Algorithm of Laser Spots Recognition Based on “Cat Eye Effect”

  • Qiang Wu
  • Li-Xiao Yao
  • Xu-Wen Li
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 298)


The paper designs an efficient recognition algorithm to detect laser spots with high Real-time. An improved Otsu is proposed to identify the target and exclude the noise on the condition of atmospheric turbulence. The problem that spot center is not accurate caused by the phenomenon of "supersaturated" is efficiently solved as well. Firstly, the difference the foreground image and the background image is calculated, the morphological filtering is done to segment the target. The elliptic characteristic of the target is used for preliminary identification. Many steps are designed in order to remove False-alarms and improve recognition accuracy. The algorithm is applied in the hardware TMS320C6455 system. Extensive experiments show that the algorithm not only ensures the matching accuracy but also improves the time response.


Spots Recognition Improved Otsu Algorithm Ellipse Detection Target Selection 


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  1. 1.
    Lin Xibo, A.: Summary of Laser Technology Application. J. Aerospace Shanghai 32(3) (2006)Google Scholar
  2. 2.
    Tong, L.-J., Jiang, X.-Y.: Target Detection Based on Laser Imaging with “Cat Eye Effect”. J. Laser & Infrared 9, 982–985 (2009)Google Scholar
  3. 3.
    Kamerman, G.W.: Laser Radar Signals the Civilian Sector. J. Laser Focus World (4), 81–87 (1996)Google Scholar
  4. 4.
    Zhang, Y.-J.: Image Segmentation, vol. 2, 3, pp. 43–60, 149–153. M. Sciences Press, Beijing (2001)Google Scholar
  5. 5.
    Lecocq, C., Deshors, G.: Sight Laser detection modeling. In: Proc. SPIE, vol. 5086, pp. 280–286 (2003)Google Scholar
  6. 6.
    Haibo, L., Jing, S.: Digital Iimage Processing Using Visual C++. pp. 245–251. M. China Machine Press, BeijingGoogle Scholar
  7. 7.
    Castlemen, K.R.: Digital Image Processing. Publishing House of Electronics Industry (1996)Google Scholar
  8. 8.
    Li, S.: Image Segmentation Methods Based on ROI and Adaptive Otsu Threshold Algorithm. J. Modern Electronics Technique 34(6) (2010)Google Scholar
  9. 9.
    Xie, Y.H., Ji, Q.: A New Efficient Ellipse Detection Method. In: J. Proceedings of the 16th International Conference on Pattern Recognition. IEEE Computer Society, Los Alamitos (2002)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Qiang Wu
    • 1
  • Li-Xiao Yao
    • 1
  • Xu-Wen Li
    • 2
  1. 1.College of Electronic Information and Control Engineering of Beijing University of TechnologyBeijingChina
  2. 2.College of Life Science and Bio-engineering of Beijing University of TechnologyBeijingChina

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