Algorithms for clustering data
Algorithms for clustering data
ACM Transactions on Graphics (TOG)
Pattern Recognition Letters
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Computer vision based method for real-time fire and flame detection
Pattern Recognition Letters
Fire detection using statistical color model in video sequences
Journal of Visual Communication and Image Representation
A target-based color space for sea target detection
Applied Intelligence
Hi-index | 0.00 |
New generation vessels are equipped with fire detecting sensors; however, fire may not immediately be detected if it is far away from the sensors. The fire process therefore cannot be recorded. A video-based fire alarm system is developed to overcome the drawbacks of traditional fire detection equipment. This paper presents a video-based flame and smoke detection method for vessels. For flame detection, the dominant flame color lookup table (DFCLT) is created by using the fuzzy c-means clustering algorithm. The changed video frames are automatically selected and the changed regions deduced from these frames. An elementary, medium, or emergency flame alarm is then triggered by comparing the pixels of changed regions with the DFCLT. The changed video frames are automatically selected for smoke detection. The changed regions are deduced from these frames. If the shape of the changed region conforms to the characteristic which the top area is wider than the bottom area, a dangerous smoke alarm is sounded. The experimental results show that the proposed fire detection approach can detect dangerous flames and smoke, effectively and efficiently.