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The Curve Filter Transform – A Robust Method for Curve Enhancement

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Advances in Visual Computing (ISVC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6454))

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Abstract

In this paper we introduce the Curve Filter Transform, a powerful tool for enhancing curve-like structures in images. The method extends earlier works on orientation fields and the Orientation Field Transform. The result is a robust method that is less sensitive to noise and produce sharper images than the Orientation Field Transform. We describe the method and demonstrate its performance on several examples where we compare the result to the Canny edge detector and the Orientation Field Transform. The examples include a tomogram from a biological cell and we also demonstrate how the method can be used to enhance handwritten text.

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References

  1. Ballard, D.H.: Generalizing the Hough Transform to Detect Arbitrary Shapes. Pattern Recognition 13, 111–112 (1981)

    Article  MATH  Google Scholar 

  2. Brega, M.: Orientation Fields and Their Application to Image Processing. Master’s Thesis, University of Colorado at Boulder (2005)

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  3. Canny, J.: A Computational Approach to Edge Detection. IEEE Trans. Pattern Analysis 8, 679–698 (1986)

    Article  Google Scholar 

  4. Gu, J., Zhou, J.: A novel model for orientation field of fingerprints. In: Proc. 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 493–498 (2003)

    Google Scholar 

  5. Sandberg, K., Brega, M.: Segmentation of thin structures in electron micrographs using orientation fields. J. Struct. Biol. 157, 403–415 (2007)

    Article  Google Scholar 

  6. Sandberg, K.: Methods for image segmentation in cellular tomography. In: McIntosh, J.R. (ed.) Methods in Cell Biology: Cellular Electron Microscopy, vol. 79, pp. 769–798. Elsevier, Amsterdam (2007)

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  7. Sandberg, K.: Curve enhancement using orientation fields. In: Bebis, G. (ed.) ISVC 2009, Part 1. LNCS, vol. 5875, pp. 564–575. Springer, Heidelberg (2009)

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  8. Sandberg, K.: The Generalized Orientation Field Transform. In: Barneva, R.P., et al. (eds.) Object Modeling, Algorithms, and Applications, pp. 107–112. Research Publishing (2010)

    Google Scholar 

  9. Weickert, J.: Anisotropic Diffusion in Image Processing. Teubner-Verlag, Stuttgart (1998)

    Google Scholar 

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Sandberg, K. (2010). The Curve Filter Transform – A Robust Method for Curve Enhancement. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17274-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-17274-8_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17273-1

  • Online ISBN: 978-3-642-17274-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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