The Identification and Recognition Based on Point for Blood Vessel of Ocular Fundus

  • Zhiwen Xu
  • Xiaoxin Guo
  • Xiaoying Hu
  • Xu Chen
  • Zhengxuan Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3832)


Today, iris recognition, fingerprint recognition, face recognition, voice recognition and other biometric technology are experiencing rapid development. This paper addresses a new biometric technology–the identification and recognition based on point of blood vessel skeleton for ocular fundus. The image for green gray scale of ocular fundus is utilized. The cross point of skeleton shape of blood vessel for ocular fundus using contrast-limited adaptive histogram equalization is extracted at first. After filtering treatment and extracting shape, shape curve of blood vessels is obtained. The cross point of shape for curve matching is later carried out by means of cross point matching. The recognition based on shape for blood vessel of ocular fundus has been demonstrated in this paper to possess high Identification and recognition rate, low rejection recognition rate as well as good universality, exclusiveness and stability. With more and more progress made in extracting technology, the recognition for blood vessel of optic fundus is to become an effective biometric technology.


Feature Point Cross Point Fundus Image Iris Recognition Biometric Feature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Ulupinar, F., Medioni, G.: Refining edges detected by LoG operator. Comput Vis Graph and Image Process 51, 275–298 (1990)CrossRefGoogle Scholar
  2. 2.
    Canny, J.: Acomputational approach to edge detection. IEEE Trans. PAMI 8, 679–698 (1986)Google Scholar
  3. 3.
    Peng, J., Rusch, P.: Morphological filters and edge detection application to medical imaging. Annual International Conference of the IEEE Engineering In Medicine and Biology Society 13(1), 251–252 (1991)Google Scholar
  4. 4.
    Huang, C.C., Li, C.C., Fan, N., et al.: A fast morphological filter for enhancement of angiographic images. Annual International Conference of the IEEE Engineering in Medicine and Biology Society 13(1), 229–230 (1991)Google Scholar
  5. 5.
    Tascini, G., Passerini, G., Puliti, P., et al.: Retina vascular network recognition. Proc SPIE 1898, 322–329 (1993)CrossRefGoogle Scholar
  6. 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)CrossRefGoogle Scholar
  7. 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)CrossRefGoogle Scholar
  8. 8.
    Matsopoulos George, K., Mouravliansky Nicolaos, A., Delibasis Konstantinos, K., et al.: Automatic retinal image registration scheme using global optimization techniques. IEEE Trans On Information Technology In Biomedicine 3(1), 47–60 (1999)CrossRefGoogle Scholar
  9. 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)CrossRefGoogle Scholar
  10. 10.
    Xiao-Si, Z., Xin-Bao, N., Yi-Long, Y., Yun, C.: An Improved Point Pattern Algorithm for Fingerprint Matching. Journal of Nanjing University 39(4), 491–498 (2003)Google Scholar
  11. 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

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Zhiwen Xu
    • 1
  • Xiaoxin Guo
    • 1
  • Xiaoying Hu
    • 2
  • Xu Chen
    • 1
  • Zhengxuan Wang
    • 1
  1. 1.Open Symbol Computation and Knowledge Engineering Laboratory of State Education DepartmentCollege of Computer Science and Technology 
  2. 2.The First Clinical HospitalJilin UniversityChangchun CityChina

Personalised recommendations