Flame detection algorithms based on temporal-spatial visual saliency

Introduced the idea of visual saliency in computer vision, the model of flame detection is proposed based on the temporal-spatial visual saliency. Firstly, the Lab color space is obtained, then three channels (L, a, b) are segmented with threshold and filtered in Gaussian. The grayscale integral pro...

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Bibliographic Details
Published in2015 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC) pp. 1 - 5
Main Authors Wu Dongmei, Yang Juanli, Li Baiping, Liu Xiaopei
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2015
Subjects
Accuracy
Brightness
brightness saliency
Dispersion
Fires
FROI
Gray-scale
Image color analysis
Lab color space
Visualization
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Summary:Introduced the idea of visual saliency in computer vision, the model of flame detection is proposed based on the temporal-spatial visual saliency. Firstly, the Lab color space is obtained, then three channels (L, a, b) are segmented with threshold and filtered in Gaussian. The grayscale integral projection method is used to extract the brightness saliency of flame. Secondly, the flame region of interest (FROI) is acquired by frame difference of flame color, and the region is determined through dispersion and cumulative movement. Finally, the integral saliency map of the current frame is formed by compositing color, brightness and motion saliency. Experiments show that the proposed model achieves better performance on flame detection than others under different video scenes.
ISBN:1479989185
9781479989188
DOI:10.1109/ICSPCC.2015.7338834