Automatic flame tracking technique for atrium fire from video images

Smoke control is one of the important aspects in atrium fire. For an efficient smoke control strategy, it is very important to identify the smoke and fire source in a very short period of time. However, traditional methods such as point type detectors are not effective for smoke and fire detection in large space such as atrium. Therefore, video smoke and fire detection systems are proposed. For the development of the system, automatic extraction and tracking of flame are two important problems needed to be solved. Based on entropy theory, region growing and Otsu method, a new automatic integrated algorithm, which is used to track flame from video images, is proposed in this paper. It can successfully identify flames from different environment, different background and in different form. The experimental results show that this integrated algorithm has stronger robustness and wider adaptability. In addition, because of the low computational demand of this algorithm, it is also possible to be used as part of a robust, real-time smoke and fire detection system.