CN102881106B - Dual-detection forest fire identification system through thermal imaging video and identification method thereof - Google Patents
Dual-detection forest fire identification system through thermal imaging video and identification method thereof Download PDFInfo
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- CN102881106B CN102881106B CN201210331547.0A CN201210331547A CN102881106B CN 102881106 B CN102881106 B CN 102881106B CN 201210331547 A CN201210331547 A CN 201210331547A CN 102881106 B CN102881106 B CN 102881106B
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Abstract
The invention discloses a dual-detection forest fire identification system through a thermal imaging video and an identification method thereof. The identification system comprises a thermal imaging camera, a video camera and a processing unit, wherein both the thermal imaging camera and the video camera are in signal communication with the processing unit; the processing unit comprises a thermal imaging analysis unit and a video image analysis unit and calculates angular points of a heat source image and a video image as well as the affine equation between the thermal imaging camera and the video camera through matching the angular points to realize the mapping between a thermal imaging image and the video image; and the position corresponding to an abnormal heat source can be marked on the video image. The dual-detection forest fire identification system through the thermal imaging video and the identification method thereof are simple and practical, and have high identification accuracy and low missing and false report rate. In addition, the forest fire can be detected in low-speed cruising without adopting the fixed-point detection in a common pre-reserved point mode, the blind area of detection can be avoided, and the practicability is good.
Description
Technical field
The present invention relates to forest fires recognition system, be specifically related to a kind of thermal imaging video two mirror forest fires recognition system and recognition methods thereof.
Background technology
At present, in the automatic identification field of fire alarm, often adopt image recognition technology or thermal imaging to realize detection and the warning of fire alarm.Adopt image recognition technology to carry out fire alarm and detect and refer to and utilize monitor video, the feature in video and image according to smog or fire, adopts image processing techniques, a kind of fire alarm detection method of identifying.In order to improve recognition effect, need in advance background image to be learnt.Therefore monitoring preset point can be set conventionally, call monitoring preset point, by the priori of background image, smog and fire alarm be identified.This mode is identified and is had a large amount of blind areas, and coverage rate is not high, meanwhile, uses image recognition technology to carry out recognition correct rate also not high.Glow or time on fire, abnormal rising can occur temperature, therefore also can utilize this feature due to forest, adopt thermal imaging to monitor abnormal high temperature region.But, use thermal imaging to be subject to the interference of the thermals source such as vehicle motor.
Summary of the invention
Goal of the invention: for the deficiencies in the prior art, the object of this invention is to provide the two mirror of a kind of thermal imaging video forest fires recognition system, to improve the accuracy of identification, meet user demand.Another object of the present invention is to provide the recognition methods of the two mirror of a kind of above-mentioned thermal imaging video forest fires recognition system.
Technical scheme: in order to realize foregoing invention object, the technical solution used in the present invention is as follows:
The two mirror of a kind of thermal imaging video forest fires recognition system, comprises thermal imaging camera, video frequency pick-up head and processing unit; Described thermal imaging camera and video frequency pick-up head all carry out signal and communication with processing unit; Described processing unit has judged whether abnormal thermal source by the gray-scale value that detects graphic images, comprises thermal imaging analytic unit and video image analysis unit; Described processing unit calculates the angle point of thermal source image and video image, and by corners Matching and calculate the affine equation between thermal imaging camera and video frequency pick-up head, realize the mapping between graphic images and video image, can on video image, identify the position that abnormal thermal source is corresponding.
Described thermal imaging camera and video frequency pick-up head are all located on The Cloud Terrace.
The setting threshold of the gray-scale value of described graphic images is 600 degrees Celsius of corresponding gray-scale values.
Described thermal imaging analytic unit is for judging forest fires thermal source or vehicle thermal source according to the rhythm of the change of shape situation of thermal source image, light and shade and motion conditions, described video image analysis unit comprises Smoke Detection unit and fiery detecting unit, Smoke Detection unit is for judging the no generation that has smog according to the contrast metric of the extension movement feature of smog and smog, and whether fiery detecting unit has fire to occur for judging according to the variation rule of brightness, motion and light and shade.
The recognition methods of the two mirror of thermal imaging video forest fires recognition system: utilize the low speed inspection function of The Cloud Terrace to patrol and examine the forest zone of monitoring; Processing unit has judged whether abnormal thermal source by the gray-scale value that detects graphic images; When the temperature showing in graphic images exceedes 600 degrees Celsius, and region area is while being greater than 10 pixels, exits patrol mode, at thermograph image field, suspicious thermal source is analyzed, judge that suspicious thermal source is the probability of fire alarm, in video image territory, image is analyzed, judge the type of fire alarm.
The recognition methods of the two mirror of thermal imaging video forest fires recognition system, is specially:
1) image is processed and is completed by thermal imaging analytic unit and video image analysis unit;
2) before and after thermal imaging analytic unit, interval gathers multiple image, and extracts respectively the abnormal area of each two field picture;
3) judge in each frame mainly according to the change of shape situation of thermal source image, calculate the situation of change of the average gray value of each two field picture abnormal area by calculating the shape descriptor of each two field picture abnormal area, calculate the motion conditions of the abnormal thermal source of position judgment of the center of gravity of each two field picture abnormal area;
4) calculate the angle point of thermal imaging and video pictures, and mate, determine the mapping relations of pixel and video image pixel in graphic images;
5) video image is analyzed, realized the segmentation to type of alarm.
In step 3), when detection, the characteristics such as the maximum range value that the undulating quantity of the area of each frame abnormal area, front and back frame gray scale peak value, front and back frame abnormal area centre of gravity place are changed, as the input value of a support vector machine, are classified to abnormal area, and whether differentiate it is fire alarm.
In step 4), obtaining after the mapping relations of pixel and video image pixel in graphic images, user is on computers when playing image, and expression abnormal high temperature region, is convenient to staff and makes accurate judgement.
In step 5), video image analysis is specially: obtaining after the mapping relations of pixel and video image pixel in graphic images, the image of correspondence position in video image of the abnormal area in thermal imaging is analyzed; If the mean picture brightness value in this region is greater than the threshold value of setting, for naked light is reported to the police; Image to region top carries out optical flow analysis, if the image of this top, region there is optical flow field, and have the area image contrast of light stream to be less than adjacent domain, be pyrotechnics warning; Other situations are the warning of glowing.
The two mirror of this thermal imaging video forest fires recognition system, in the time of work, arranges The Cloud Terrace to work in the mode of patrolling and examining, and processing unit detects graphic images gray-scale value and judged whether abnormal thermal source.If note abnormalities, thermal source stops patrolling and examining, by graphic images, video image are carried out to image processing, and further judgement.Image is processed and is completed by thermal imaging analytic unit and video image analysis unit.Thermal imaging analytic unit is mainly the interference of the thermal source such as forest fires or vehicle according to the change of shape situation of thermal source image, the rhythm of light and shade, motion determination.Video image analysis unit is mainly divided into two large classes: Smoke Detection unit and fiery detecting unit.Smoke Detection unit is mainly the extension movement feature according to smog, and the contrast metric of smog etc. judges whether the generation of smog.Fire detecting unit is mainly to judge according to the variation rule of brightness, motion and light and shade.
Beneficial effect: compared with prior art, thermal imaging video of the present invention two mirror forest fires recognition system and recognition methods thereof, simple possible, the accuracy of identification is high, fails to report, rate of false alarm is low, can realize at the low speed middle detection forest fires that cruise, but not adopt common preset point mode to fix a point to detect, stop to detect blind area, there is good practicality, can produce good economic benefit and social effect.
Accompanying drawing explanation
Fig. 1 is the schematic diagram of the two mirror of thermal imaging video forest fires recognition system;
Fig. 2 is forest fires identification main flow chart;
Fig. 3 is thermal source graphical analysis process flow diagram.
Embodiment
Below in conjunction with accompanying drawing, the present invention is further illustrated.
As shown in Figure 1, the two mirror of thermal imaging video forest fires recognition system, major part comprises thermal imaging camera, video frequency pick-up head and processing unit, and thermal imaging camera and video frequency pick-up head all reach processing unit by image, and thermal imaging camera and video frequency pick-up head are all located on The Cloud Terrace.Processing unit comprises thermal imaging analytic unit and video image analysis unit; Thermal imaging analytic unit is for judging forest fires thermal source or vehicle thermal source according to the rhythm of the change of shape situation of thermal source image, light and shade and motion conditions; Video image analysis unit comprises Smoke Detection unit and fiery detecting unit, Smoke Detection unit is for judging the no generation that has smog according to the contrast metric of the extension movement feature of smog and smog, and whether fiery detecting unit has fire to occur for judging according to the variation rule of brightness, motion and light and shade.There is linear relationship in gray scale and the temperature of thermal imaging camera, can pass through in advance the calibration to thermal imaging camera, obtains 600 degrees Celsius of corresponding gray-scale values; In the time that the temperature value of thermal imaging camera mensuration is greater than 600 degrees Celsius, be judged as abnormal thermal source.
As shown in Figure 2, when system works, utilize the low speed inspection function of supervisory system to patrol and examine the forest zone of monitoring.This processing unit has judged whether abnormal thermal source by the gray-scale value that detects graphic images.When the temperature showing in graphic images exceedes 600 degrees Celsius, and when region area is greater than 10 pixels, exit patrol mode, at thermograph image field, suspicious thermal source is analyzed, judge that suspicious thermal source is the probability of fire alarm, in video image territory, image is analyzed, judge the type of fire alarm, as shown in Figure 3, be specially:
1) image is processed and is completed by thermal imaging analytic unit and video image analysis unit.
2) before and after thermal imaging analytic unit, interval gathers multiple image, and extracts respectively the abnormal area of each two field picture.
3) judge in each frame mainly according to the change of shape situation of thermal source image, calculate the situation of change of the average gray value of each two field picture abnormal area by calculating the shape descriptor of each two field picture abnormal area, calculate the motion conditions of the abnormal thermal source of position judgment of the center of gravity of each two field picture abnormal area.The feature of fire is that its shape is not often fixed, its temperature (gray-scale value that heat picture is corresponding) has obvious fluctuation, the position of abnormal area center of gravity not to have variation fast.And its shape of feature of the abnormal thermal source such as vehicle motor is fixed, its temperature does not have obvious fluctuation, between main combustion period, may there is large variation in the centre of gravity place of heat source region.When detection, the characteristics such as the maximum range value that the undulating quantity of the area of each frame abnormal area, front and back frame gray scale peak value, front and back frame abnormal area centre of gravity place are changed are as the input value of a support vector machine, whether abnormal area, differentiating it is fire alarm if being classified.
4) calculate the angle point of thermal imaging and video pictures, and mate, determine the mapping relations of pixel and video image pixel in graphic images.
5) video image is analyzed, realized the segmentation to type of alarm.Obtaining after the mapping relations of pixel and video image pixel in graphic images, the image of correspondence position in video image of the abnormal area in thermal imaging is analyzed.If the mean picture brightness value in this region is greater than the threshold value of setting, for naked light is reported to the police; Image to region top carries out optical flow analysis, if the image of this top, region there is optical flow field, and have the area image contrast of light stream to be less than adjacent domain, be pyrotechnics warning; Other situations are the warning of glowing.
Obtaining after the mapping relations of pixel and video image pixel in graphic images, user is on computers when playing image, and expression abnormal high temperature region, is convenient to staff and makes accurate judgement.
Claims (4)
1. the two mirror of a thermal imaging video forest fires recognition system, comprises thermal imaging camera, video frequency pick-up head and processing unit; Described thermal imaging camera and video frequency pick-up head all carry out signal and communication with processing unit; Described processing unit has judged whether abnormal thermal source by the gray-scale value that detects graphic images, comprises thermal imaging analytic unit and video image analysis unit; It is characterized in that: described processing unit calculates the angle point of thermal source image and video image, and by corners Matching and calculate the affine equation between thermal imaging camera and video frequency pick-up head, realize the mapping between graphic images and video image, can on video image, identify the position that abnormal thermal source is corresponding.
2. the two mirror of thermal imaging video according to claim 1 forest fires recognition system, is characterized in that: described thermal imaging camera and video frequency pick-up head are all located on The Cloud Terrace.
3. the two mirror of thermal imaging video according to claim 1 forest fires recognition system, is characterized in that: the setting threshold of the gray-scale value of described graphic images is 600 degrees Celsius of corresponding gray-scale values.
4. the two mirror of thermal imaging video according to claim 1 forest fires recognition system, it is characterized in that: described thermal imaging analytic unit is used for according to the change of shape situation of thermal source image, the rhythm of light and shade and motion conditions are judged forest fires thermal source or vehicle thermal source, described video image analysis unit comprises Smoke Detection unit and fiery detecting unit, Smoke Detection unit is for judging the no generation that has smog according to the contrast metric of the extension movement feature of smog and smog, fire detecting unit is used for according to brightness, whether the variation rule of motion and light and shade is judged has fire to occur.
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| CN117671914B (en) * | 2023-10-26 | 2024-06-04 | 广州成至智能机器科技有限公司 | Unmanned aerial vehicle multi-sensor forest fire identification method, device and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101175202A (en) * | 2007-10-31 | 2008-05-07 | 天津市亚安科技电子有限公司 | Video monitoring apparatus based on double optical band |
| CN101673448A (en) * | 2009-09-30 | 2010-03-17 | 青岛科恩锐通信息技术有限公司 | Method and system for detecting forest fire |
| CN101833838A (en) * | 2010-05-27 | 2010-09-15 | 王巍 | Large-range fire disaster analyzing and early warning system |
| CN102280005A (en) * | 2011-06-09 | 2011-12-14 | 广州飒特电力红外技术有限公司 | Early warning system for fire prevention of forest based on infrared thermal imaging technology and method |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050162515A1 (en) * | 2000-10-24 | 2005-07-28 | Objectvideo, Inc. | Video surveillance system |
| CA2392410A1 (en) * | 2002-07-04 | 2004-01-04 | Dan Keith Andersen | Method of aerial monitoring of forests |
| US20050104771A1 (en) * | 2003-09-17 | 2005-05-19 | Spectrotech, Inc. | Airborne imaging spectrometry system and method |
| US8912978B2 (en) * | 2009-04-02 | 2014-12-16 | GM Global Technology Operations LLC | Dynamic vehicle system information on full windshield head-up display |
-
2012
- 2012-09-10 CN CN201210331547.0A patent/CN102881106B/en active Active
- 2012-09-10 CN CN201410004366.6A patent/CN103761826B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101175202A (en) * | 2007-10-31 | 2008-05-07 | 天津市亚安科技电子有限公司 | Video monitoring apparatus based on double optical band |
| CN101673448A (en) * | 2009-09-30 | 2010-03-17 | 青岛科恩锐通信息技术有限公司 | Method and system for detecting forest fire |
| CN101833838A (en) * | 2010-05-27 | 2010-09-15 | 王巍 | Large-range fire disaster analyzing and early warning system |
| CN102280005A (en) * | 2011-06-09 | 2011-12-14 | 广州飒特电力红外技术有限公司 | Early warning system for fire prevention of forest based on infrared thermal imaging technology and method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111973914A (en) * | 2020-08-13 | 2020-11-24 | 深圳市朗驰欣创科技股份有限公司 | Transformer substation wheel type inspection robot with automatic fire extinguishing function |
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