Title
Flame Detection Using Generic Color Model And Improved Block-Based Pca In Active Infrared Camera
Abstract
In this paper, we proposed an all-weather flame detection algorithm which could make full use of active infrared cameras presently installed in many public places for surveillance purposes. Firstly, according to the different spectral imaging results in day and night, we propose a video type classification algorithm (VTCA) via imaging clues. VTCA could help us select different flame visual features in color image and infrared image. Secondly, we use a generic YCbCr-color-space-based chrominance model to extract regions of interest (ROI) of flame. Thirdly, two flame dynamic features are used to verify the candidate ROIs, which are common flame flicker feature and an improved block-based PCA in consecutive frames. The experimental results show that the proposed flame detection model has been successfully applied to various situations, including day and night, indoor and outdoor on our test video datasets, and it gives a better performance compared with other state-of-the-art methods.
Year
DOI
Venue
2018
10.1142/S0218001418500143
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
Active infrared camera, video-type classification, generic color model, dynamic flame feature
Flicker,Computer vision,Infrared image,Spectral imaging,Pattern recognition,Chrominance,Flame detection,Artificial intelligence,Color model,Infrared,Mathematics,Color image
Journal
Volume
Issue
ISSN
32
5
0218-0014
Citations 
PageRank 
References 
0
0.34
8
Authors
4
Name
Order
Citations
PageRank
Qian Zhao1215.80
Fengdong Sun251.89
Wenhui Li38328.12
Peixun Liu483.73