DOI QR코드

DOI QR Code

Object Recognition Algorithm with Partial Information

  • 투고 : 2019.09.20
  • 심사 : 2019.10.18
  • 발행 : 2019.12.31

초록

Due to the development of video and optical technology today, video equipments are being used in a variety of fields such as identification, security maintenance, and factory automation systems that generate products. In this paper, we investigate an algorithm that effectively recognizes an experimental object in an input image with a partial problem due to the mechanical problem of the input imaging device. The object recognition algorithm proposed in this paper moves and rotates the vertices constituting the outline of the experimental object to the positions of the respective vertices constituting the outline of the DB model. Then, the discordance values between the moved and rotated experimental object and the corresponding DB model are calculated, and the minimum discordance value is selected. This minimum value is the final discordance value between the experimental object and the corresponding DB model, and the DB model with the minimum discordance value is selected as the recognition result for the experimental object. The proposed object recognition method obtains satisfactory recognition results using only partial information of the experimental object.

키워드

참고문헌

  1. N. Bourbakis, Artificial Intelligence and Automation, World Scientific, pp. 10-26, 1998.
  2. A. Wexelblat, Virtual Reality Applications and Explorations, Academic Press, pp. 3-33, 2014.
  3. H. Cheng, Autonomous Intelligent Vehicles, Springer, pp. 13-20, 2011.
  4. C. Leondes, Image Processing and Pattern Recognition, Academic Press, pp. 22-35, 1998.
  5. K. Nam, "The Image of Elderly Perceived by Age of 4 and 5 Years", Journal of the Convergence on Culture Technology(JCCT), Vol. 2, No. 2, pp. 1-8, 2016. https://doi.org/10.17703/JCCT.2016.2.2.1
  6. S. Yoo, "Adaptive Thinning Algorithm for External Boundary Extraction", International Journal of Advanced Culture Technology (IJACT), Vol. 4, No. 4, pp. 75-80, 2016. https://doi.org/10.17703/IJACT.2016.4.4.75
  7. W. Pratt, Introduction to Digital Image Processing, CRC Press, pp. 139-154, 2013.
  8. M. Friedman, A. Kandel, Introduction to Pattern Recognition, World Scientific, pp. 55-68, 1999.