Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
권호 표지

Reducing Computational Complexity for Local Maxima Detection Using Facet Model

페이싯 모델을 이용한 국부 극대점 검출의 처리 속도 개선

  • Received : 2012.05.17
  • Accepted : 2012.08.01
  • Published : 2012.07.30
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we propose a technique to detect the size and location of the small target in images by using Gaussian kernel repeatedly. In order to detect the size and location of the small target, we find the local maximum value by applying the facet model and then use the $3{\times}3$ Gaussian kernel repeatedly. we determine the size of small target by comparing the local maximum value $D_2$ according to the number of iteration. To reduce the computational complexity, we use the Gaussian pyramid when using the kernel repeatedly. Through the experiment, we verified that the size and location of the small target is detected by the number of iterations and results show improvements from conventional methods.

본 논문에서는 영상에서 반복적인 가우시안 커널을 사용하여 소형 표적의 크기와 위치를 검출하는 방법을 제안한다. 소형 표적의 크기와 위치를 검출하는 방법은 우선 페이싯 모델을 원 영상에 적용하여 국부 극대 값을 검출하고 $3{\times}3$ 가우시안 커널을 반복적으로 사용한다. 이때 반복횟수에 따른 국부 극대값 $D_2$를 비교하여 이에 따른 소형 표적의 크기를 결정한다. 또한 계산의 복잡성을 줄이기 위하여 커널을 반복적으로 사용할 때 가우시안 피라미드를 사용하였다. 실험에서는 소형 표적의 크기와 위치가 반복 횟수에 따라 정확히 검출되는 것을 확인하였고 기존의 방법에 비하여 처리속도가 개선된 것을 확인하였다.

Keywords

References

  1. J. Li, Z. Shen and W. Yang, "Small target detection in noisy image sequences," Proc. of IEEE, vol. 2, pp. 868-872, 1997.
  2. M. Hu, Y. Shen, and Z. Shen, "New adaptive background suppression algorithm via one step M- filter," Proc. of ICSP, vol. 2, 2006.
  3. J. Peng, and W. Zhou, "Infrared background suppression for segmenting and detecting small target," Acta Electron, vol. 27, no. 12, pp. 47-51, 1999.
  4. L. Yang, J. Yang, and K. Yang, "Adaptive detection for infrared small target under sea-sky complex background," Electron. Lett., vol. 40, no. 17, pp. 1083-1085, 2004. https://doi.org/10.1049/el:20045204
  5. D. J. Gregoris, S. K. W. Yu and S. Tritchew, "Detection of dim targets in FLIR imagery using multi scale transforms," Proc. of SPIE 2269, pp. 62-71, 1994.
  6. G. Wang, T. Zhang, L. Wei, and N. Sang, "Efficient method for multi scale small target fusion detection from a natural scene," Optical Engineering vol. 35, no. 3, pp. 761-768, 1997.
  7. Z. C. Wang, J. W. Tian, J. Liu, and S. Zheng, "Small infrared target fusion detection based on support vector machines in the wavelete domain," Optical Engineering, vol. 45, no. 7, 2006.
  8. Haralick, R.M. "Digital step edges from zero crossing of second directional derivatives," IEEE Trans. Pattern Anal. Mach. Intell., pp. 58-68, 1984.
  9. G. D. Wang, Ch. Y. Chen and X. B. Shen, "Facet-based infrared small target detection method," ELECTRONICS LETTERS, vol. 41, no. 22, pp 1244-1246, 2005. https://doi.org/10.1049/el:20052289
  10. Gyoon-Jung Lee, Ji-Hwan Park, Jae-Heum Joo, Ki-Gon Nam, "The Size and Position Detection of the Small Target in Infrared Image," Information: An International Interdisciplinary Joural, vol. 14, no. 11, pp. 3857-3868, Nov. 2011.