Fire Detection Algorithms Using Multimodal ... - Bilkent University

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CHAPTER 2. FLAME DETECTION IN VISIBLE RANGE VIDEO 19{ 1, 1, 1 }, respectively, as shown in Fig. 2.3. The filter bank produces wavelet4 2 4subsignals d n (x) and e n (x). If there is high frequency activity at pixel locationx, high-band subsignals d and e get non-zero values. However, in a stationarypixel, the values of these two subsignals should be equal to zero or very close tozero because of high-pass filters used in subband analysis. If the pixel is part ofa flame boundary at some time (see Fig. 2.4), then there will be several spikesin one second due to transitions from background colors to flame colors and viceversa. If there is an ordinary fire-colored moving object going through pixel atlocation x, then there will be a single spike in one of these wavelet subsignalsbecause of the transition from the background pixel to the object pixel as shownin Fig. 2.5. The number of zero crossings of the subband signals d n and e n in afew seconds can be used to discriminate between a flame pixel and an ordinaryfire colored object pixel. If this number is above some threshold, then an alarmcan be issued for this pixel.The temporal history of the red channel of a pixel at location x = (111, 34)which is part of a flame, and the corresponding wavelet signals are shown inFig. 2.4. A flicker in the red channel values of this flame pixel is obvious from thefigure. The pixel is part of a flame for image frames with time steps n=1, 2, 3, 19,23, 24, 41 and 50. It becomes part of the background for n=12,...,17, 20, 21, 26,27, 31,...,39, 45, 52,..., and 60. Wavelet domain subsignals d n and e n reveal thefluctuations of the pixel at location x = (111, 34) with several zero crossings. Dueto a down-sampling operation during wavelet computation, the length of waveletsignals are halved after each stage of subband filtering. As a result, the valueof a sample in a subband signal corresponds to several samples in the originalsignal, e.g., the value of d 5 (111, 34) corresponds to the values of Ĩ10(111, 34) andĨ 11 (111, 34), and the value of e 4 (111, 34) corresponds to the values of Ĩ12(111, 34),Ĩ 13 (111, 34), Ĩ14(111, 34) and Ĩ15(111, 34), in the original signal.The temporal history of the red channel of a pixel at location x = (18, 34),which is part of a fire colored object, and the corresponding wavelet signals areshown in Fig. 2.5. As shown in this figure, neither the original nor the waveletsignals exhibit oscillatory behavior. The pixel is part of a white-colored backgroundfor n=1, 2, and 3, becomes part of a fire colored object for n=4, 5, 6, 7,
CHAPTER 2. FLAME DETECTION IN VISIBLE RANGE VIDEO 20Figure 2.4: (a) Temporal variation of image pixel at location x = (111, 34), Ĩn(x).The pixel at x = (111, 34) is part of a flame for image frames I(x, n), n=1, 2, 3,19, 23, 24, 41 and 50. It becomes part of the background for n = 12,..., 17, 20,21, 26, 27, 31,..., 39, 45, 52,..., and 60. Wavelet domain subsignals (b) d n and (c)e n reveal the fluctuations of the pixel at location x = (111, 34).
Page 3 and 4: I certify that I have read this the
Page 7 and 8: viiiçin de işaret işleme yöntem
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Page 20 and 21: Chapter 1IntroductionDynamic textur
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CHAPTER 5. FLAME DETECTION USING PI
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Chapter 7Conclusion and Future Work
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CHAPTER 7. CONCLUSION AND FUTURE WO
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Bibliography[1] B. Albers and A. Ag
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BIBLIOGRAPHY 112[18] D. Chetverikov
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BIBLIOGRAPHY 114[38] G. Healey, D.
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BIBLIOGRAPHY 116[56] U. Niesen, D.
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BIBLIOGRAPHY 118[77] C. Stauffer an
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