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Recognition for Ocular Fundus Based on Shape of Blood Vessel

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Graphics Recognition. Ten Years Review and Future Perspectives (GREC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3926))

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Abstract

A new biometric technology-recognition ocular fundus based on shape of blood vessel skeleton-is addressed in this paper. The gray scale image of ocular fundus is utilized to extract the skeletons of its blood vessels. The cross points on the skeletons are used to match two fundus images. Experiments show high recognition rate, low recognition rejection rate as well as good universality, exclusiveness and stability of this method.

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References

  1. Ulupinar, F., Medioni, G.: Refining edges detected by LoG operator. Computer Vis Graph and Image Process 51, 275–298 (1990)

    Article  Google Scholar 

  2. Canny, J.: Acomputational approach to edge detection. IEEE Trans, PAMI 8, 679–698 (1986)

    Article  Google Scholar 

  3. Peng, J., Rusch, P.: Morphological filters and edge detection application to medical imaging. In: Annual International Conference of the IEEE Engineering In Medicine and Biology Society, vol. 13(1), pp. 251–252 (1991)

    Google Scholar 

  4. Huang, C.C., Li, C.C., Fan, N., et al.: A fast morphological filter for enhancement of angiographic images. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 13(1), pp. 229–230 (1991)

    Google Scholar 

  5. Tascini, G., Passerini, G., Puliti, P., et al.: Retina vascular network recognition. Proc. SPIE 1898, 322–329 (1993)

    Article  Google Scholar 

  6. Chauduri, S., Chatterjee, S., Katz, N., et al.: Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Trans. Med. Imaging 8, 263–269 (1989)

    Article  Google Scholar 

  7. Ji, T.-L., Sundareshan, M.K., Roehrig, H.: Adaptive image contrast enhancement based on human visual properties. IEEE Trans. Med. Imaging 13, 573–586 (1994)

    Article  Google Scholar 

  8. Matsopoulos, G.K., Mouravliansky, N.A., Delibasis, K.K., et al.: Automatic retinal image registration scheme using global optimization techniques. IEEE Trans. Information Technology in Biomedicine 3(1), 47–60 (1999)

    Article  Google Scholar 

  9. Maes, F., Collignon, A., Vandermeulen, D., et al.: Multi-modality image registration by maximization of mutual information. IEEE Trans. Med. Img. 16(2), 187–198 (1997)

    Article  Google Scholar 

  10. Zhan, X.-S., Ning, X.-B., Yin, Y.-L., Chen, Y.: An improved point pattern algorithm for fingerprint matching. Journal of Nanjing University 39(4), 491–498 (2003)

    Google Scholar 

  11. Qi, Y., Tian, J., Deng, X.: Genetic algorithm based fingerprint matching algorithm and its application on automated fingerprint identification system. Journal of Software 11(4), 488–493 (2000)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Key Laboratory of Symbolic Computation and Knowledge Engineering, Jilin University, Changchun, 130012, China

    Zhiwen Xu, Xiaoxin Guo, Xu Chen & Zhengxuan Wang

  2. College of Computer Science and Technology, Jilin University, Changchun, 130012, China

    Zhiwen Xu, Xiaoxin Guo, Xu Chen & Zhengxuan Wang

  3. The First Clinical Hospital, Jilin University, Changchun, 130012, China

    Xiaoying Hu

Authors
  1. Zhiwen Xu
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  2. Xiaoxin Guo
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  3. Xiaoying Hu
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  4. Xu Chen
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  5. Zhengxuan Wang
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Editor information

Editors and Affiliations

  1. Department of Computer Science, City University of Hong Kong, Hong Kong, China

    Wenyin Liu

  2. Computer Vision Center, Universitat Autònoma de Barcelona, 08193, Bellaterra (Barcelona), Spain

    Josep Lladós

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© 2006 Springer-Verlag Berlin Heidelberg

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Xu, Z., Guo, X., Hu, X., Chen, X., Wang, Z. (2006). Recognition for Ocular Fundus Based on Shape of Blood Vessel. In: Liu, W., Lladós, J. (eds) Graphics Recognition. Ten Years Review and Future Perspectives. GREC 2005. Lecture Notes in Computer Science, vol 3926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11767978_12

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  • DOI: https://doi.org/10.1007/11767978_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34711-8

  • Online ISBN: 978-3-540-34712-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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