Abstract
Channel smoothing is an alternative to diffusion filtering for robust estimation of image features. Its main advantages are speed, stability with respect to parameter changes, and a simple implementation. However, channel smoothing becomes instable in certain situations, typically for elongated, periodic patterns like for instance fingerprints. As for the diffusion filtering an anisotropic extension is required in these cases. In this paper we introduce a new method for anisotropic channel smoothing which is comparable to coherence enhancing diffusion, but faster and easier to implement. Anisotropic channel smoothing implements an orientation adaptive non-linear filtering scheme as a special case of adaptive channel filtering. The smoothing algorithm is applied to several fingerprint images and the results are compared to those of coherence enhancing diffusion.
This work has been supported by DFG Grant FE 583/1–2
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Felsberg, M., Granlund, G. (2003). Anisotropic Channel Filtering. In: Bigun, J., Gustavsson, T. (eds) Image Analysis. SCIA 2003. Lecture Notes in Computer Science, vol 2749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45103-X_100
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DOI: https://doi.org/10.1007/3-540-45103-X_100
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