Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지
DOI QR코드

DOI QR Code

Image Matching Algorithm for Thermal Panorama Image Construction Adaptable for Fire Disasters

화재상황에서 적용가능한 열화상 카메라의 파노라마 촬영을 위한 동일점 추출 알고리즘

  • Gwak, Dong-Gi (Department of Mechanical Design and Robot Engineering, Seoul National University of Science and Technology) ;
  • Kim, Dong Hwan (Department of Mechanical System Design Engineering, Seoul National University of Science and Technology)
  • 곽동기 (서울과학기술대학교 대학원 기계설계로봇공학과) ;
  • 김동환 (서울과학기술대학교 기계시스템디자인공학과)
  • Received : 2016.08.10
  • Accepted : 2016.10.17
  • Published : 2016.11.01
Download PDF
⟨ Previous Next ⟩

Abstract

In a fire disaster in a tunnel, people should be rescued immediately using the information obtained from cameras or sensors. However, in heavy smoke from a fire, people cannot be clearly identified by a mounted CCTV, which is only effective in a clear environment. A thermal camera can be an alternative to this in smoky situations and is capable of detecting people from their emitted thermal energy. On the other hand, the thermal image camera has a smaller field of view than an ordinary camera due to its lens characteristics and temperature error, etc. In order to cover a relatively wide area, panoramic image construction needs to be implemented. In this work, a template-based similarity matching algorithm for constructing the panorama image is proposed and its performance is verified through experiments. This scheme provides guidelines for coping with difficulty in image construction, which requires an exact correspondence search for two images in cases of heavy smoke.

Keywords

References

  1. W. Joseph and B. Lattimer, "Evaluation of navigation sensors in fire smoke environments," Fire Technology, vol. 50, pp. 1459-1481, 2014. https://doi.org/10.1007/s10694-013-0356-3
  2. J. Yang, J. Jeon, and G. Park "Overlap estimation for panoramic image generation," The Journal of Korea Society of Communication and Sapce Technology (in Korean), vol. 9, pp. 18-27, Nov. 2014.
  3. J. Kim and D. Kim, "Matching points filtering applied panorama image processing SURF and RANSAC algorithm," Journal of The Insitute of Electronics and Infomation Engineers, vol. 51, no. 4, pp. 144-159, Apr. 2014. https://doi.org/10.5573/ieie.2014.51.4.144
  4. K. Kim and J. Park, "Calibration of radial distortion and synthesis of panoramic image from multi-directional camera images," The Journal of Korean Institute of Next Generation Computing (in Korean), vol. 9, no. 6, pp. 56-65, Dec. 2013.
  5. R. Brunelli, "Template matching techniques in computer vision: Theory and practice," A John Wiley and Sons, Mar. 2009.
  6. L. Juan, S. Shin, H. Park, and O. Gwun, "Stitching for panorama based on SURF and multi-band blending," Journal of Korea Multimedia Society, vol. 14, no. 2, pp. 201-209, Feb. 2011. https://doi.org/10.9717/kmms.2011.14.2.201
  7. C. Harris and M. Stephens, "A combined corner and edge detector," Proceedings of the 4th Alvey Vision Conference, pp. 147-151, 1988.
  8. C. Tomasi and T. Kanade, "Detection and tracking of point feature," Pattern Recognition, vol. 37, pp. 165-168, 2004. https://doi.org/10.1016/S0031-3203(03)00234-6
  9. Tsai, "Fast normalized cross correlation for defect detection," Pattern Recognition Letters, vol. 24, no. 15, pp. 2625-2631, Nov. 2003. https://doi.org/10.1016/S0167-8655(03)00106-5
  10. A. Kumar, A. Joshi, A. Kumar, A. Mittal, and R. Hangodkar, "Template matching application in geo-referencing of remote sensing temporal image," International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 7, no. 2, pp. 201-210, Jul. 2014. https://doi.org/10.14257/ijsip.2014.7.2.19
  11. OpenCV, "Stitching," http://docs.opencv.org/2.4/modules/stitching/doc/stitching.html, Aug. 2016.