Applications of fire detection as a tool have increased to due to the frequent occurrence of extended fires with consequences on human health and security. Fires represent a constant threat to ecological systems, infrastructure and human lives. Past has witnessed multiple instances of fires. With the faster and faster urbanization process, more and more high-rise buildings appear around us. This also can make the frequency of fire increase and bring great losses to people’s lives and property. In areas where fire would pose an unreasonable threat to property, human life or important biological communities, efforts should be made to reduce dangers of fire. As the damage caused by fires is so tremendous that the early fire detection is becoming more and more important . Recently, some fire detectors have been used in many places, they used the smoke, temperature and photosensitive characteristics to detect fires. But they are too worse to meet the needs in a large space, harsh environment or the outdoor environment etc. With these types of techniques, not only can fires be detected, but also the approximate range to which a fire can spread may be determined. This project attempts to devise an algorithm which could prove as a holistic approach to fire detection using video surveillance. This research works around fire color and also focuses more on other peculiar characteristics of fire that could prove more efficient in its detection. As this research project uses grayscale video processing devices, it could be more convenient to develop an algorithm which will determine the self-luminous feature of fire. Variance in the brightness, which could be observed as flickering by the human eye can also be a vital parameter to enhance the efficiency of fire detection. Inclusion of the randomness feature of fire can also prove beneficial in improving the detection rate. Therefore, the fundamental problem of this work is to devise a holistic approach to detect fire using image processing . This research project uses grayscale video processing devices, which is more convenient to develop an algorithm to determine the self-luminous feature of fire. Variance in the brightness, which can be observed as flickering by the human eye can also be a vital parameter to enhance the efficiency of fire detection. As fire is shapeless, randomness of edges of fire can be another feature to improve the rate of detection. The central objective of this research is to design and implement fire-detection algorithms using HSV model.
Software And Hardware