Thermal Video Analysis for Fire Detection Using Shape Regularity and Intensity Saturation Features
This paper presents a method to detect fire regions in thermal videos that can be used for both outdoor and indoor environments. The proposed method works with static and moving cameras. The detection is achieved through a linear weighted classifier which is based on two features. The features are extracted from candidate regions by the following process; contrast enhance by the Local Intensities Operation and candidate region selection by thermal blob analysis. The features computed from these candidate regions are; region shape regularity, determined by Wavelet decomposition analysis and region intensity saturation. The method was tested with several thermal videos showing a performance of 4.99% of false positives in non-fire videos and 75.06% of correct detection with 7.27% of false positives in fire regions. Findings indicate an acceptable performance compared with other methods because this method unlike other works with moving camera videos.
Keywordsfire detection thermal image processing image segmentation
- 6.Kamgar-Parsi, B.: Improved image thresholding for object extraction in IR images. IEEE International Conference on Image Processing 1, 758–761 (2001)Google Scholar
- 7.Heriansyah, R., Abu-Bakar, S.A.R.: Defect detection in thermal image for nondestructive evaluation of petrochemical equipments. In: NDT & E International, vol. 42(8), pp. 729–774. Elsevier, Amsterdam (2009)Google Scholar
- 8.Chacon, M.I.: Digital Image Processing (in spanish). Editorial Trillas (2007)Google Scholar
- 9.Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn., pp. 648–649. Prentice-Hall, Englewood Cliffs (2002)Google Scholar