Transmission: a new feature for computer vision based smoke detection
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part I
Detection and classification of nano-scale particles with image histograms
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
Digital Signal Processing
Adaptive estimation of visual smoke detection parameters based on spatial data and fire risk index
Computer Vision and Image Understanding
| Hi-index | 0.00 |
For open spaces, this paper proposes a novel method for automatic fire smoke detection based on image visual features. The greatest characteristic of the method is that both static and dynamic features of fire smoke are investigated. And the basic strategy is that we extract features of the moving target including growth, disorder, frequent flicker in boundaries, self- similarity and local wavelet energy as a joint feature vector which will be normalized, and then a BP artificial neural network is trained to recognize fire smoke. Experimental results show that this method can achieve early detection of fire accident with high accuracy and stronger anti-jamming ability.