Abstract
In this paper we introduce a scheme to obtain affine invariant descriptors for color images using Independent Component Analysis (ICA), which is a further application of using ICA on contour-known objects. First, some feature points can be found by hue-histogram of the color images in HIS space. Then ICA is applied to extract an invariant descriptor between these corresponding points, which can be a representation of shape similarity between original image and its affine image. This proposed algorithm can also estimate affine motion parameters. Simulation results show that ICA method has better performance compared with Fourier methods.
This research is supported by the NSF(60171036) and the significant technology project (03DZ14015), Shanghai, China.
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References
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Liu, C., Huang, X., Zhang, L. (2005). Affine Invariant Descriptors for Color Images Based on Independent Component Analysis. In: Wang, J., Liao, X., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427391_158
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DOI: https://doi.org/10.1007/11427391_158
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25912-1
Online ISBN: 978-3-540-32065-4
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