Fire Detection Technology Based on Infrared Image Processing

2013 ◽  
Vol 347-350 ◽  
pp. 3426-3430 ◽  
Author(s):  
Xiao Jun Liu
Keyword(s):  
Genetic Algorithm ◽  
Infrared Image ◽  
Fire Detection ◽  
Ccd Camera ◽  
Chain Code ◽  
Light Interference ◽  
Feature Change ◽  
Infrared Image Processing ◽  
Detection Technology ◽  
Background Difference

This paper proposes a method to detect fire by processing the images captured by an CCD camera with infrared filter. First, the flame objects are detected by using two consecutive frames difference and background difference. Using genetic algorithm to optimize the threshold, the image is segmented by using Ostu. The boundary chain code is acquired on the basis of extracting flame contour. Lastly, shape feature, change feature and edge jitter feature are used to judge whether the fire exists. This method suppresses visible light interference. The experiment results show that the algorithm has higher reorganization rate in different environment.

Method of Pointing Measurement Based on Infrared Image Processing for Mid-Infrared Laser

2012 ◽  
Vol 49 (8) ◽  
pp. 081404
Author(s):  
郭汝海 Guo Ruhai ◽  
孙涛 Sun Tao ◽  
王兵 Wang Bing
Keyword(s):  
Image Processing ◽  
Infrared Image ◽  
Infrared Laser ◽  
Mid Infrared ◽  
Infrared Image Processing

scholarly journals Fire detection with infrared images using cascaded neural network

2019 ◽  
Vol 13 ◽  
pp. 174830261989543
Author(s):  
Li Deng ◽  
Qian Chen ◽  
Yuanhua He ◽  
Xiubao Sui ◽  
Quanyi Liu ◽  
...  
Keyword(s):  
Neural Network ◽  
False Alarm ◽  
False Alarm Rate ◽  
Early Stage ◽  
Infrared Camera ◽  
Fire Detection ◽  
Image Texture ◽  
Infrared Images ◽  
Detection Technology ◽  
Civil Aircraft

The existing equipment of civil aircraft cargo fire detection mainly uses photoelectric smoke detectors, which has a high false alarm rate. According to Federal Aviation Agency’s (FAA) statistics, the false alarm rate is as high as 99%. 1 In the cargo of civil aircraft, the traditional photoelectric detection technology cannot effectively distinguish interference particles from smoke particles. Since the video smoke detection technology has proven to be reliable in many large scenarios, a deep learning method of image processing for fire detection is proposed. The proposed convolutional neural network is constructed of front end network and back end network cascaded with the capsule network and the circularity computation for the dynamic infrared fire image texture extraction. In order to accurately identify whether there is a fire in the area and give the kind of burning substances, a series of fuels are selected, such as n-heptane, cyclohexane, and carton for combustion reaction, and infrared camera is used to take infrared images of all fuel combustion. Experimental results show that the proposed method can effectively detect fire at the early stage of fire which is applicable for fire detection in civil aircraft cargoes.

Method for Uncooled Infrared Image Processing

2013 ◽  
Vol 427-429 ◽  
pp. 1948-1951
Author(s):  
Jia Lin Ma ◽  
Xia Zhang
Keyword(s):  
Image Processing ◽  
Infrared Imaging ◽  
Imaging System ◽  
Infrared Detector ◽  
Infrared Image ◽  
National Defense ◽  
Histogram Modification ◽  
Infrared Image Processing ◽  
Manufacturing Techniques ◽  
Uncooled Infrared Imaging

Uncooled infrared imaging system has been increasingly applied in both the national defense and various fields of national economy. Such popularity is attributed to many of its advantages, including small size, light weight, low energy-consumption and superior portability. However, as limited by the structure and the material of infrared detector and the manufacturing techniques, infrared images are plagued with low resolution and poor image quality. This paper mainly studies the uncooled infrared image processing based on the gray levels partition processing, gray levels stretching and histogram modification, it aims to enhance the visual effect of infrared image.

Emissivity Calibration and Research of Infrared Image Processing in the Cutting Temperature Test

2007 ◽  
Vol 10-12 ◽  
pp. 928-933
Author(s):  
Yi Wen Wang ◽  
Huan Rui Hao ◽  
Xian Li Liu ◽  
Cai Xu Yue
Keyword(s):  
Thermal Imaging ◽  
Imaging System ◽  
Cutting Temperature ◽  
Infrared Image ◽  
Edge Extraction ◽  
Imaging Device ◽  
Infrared Image Processing ◽  
System Temperature ◽  
Thermal Imaging System ◽  
Temperature Test

It is by the emissivity of the goal objects and the noise problem of the high temperature images that people are puzzled during the course of the cutting temperature tested by the application of thermal imaging device. By using thermocouples, and getting the comparison of thermocouples and the thermal imaging system temperature, we calibrate object emissivity, handle the image noise by improved median method, carry on the edge extraction of image, obtain the temperature of measured objects, and finally confirm the accuracy of the data got by the thermal imaging device with contact measurement.

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