Fire Detection Algorithms Using Multimodal ... - Bilkent University

CHAPTER 3. FLAME DETECTION IN INFRA-RED (IR) VIDEO 51Table 3.1: Detection results for some of the test clips. In the video clip V3, flamesare hindered by a wall for most of the time.Number of framesNumber of falseVideo Number of frames in which flames detected positive framesclips with flames CVH Method Our Method CVH Method Our MethodV1 0 17 0 17 0V2 0 0 0 0 0V3 71 42 63 0 0V4 86 71 85 0 0V5 44 30 41 0 0V6 79 79 79 0 0V7 0 15 0 15 0V8 101 86 101 0 0V9 62 52 59 8 0V10 725 510 718 54 0V11 1456 1291 1449 107 0V12 988 806 981 19 0The proposed method was also tested with regular video recordings in comparisonwith the modified version of the method in [36] and the fire detectionmethod described in [87]. The method in [87] uses frequency subband analysis todetect 10 Hz flame flicker, instead of using HMMs to capture the random temporalbehavior in flames. Results for some of the clips are presented in Table 3.3.The clip V17 does not contain any fire, either. However it leads to false alarmsbecause a man with bright fire colored shirt dances in front of the camera to foolthe algorithm. This man would not cause any false alarms if an infrared camerawere used instead of a regular visible range camera.It should also be noted that, the proposed method is computationally moreefficient than [36] because it is mostly based on contour analysis of the brightmoving objects. Average processing time per frame for the proposed method is5 msec as shown in Table 3.3.