values between two images. Similar methodology has been proposed by Viola [11] and Lai & Fang [6]. Viola proposed to do image matching through establishment of an imaging function based on a consistency principle. Lai & Fang proposed a parametric form of the imaging function. In cases where the illumination variation is not globally uniform and the parametric form of imaging function is not obvious, one needs to have a more robust method. Our method aims to take care of spatially non-uniform illumination variation and affine distortion. Central to our method is the proposal of a localized consistency principle, implemented through a non-parametric way of estimating the imaging function. The estimation is effected through optimizing a similarity measure that is robust under spatially non-uniform illumination variation and affine distortion. Experimental results are presented from both synthetic and real data. Encouraging results were obtained.
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© 2002 Springer-Verlag Berlin Heidelberg
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Wang, B., Sung, K.K., Ng, T.K. (2002). The Localized Consistency Principle for Image Matching under Non-uniform Illumination Variation and Affine Distortion. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds) Computer Vision — ECCV 2002. ECCV 2002. Lecture Notes in Computer Science, vol 2350. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47969-4_14
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DOI: https://doi.org/10.1007/3-540-47969-4_14
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