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A Thinning Model for Handwriting-Like Image Skeleton

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Computer Engineering and Networking

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 277))

Abstract

In order to solve the letter skeleton problem with handwriting-like attributes, a thinning model is used in this paper. By introducing improved reservation and eliminating produces, additional pixels are constrained by thinning nearest pixels. In the experiment, the proposed method is compared with others in the literature English letters by using the one pass thinning algorithm (OPTA) and Hilditch methods. Empirical results show that the proposed model can thin handwriting-like skeleton in terms of reserving topology and eliminating extra pixels.

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References

  1. Jawahar, C. V., Balasubramanian, A., Million, M., & Namboodiri, A. M. (2009). Retrieval of online handwriting by synthesis and matching. Pattern Recognition, 42(7), 1445–1457.

    Article  MATH  Google Scholar 

  2. Cheng, J., Wang, J., Jiang, S., Zhou, Z.-H., & Hancock, E. (2011). Special edition on semi-supervised learning for visual content analysis and understanding”. Pattern Recognition, 44(10–11): 2242–2243.

    Google Scholar 

  3. Shang, L., Yi, Z., & Ji, L. (2007). Binary image thinning using autowaves generated by PCNN. Neural Processing Letters, 25(1), 49–62.

    Article  Google Scholar 

  4. Xing-kui, F., Lin-yan, L., & Zu-quan, Y. (1999). A new thinning algorithm for finger print image. Journal of Image and Graphics, 4(10), 835–838.

    Google Scholar 

  5. Peter I. Rockett, “An Improved Rotation-Invariant Thinning Algorithm,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 10, pp. 1671–1674, Oct. 2005.

    Google Scholar 

  6. Jia, Yu., & Yaqin, Li. (2009). Improving Hilditch thinning algorithms for text image”. 2009 International Conference on E-Learning, E-Business. Enterprise information Systems and E-Government. pp. 76–79.

    Google Scholar 

  7. Imiya, A., & Saito, M. (2006). Thinning by curvature flow. Journal of Visual Communication and Image Representation, 17(1), 27–41.

    Article  Google Scholar 

  8. Ravi, J., Raja, K. B., & Venugopal, K. R. (2009). Fingerprint recognition using minutiae score matching. International Journal of Engineering Science and Technology, 1, 35–42.

    Google Scholar 

  9. Bag, S., & Harit, G. (2011). An improved contour-based thinning method for character images. Pattern Recognition Letters, 32(11), 1836–1842.

    Article  Google Scholar 

  10. Jinhai, C. (2012). Robust filtering-based thinning algorithm for pattern recognition. The Computer Journal, 55(7), 887–896.

    Article  Google Scholar 

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Correspondence to Shijiao Zhu .

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© 2014 Springer International Publishing Switzerland

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Zhu, S., Yang, J., Zhu, Xf. (2014). A Thinning Model for Handwriting-Like Image Skeleton. In: Wong, W.E., Zhu, T. (eds) Computer Engineering and Networking. Lecture Notes in Electrical Engineering, vol 277. Springer, Cham. https://doi.org/10.1007/978-3-319-01766-2_79

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  • DOI: https://doi.org/10.1007/978-3-319-01766-2_79

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01765-5

  • Online ISBN: 978-3-319-01766-2

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