Survey of computer vision-based natural disaster warning systems

Optical Engineering

Volumn 51, Issue 7, 2012, Pages

  Ko, Byoungchul ^a   Kwak, Sooyeong ^b  

^a Keimyung University   (South Korea)

^b Hanbat National University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

FLOOD PREVENTION; FUTURE RESEARCH DIRECTIONS; LANDSLIDE DETECTION; NATURAL DISASTERS; PATTERN RECOGNITION TECHNIQUES; RESEARCH FIELDS; SURVEILLANCE SYSTEMS; WATER LEVEL DETECTIONS; VISION SENSORS; WILDFIRE DETECTION;

DISASTER PREVENTION; FLOOD CONTROL; GEOGRAPHIC INFORMATION SYSTEMS; INFORMATION TECHNOLOGY; PATTERN RECOGNITION; WATER LEVELS; COASTAL ZONES; FIRES; LANDSLIDES; REMOTE SENSING;

DISASTERS;

EID: 84875608052     PISSN: 00913286     EISSN: 15602303     Source Type: Journal    
DOI: 10.1117/1.OE.51.7.070901     Document Type: Review

References (36)

1. K. Suzuki, Good Practices 2007 Supplement, Asian Disaster Reduction Center (ADRC), Japan (2007).
2. B. C. Ko, K. H. Jung, and J. Y. Nam, "Early fire detection algorithm based on irregular patterns of flames and hierarchical Bayesian Networks," Fire Safety J. 45(2), 262-270 (2010).
3. Wikipedia, Smoke detector [Online]. Available: http://en.wikipedia.org/ wiki/Smoke-detector#Optical (2011).
4. B. Marshall, How Smoke Detectors Work, An article of HowStuffWorks.com, (April 2010).
5. J. Yu and H. Hahn, "Remote detection and monitoring of a water level using narrow band channel," J. Inform. Sci. Eng. 26(1), 71-82 (2010).
6. R. A. Lawson, "Tsunami detection systems for international requirements," in Oceans, Vancouver, BC, pp. 1-7 (2007).
7. G. M. Beltrami, M. D. Risio, and P. D. Girolamo, The Tsunami Threat-Research and Technology, InTech open access publisher (2011).
8. K. Higuchi et al., "Application of new landslide monitoring technique using optical fiber sensor at Takisaka landslide," in 1st North American Landslide Conf, pp. 1-9 (2007).
9. B. C. Ko, H. J. Hwang, and J. Y Nam, "Nonparametric membership functions and fuzzy logic for vision sensor-based flame detection," J. Opt. Eng. 49(12), 127202 (2010).
10. B. C. Ko, S. J. Ham, and J. Y Nam, "Modeling and formalization of fuzzy finite automata for detection of irregular fire flames," IEEE Trans. Circuits Syst. Video Technol. 21(12), 1903-1912 (2011).
11. B. C. Ko, J. Y Kwak, and J. Y Nam, "Wildfire smoke detection using temporal-spatial features and random forest classifiers," Opt. Eng. 51(1), 017208 (2012).
12. S. J. Ham, B. C. Ko, and J. Y Nam, "Vision-based forest smoke detection using analyzing of temporal patterns of smoke and their probability models," Proc. SPIE 7877, 78770A (2011).
13. Y H. Habiboglu, O. Gunay, and E. Cetin, "Real-time wildfire detection using correlation descriptors," in 19th European Signal Processing Conf, Barcelona, Spain, pp. 894-898 (2011).
14. B. U. Toreyin and A. E. Cetin, "Wildfire detection using LMS based active learning," in Proc. IEEE Int. Conf. on Acoustics Speech and Signal Processing, pp. 1461-1464 (2009).
15. J. Gubbi, S. Marusica, and M. Palaniswamia, "Smoke detection in video using wavelets and support vector machines," Fire Safety J. 44(8), 1110-1115 (2009).
16. P. Guillemant and J. Vicente, "Real-time identification of smoke images by clustering motions on a fractal curve with a temporal embedding method," Opt. Eng. 40(4) 554-563 (2001).
17. O. Gunay et al., "Video based wild fire detection at night," Fire Safety J. 44(6), 860-868 (2009).
18. T. Celik, H. Ozkaramanli, and H. Demirel, "Fire and smoke detection without sensors: image processing based approach," in European Signal Processing. Conference, pp. 1794-1798 (2007).
19. J. Li et al., "Technique for automatic forest fire surveillance using visible light image," in Int. Conf. Geoscience and Remote Sensing Symposium, Vol. 5, pp. 31-35 (2005).
20. I. Bosch et al., "Infrared image processing and its application to forest fire surveillance," in IEEE Int. Conf on Advanced Video and Signal Based Surveillance, pp. 283-288, IEEE Computer Society, Washington, DC (2007).
21. S. Udomsiri and M. Iwahashi, "Design of FIR filter for water level detection," World Acad. Sci. Eng. Technol. 48, 47-52 (2008).
22. S. Park et al., "The water level detection algorithm using the accumulated histogram with band pass filter," Acad. Sci. Eng. Technol. 56, 193-197 (2009).
23. J. Y Kwak, B. C. Ko, and J. Y Nam, "Automatic water-level detection using CCD camera and k-mean clustering," J. Kor. Soc. Image Sci. Technol. 17(9), 1-8 (2011).
24. K. W. Chapman, Camera based water level detection, White paper of the Imaging Source Europe GmbH (2011).
25. H. Burcharth, Developing Coastal Video Systems in Support of Coastal Zone Management, The CoastView Project: 3rd Annual (Final) Report, The CoastView Project.org (2005).
26. I. Turner and D. Anderson, "Web-based and 'real-time' beach management system," Coast. Eng. 54(6-7), 555-565 (2007).
27. L. Uunk, K M. Wijnberg, and R. Morelissen, "Automated mapping of the intertidal beach bathymetry from video images," Coast. Eng. 57(4), 461-469 (2010).
28. K. Ishimoto, T Chiba, and Y Kajiya, "Wave overtopping detection by imge processing," in The second World Congress on Intelligent Transport Systems, pp. 515-518 (1995)
29. Ministry of Land, Infrastructure and Transport in Japan, Overtopping Wave Monitoring system, ITS Handbook 2001-2002 (2001).
30. M. Seki, H. Taniguchi, and M. Hashimoto, "Overtopping wave detection based on wave contour measurement," IEEJ Trans. Electron. Inform. Syst. 127(4), 599-604 (2007).
31. J. Y Rau, Y C. Shao, and L.-C. Chen, "Landslides detection using aerial ortho-images and LiDAR data," in Proc. of Asian Assoc. Remote Sens., pp. 1-6 (2006).
32. J. Hervas and P. L. Rosin, "Image thresholding for landslide detection by genetic programming," in Proc. of the First International Workshop on Multitemporal Remote Sensing Images, Italy, pp. 65-72 (2002).
33. S. K. Bejo, M. Petrou, and A. Ganas, "Local similarity measure for landslide detection and identification in comparison with the image differencing method," Int. J. Remote Sensing 31(23), 6033-6045 (2010).
34. T R. Martha and N. Kerle, "Segment optimisation for object-based landslide detection," Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci. XXXVIII-4/C7(1), 1-6 (2010).
35. B. C. Ko et al., "Current trend in natural disaster warning systems based on computer vision techniques," in First Asian Conf. on Pattern Recog-nition, Beijing, China, pp. 1-5 (2011)
36. M. Davidson et al., "The coastview project: developing video-derived coastal state Indicators in support of coastal zone management," Coast. Eng. 54(6-7), 463-475 (2007).