scholarly journals DeepFireNet: A real-time video fire detection method based on multi-feature fusion

2020 ◽  
Vol 17 (6) ◽  
pp. 7804-7818
Author(s):  
Bin Zhang ◽  
◽  
Linkun Sun ◽  
Yingjie Song ◽  
Weiping Shao ◽  
...  
Keyword(s):  
Real Time ◽  
Detection Method ◽  
Feature Fusion ◽  
Fire Detection

scholarly journals Erratum to: Real-time, large-scale duplicate image detection method based on multi-feature fusion

2017 ◽  
Vol 16 (5) ◽  
pp. 1881-1881
Author(s):  
Ming Chen ◽  
Yuhua Li ◽  
Zhifeng Zhang ◽  
Ching-Hsien Hsu ◽  
Shangguang Wang
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Detection Method ◽  
Feature Fusion ◽  
Image Detection ◽  
Duplicate Image Detection

Real-time, large-scale duplicate image detection method based on multi-feature fusion

2016 ◽  
Vol 13 (3) ◽  
pp. 557-570 ◽  
Author(s):  
Ming Chen ◽  
Yuhua Li ◽  
Zhifeng Zhang ◽  
Ching-Hsien Hsu ◽  
Shangguang Wang
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Detection Method ◽  
Feature Fusion ◽  
Image Detection ◽  
Duplicate Image Detection

scholarly journals A Real-Time Fire Detection Method from Video with Multifeature Fusion

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Faming Gong ◽  
Chuantao Li ◽  
Wenjuan Gong ◽  
Xin Li ◽  
Xiangbing Yuan ◽  
...  
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Real Time ◽  
Detection Method ◽  
Computation Time ◽  
Fire Detection ◽  
Support Vector ◽  
Fire Monitoring ◽  
Spatiotemporal Information ◽  
Flame Region

The threat to people’s lives and property posed by fires has become increasingly serious. To address the problem of a high false alarm rate in traditional fire detection, an innovative detection method based on multifeature fusion of flame is proposed. First, we combined the motion detection and color detection of the flame as the fire preprocessing stage. This method saves a lot of computation time in screening the fire candidate pixels. Second, although the flame is irregular, it has a certain similarity in the sequence of the image. According to this feature, a novel algorithm of flame centroid stabilization based on spatiotemporal relation is proposed, and we calculated the centroid of the flame region of each frame of the image and added the temporal information to obtain the spatiotemporal information of the flame centroid. Then, we extracted features including spatial variability, shape variability, and area variability of the flame to improve the accuracy of recognition. Finally, we used support vector machine for training, completed the analysis of candidate fire images, and achieved automatic fire monitoring. Experimental results showed that the proposed method could improve the accuracy and reduce the false alarm rate compared with a state-of-the-art technique. The method can be applied to real-time camera monitoring systems, such as home security, forest fire alarms, and commercial monitoring.

Fire Detection Technologies Based on Video Image

2013 ◽  
Vol 659 ◽  
pp. 134-138
Author(s):  
Meng Xin Li ◽  
Wei Jing Xu ◽  
Ying Zhang ◽  
Jing Hou
Keyword(s):  
Signal Detection ◽  
Real Time ◽  
Monitoring System ◽  
Error Rate ◽  
Detection Method ◽  
Fire Detection ◽  
Fire Frequency ◽  
Large Impact ◽  
The Real ◽  
Detection Technologies

Because of high fire frequency and huge losses, the research of fire signal detection in the monitoring system is an important task in the fire-preventing field. The fire signal detection method based on vision can overcome the shortcomings that exist in some traditional methods i.e. it can surmount the large impact on environmental interference factors, such as temperature, photographic and smoke of environment. With many researcher’s results, it shows clearly that the error rate of flame recognition is low, and also the real-time ability and the anti-disturbance ability are very good.

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