基于视频图像序列处理的火焰侦测计算机科学与技术专业论文.docx

哈尔滨工业大学工学硕士学位论文 哈尔滨工业大学工学硕士学位论文 II II Abstract The early and real-time detection of fire flames based on video image sequence processing is mainly through the analysis of the video image sequence in the surveillance cameras, utilizing image processing technologies and changes in the characteristics of flame image in a continuous sequence. Comparing with the traditional fire detection technologies, this method could detect more information, such as the location, the size and the growth ratio of flames, etc. And it can be applied to multi-dimensions. In this paper, a thorough research has been done on the algorithms of image enhancement, noise filtering, edge detection, frequency detection and their applications in the fire video image processing. On the base of integration of algorithm above, a three-stage-based intelligent fire detection method was proposed. First stage is also known as the flame image segmentation stage. First, we analyzed and compared the various background updating algorithms and improved the median background updating algorithm that behaves robust. We optimized the calculation speed and significantly reduced the mean time complexity. Second, after analyzing a variety of statistical models on the color of fire flames and comparing the results, we used a compromise solution: integrating both RGB and HIS color statistical models, filtering and optimizing the extracted flame region of last step. Second stage is to detect other characteristics of the flame. First, we detected the flame shape. After comparing and analyzing the state-of-the-art detection methods, we proposed to use canny edge detection algorithm to extract the edges and then to calculate the perimeter and area ratio to make the classification. Second, we detected the flame frequency. We approximated to estimate the jittery frequency by the changes of flame edges. Third, by comparing the two frames between the changes of the S channel histogram to filter objects similar to flames, we de