CN102881106A - 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
- Publication number
- CN102881106A CN102881106A CN2012103315470A CN201210331547A CN102881106A CN 102881106 A CN102881106 A CN 102881106A CN 2012103315470 A CN2012103315470 A CN 2012103315470A CN 201210331547 A CN201210331547 A CN 201210331547A CN 102881106 A CN102881106 A CN 102881106A
- Authority
- CN
- China
- Prior art keywords
- thermal imaging
- video
- image
- video image
- mirror
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture
- Y02A40/28—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture specially adapted for farming
Landscapes
- Image Analysis (AREA)
- Fire-Detection Mechanisms (AREA)
- Alarm Systems (AREA)
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 the 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 the fire alarm detection and refer to 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 usually the monitoring preset point can be set, call the 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, and simultaneously, it is not high to use image recognition technology to carry out recognition correct rate yet.Because forest is glowed or when on fire, temperature can raise by abnormal, therefore also can utilize these characteristics, adopts thermal imaging that the abnormal high temperature zone is monitored.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 purpose 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, satisfy user demand.Another object of the present invention provides 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 the foregoing invention purpose, 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 unusual 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 affine equation between thermal imaging camera and the video frequency pick-up head, realize the mapping between graphic images and the video image, can be in position corresponding to the video image unusual thermal source of sign.
Described thermal imaging camera and video frequency pick-up head all are located on the The Cloud Terrace.
The setting threshold of the gray-scale value of described graphic images is the gray-scale value of 600 degrees centigrade of correspondences.
Described thermal imaging analytic unit is used for judging forest fires thermal source or vehicle thermal source according to the change of shape situation of thermal source image, rhythm and the motion conditions of light and shade, described video image analysis unit comprises Smoke Detection unit and fiery detecting unit, the Smoke Detection unit is used for judging the no generation that smog is arranged according to the extension movement feature of smog and the contrast metric of smog, and fiery detecting unit is used for judging according to the variation rule of brightness, motion and light and shade whether the fire generation is arranged.
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 that the forest zone of monitoring is patrolled and examined; Processing unit has judged whether unusual thermal source by the gray-scale value that detects graphic images; The temperature that shows in graphic images surpasses 600 degrees centigrade, and region area withdraws from patrol mode during greater than 10 pixels, at the thermograph image field suspicious thermal source is analyzed, judge that suspicious thermal source is the probability of fire alarm, in the 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 finished by thermal imaging analytic unit and video image analysis unit;
2) interval gathers multiple image before and after the thermal imaging analytic unit, and extracts respectively the abnormal area of each two field picture;
3) judge in each frame mainly change of shape situation according to the thermal source image, calculate the situation of change of the average gray value of each two field picture abnormal area by the shape descriptor that calculates each two field picture abnormal area, calculate the motion conditions of the unusual 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 the graphic images;
5) video image is analyzed, realized the segmentation to type of alarm.
In the step 3), during detection, with the undulating quantity of the area of each frame abnormal area, front and back frame gray scale peak value, characteristics such as maximum range value that front and back frame abnormal area centre of gravity place the changes input value as a support vector machine, abnormal area is classified, differentiate its whether fire alarm.
In the step 4), in obtaining graphic images after the mapping relations of pixel and video image pixel, during playing image, the expression abnormal high temperature is regional, is convenient to the staff and makes accurate judgement on computers for the user.
In the step 5), video image analysis is specially: in obtaining graphic images, after the mapping relations of pixel and video image pixel, the image of correspondence position in video image of the abnormal area in the thermal imaging is analyzed; If mean picture brightness value that should the zone greater than the threshold value of setting, then is the naked light warning; Image to zone top carries out optical flow analysis, if image that should the top, zone have an optical flow field, and the area image contrast that light stream is arranged then is the pyrotechnics warning less than adjacent domain; Other situations are the warning of glowing.
The two mirror of this thermal imaging video forest fires recognition system when work, arranges The Cloud Terrace to work in the mode of patrolling and examining, and processing unit detects the graphic images gray-scale value and judged whether unusual thermal source.Thermal source then stops to patrol and examine if note abnormalities, and processes by graphic images, video image being carried out image, further judges.Image is processed and is finished by thermal imaging analytic unit and video image analysis unit.The thermal imaging analytic unit is the interference of the thermals source such as forest fires or vehicle according to change of shape situation, the rhythm of light and shade, the motion determination of thermal source image mainly.The video image analysis unit mainly is divided into two large classes: Smoke Detection unit and fiery detecting unit.The Smoke Detection unit mainly is the extension movement feature according to smog, and the contrast metric of smog etc. judges whether the generation of smog.The fire detecting unit mainly is 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 be implemented in 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 the blind area, have good practicality, can produce good economic benefit and social effect.
Description of drawings
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
The present invention is further illustrated below in conjunction with accompanying drawing.
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 with image, and thermal imaging camera and video frequency pick-up head all are located on the The Cloud Terrace.Processing unit comprises thermal imaging analytic unit and video image analysis unit; The thermal imaging analytic unit is used for judging forest fires thermal source or vehicle thermal source according to the change of shape situation of thermal source image, rhythm and the motion conditions of light and shade; The video image analysis unit comprises Smoke Detection unit and fiery detecting unit, the Smoke Detection unit is used for judging the no generation that smog is arranged according to the extension movement feature of smog and the contrast metric of smog, and fiery detecting unit is used for judging according to the variation rule of brightness, motion and light and shade whether the fire generation is arranged.There are linear relationship in gray scale and the temperature of thermal imaging camera, can in advance by the calibration to the thermal imaging camera, obtain the gray-scale value of 600 degrees centigrade of correspondences; The temperature value of measuring when the thermal imaging camera namely has been judged as unusual thermal source during greater than 600 degrees centigrade.
As shown in Figure 2, during system works, utilize the low speed inspection function of supervisory system that the forest zone of monitoring is patrolled and examined.This processing unit has judged whether unusual thermal source by the gray-scale value that detects graphic images.The temperature that shows in graphic images is above 600 degrees centigrade, and region area is during greater than 10 pixels, withdraw from patrol mode, at the thermograph image field suspicious thermal source is analyzed, judge that suspicious thermal source is the probability of fire alarm, in the 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 finished by thermal imaging analytic unit and video image analysis unit.
2) interval gathers multiple image before and after the thermal imaging analytic unit, and extracts respectively the abnormal area of each two field picture.
3) judge in each frame mainly change of shape situation according to the thermal source image, calculate the situation of change of the average gray value of each two field picture abnormal area by the shape descriptor that calculates each two field picture abnormal area, calculate the motion conditions of the unusual 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 fast variation.And its shape of feature of the unusual thermal source such as vehicle motor is fixed, its temperature does not have obvious fluctuation, and between main combustion period, large variation may occur the centre of gravity place of heat source region.During detection, with the undulating quantity of the area of each frame abnormal area, front and back frame gray scale peak value, characteristics such as maximum range value that front and back frame abnormal area centre of gravity place the changes input value as a support vector machine, abnormal area is classified, differentiate its whether fire alarm.
4) calculate the angle point of thermal imaging and video pictures, and mate, determine the mapping relations of pixel and video image pixel in the graphic images.
5) video image is analyzed, realized the segmentation to type of alarm.In obtaining graphic images, after the mapping relations of pixel and video image pixel, the image of correspondence position in video image of the abnormal area in the thermal imaging is analyzed.If mean picture brightness value that should the zone greater than the threshold value of setting, then is the naked light warning; Image to zone top carries out optical flow analysis, if image that should the top, zone have an optical flow field, and the area image contrast that light stream is arranged then is the pyrotechnics warning less than adjacent domain; Other situations are the warning of glowing.
In obtaining graphic images after the mapping relations of pixel and video image pixel, during playing image, the expression abnormal high temperature is regional, is convenient to the staff and makes accurate judgement on computers for the user.
Claims (9)
1. the two mirror of a thermal imaging video forest fires recognition system is characterized in that: comprise 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 unusual 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 affine equation between thermal imaging camera and the video frequency pick-up head, realize the mapping between graphic images and the video image, can be in position corresponding to the video image unusual thermal source of sign.
2. the two mirror of thermal imaging video according to claim 1 forest fires recognition systems, it is characterized in that: described thermal imaging camera and video frequency pick-up head all are located on the The Cloud Terrace.
3. the two mirror of thermal imaging video according to claim 1 forest fires recognition systems, it is characterized in that: the setting threshold of the gray-scale value of described graphic images is the gray-scale value of 600 degrees centigrade of correspondences.
4. the two mirror of thermal imaging video according to claim 1 forest fires recognition systems, it is characterized in that: described thermal imaging analytic unit is used for the change of shape situation according to the 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, the Smoke Detection unit is used for judging the no generation that smog is arranged according to the extension movement feature of smog and the contrast metric of smog, and fiery detecting unit is used for according to brightness, whether the variation rule of motion and light and shade is judged has fire to occur.
5. the recognition methods of the two mirror of thermal imaging video claimed in claim 1 forest fires recognition system is characterized in that: utilize the low speed inspection function of The Cloud Terrace that the forest zone of monitoring is patrolled and examined; Processing unit has judged whether unusual thermal source by the gray-scale value that detects graphic images; The temperature that shows in graphic images surpasses 600 degrees centigrade, and region area withdraws from patrol mode during greater than 10 pixels, at the thermograph image field suspicious thermal source is analyzed, judge that suspicious thermal source is the probability of fire alarm, in the video image territory, image is analyzed, judge the type of fire alarm.
6. the recognition methods of the two mirror of thermal imaging video according to claim 5 forest fires recognition system is characterized in that, is specially:
1) image is processed and is finished by thermal imaging analytic unit and video image analysis unit;
2) interval gathers multiple image before and after the thermal imaging analytic unit, and extracts respectively the abnormal area of each two field picture;
3) judge in each frame mainly change of shape situation according to the thermal source image, calculate the situation of change of the average gray value of each two field picture abnormal area by the shape descriptor that calculates each two field picture abnormal area, calculate the motion conditions of the unusual 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 the graphic images;
5) video image is analyzed, realized the segmentation to type of alarm.
7. the recognition methods of the two mirror of thermal imaging video according to claim 6 forest fires recognition system, it is characterized in that, in the step 3), during detection, with the undulating quantity of the area of each frame abnormal area, front and back frame gray scale peak value, characteristics such as maximum range value that front and back frame abnormal area centre of gravity place the changes input value as a support vector machine, abnormal area is classified, differentiate its whether fire alarm.
8. the recognition methods of the two mirror of thermal imaging video according to claim 6 forest fires recognition system, it is characterized in that, in the step 4), in obtaining graphic images after the mapping relations of pixel and video image pixel, the user is on computers during playing image, expression abnormal high temperature zone is convenient to the staff and is made accurate judgement.
9. the recognition methods of the two mirror of thermal imaging video according to claim 6 forest fires recognition system, it is characterized in that, in the step 5), video image analysis is specially: in obtaining graphic images, after the mapping relations of pixel and video image pixel, the image of correspondence position in video image of the abnormal area in the thermal imaging is analyzed; If mean picture brightness value that should the zone greater than the threshold value of setting, then is the naked light warning; Image to zone top carries out optical flow analysis, if image that should the top, zone have an optical flow field, and the area image contrast that light stream is arranged then is the pyrotechnics warning less than adjacent domain; Other situations are the warning of glowing.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210331547.0A CN102881106B (en) | 2012-09-10 | 2012-09-10 | Dual-detection forest fire identification system through thermal imaging video and identification method thereof |
| CN201410004366.6A CN103761826B (en) | 2012-09-10 | 2012-09-10 | The recognition methods of a kind of thermal imaging video two mirror forest fires recognition system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210331547.0A CN102881106B (en) | 2012-09-10 | 2012-09-10 | Dual-detection forest fire identification system through thermal imaging video and identification method thereof |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410004366.6A Division CN103761826B (en) | 2012-09-10 | 2012-09-10 | The recognition methods of a kind of thermal imaging video two mirror forest fires recognition system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102881106A true CN102881106A (en) | 2013-01-16 |
| CN102881106B CN102881106B (en) | 2014-07-02 |
Family
ID=47482413
Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410004366.6A Active CN103761826B (en) | 2012-09-10 | 2012-09-10 | The recognition methods of a kind of thermal imaging video two mirror forest fires recognition system |
| CN201210331547.0A Active CN102881106B (en) | 2012-09-10 | 2012-09-10 | Dual-detection forest fire identification system through thermal imaging video and identification method thereof |
Family Applications Before (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410004366.6A Active CN103761826B (en) | 2012-09-10 | 2012-09-10 | The recognition methods of a kind of thermal imaging video two mirror forest fires recognition system |
Country Status (1)
| Country | Link |
|---|---|
| CN (2) | CN103761826B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105450971A (en) * | 2014-08-15 | 2016-03-30 | 深圳Tcl新技术有限公司 | Privacy protection method and device of video call and television |
| CN107246913A (en) * | 2017-06-05 | 2017-10-13 | 山东神戎电子股份有限公司 | Based on the multiple forest fire protection detection method for differentiating mechanism |
| CN107481465A (en) * | 2017-08-21 | 2017-12-15 | 昆明理工大学 | A kind of aerial unmanned plane infrared monitoring method for early warning of forest adaptive cruise |
| CN109445315A (en) * | 2018-08-21 | 2019-03-08 | 成都理工大学 | High-voltage test hall safety guard and method of controlling security |
| CN111307291A (en) * | 2020-03-02 | 2020-06-19 | 武汉大学 | Surface temperature anomaly detection and positioning method, device and system based on unmanned aerial vehicle |
| WO2020151453A1 (en) * | 2019-01-22 | 2020-07-30 | 杭州海康微影传感科技有限公司 | Open fire detection method and device, and storage medium |
| CN113554845A (en) * | 2021-06-25 | 2021-10-26 | 东莞市鑫泰仪器仪表有限公司 | Be used for forest fire prevention thermal imaging device |
| CN114792459A (en) * | 2021-01-25 | 2022-07-26 | 杭州申弘智能科技有限公司 | Remote fire monitoring management system and smoke detection method |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108389352A (en) * | 2018-03-14 | 2018-08-10 | 青岛市光电工程技术研究院(中国科学院光电研究院青岛光电工程技术研究中心) | Fire source probing method and device |
| CN110390788A (en) * | 2019-08-21 | 2019-10-29 | 深圳云感物联网科技有限公司 | A kind of forest fire protection firework identification method and its system |
| CN110681097B (en) * | 2019-09-30 | 2021-04-16 | 张瑞祺 | Full-intelligent fire extinguishing system |
| 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 |
| CN112649095B (en) * | 2020-11-26 | 2022-09-09 | 江苏集萃未来城市应用技术研究所有限公司 | Large-range accurate temperature measurement system based on affine transformation and optical/infrared double lenses |
| CN113283276A (en) * | 2020-12-30 | 2021-08-20 | 四川弘和通讯有限公司 | Linkage thermal imaging self-learning fire point detection method and system |
| CN113029878B (en) * | 2021-03-08 | 2023-11-14 | 湖南中冶长天节能环保技术有限公司 | Method for detecting high temperature of active carbon and giving alarm in grading manner |
| CN113177496A (en) * | 2021-05-10 | 2021-07-27 | 浙江大华技术股份有限公司 | Fire point detection method, device, equipment and storage medium |
| CN113506419B (en) * | 2021-06-30 | 2022-08-19 | 中标慧安信息技术股份有限公司 | Indoor safety state analysis method and system based on video data |
| 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 (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040005085A1 (en) * | 2002-07-04 | 2004-01-08 | Andersen Dan Keith | Method of aerial monitoring of forests |
| US20050104771A1 (en) * | 2003-09-17 | 2005-05-19 | Spectrotech, Inc. | Airborne imaging spectrometry system and method |
| 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 (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050162515A1 (en) * | 2000-10-24 | 2005-07-28 | Objectvideo, Inc. | Video surveillance system |
| 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 CN201410004366.6A patent/CN103761826B/en active Active
- 2012-09-10 CN CN201210331547.0A patent/CN102881106B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040005085A1 (en) * | 2002-07-04 | 2004-01-08 | Andersen Dan Keith | Method of aerial monitoring of forests |
| US20050104771A1 (en) * | 2003-09-17 | 2005-05-19 | Spectrotech, Inc. | Airborne imaging spectrometry system and method |
| 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 (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105450971A (en) * | 2014-08-15 | 2016-03-30 | 深圳Tcl新技术有限公司 | Privacy protection method and device of video call and television |
| CN107246913A (en) * | 2017-06-05 | 2017-10-13 | 山东神戎电子股份有限公司 | Based on the multiple forest fire protection detection method for differentiating mechanism |
| CN107246913B (en) * | 2017-06-05 | 2019-11-08 | 山东神戎电子股份有限公司 | Based on the multiple forest fire protection detection method for differentiating mechanism |
| CN107481465A (en) * | 2017-08-21 | 2017-12-15 | 昆明理工大学 | A kind of aerial unmanned plane infrared monitoring method for early warning of forest adaptive cruise |
| CN109445315A (en) * | 2018-08-21 | 2019-03-08 | 成都理工大学 | High-voltage test hall safety guard and method of controlling security |
| WO2020151453A1 (en) * | 2019-01-22 | 2020-07-30 | 杭州海康微影传感科技有限公司 | Open fire detection method and device, and storage medium |
| CN111539239A (en) * | 2019-01-22 | 2020-08-14 | 杭州海康微影传感科技有限公司 | Method, device and storage medium for open fire detection |
| CN111539239B (en) * | 2019-01-22 | 2023-09-22 | 杭州海康微影传感科技有限公司 | Open fire detection method, device and storage medium |
| CN111307291A (en) * | 2020-03-02 | 2020-06-19 | 武汉大学 | Surface temperature anomaly detection and positioning method, device and system based on unmanned aerial vehicle |
| CN114792459A (en) * | 2021-01-25 | 2022-07-26 | 杭州申弘智能科技有限公司 | Remote fire monitoring management system and smoke detection method |
| CN113554845A (en) * | 2021-06-25 | 2021-10-26 | 东莞市鑫泰仪器仪表有限公司 | Be used for forest fire prevention thermal imaging device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102881106B (en) | 2014-07-02 |
| CN103761826B (en) | 2016-03-30 |
| CN103761826A (en) | 2014-04-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102881106B (en) | Dual-detection forest fire identification system through thermal imaging video and identification method thereof | |
| CN109816678B (en) | Automatic nozzle atomization angle detection system and method based on vision | |
| JP4705090B2 (en) | Smoke sensing device and method | |
| CN111179279A (en) | Comprehensive flame detection method based on ultraviolet and binocular vision | |
| CN104598895A (en) | Method and device for flame detection based on video image analysis | |
| CN105512667A (en) | Method for fire identification through infrared and visible-light video image fusion | |
| CN105046868A (en) | Fire early warning method based on infrared thermal imager in narrow environment | |
| CN110458157B (en) | Intelligent monitoring system for power cable production process | |
| CN111047568A (en) | Steam leakage defect detection and identification method and system | |
| Wang et al. | A new fire detection method using a multi-expert system based on color dispersion, similarity and centroid motion in indoor environment | |
| CN109074713B (en) | Smoke detection device, method for detecting smoke of fire, and storage medium | |
| CN104378539A (en) | Scene-adaptive video structuring semantic extraction camera and method thereof | |
| CN111008998A (en) | Automatic fire water monitor flame detection method based on binocular vision | |
| CN101930540A (en) | Video-based multi-feature fusion flame detecting device and method | |
| JP4111660B2 (en) | Fire detection equipment | |
| CN109841028B (en) | Thermal infrared imager-based heat source detection method and system and storage medium | |
| CN101916380B (en) | Video-based device and method for detecting smog | |
| CN202795630U (en) | Thermal imagery video double-identification forest fire recognition system | |
| CN105427303B (en) | A kind of vision measurement and method of estimation of substation's legacy | |
| CN111664946A (en) | Wide-area temperature screening equipment | |
| CN110120142B (en) | Fire smoke video intelligent monitoring early warning system and early warning method | |
| CN101930541A (en) | Video-based flame detecting device and method | |
| CN103020587A (en) | View analyzing method based on video image analysis | |
| KR20230064388A (en) | Composite image based fire detection system | |
| JP5309069B2 (en) | Smoke detector |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C53 | Correction of patent of invention or patent application | ||
| CB03 | Change of inventor or designer information |
Inventor after: He Tiejun Inventor after: Chen Weilong Inventor after: Feng Xiaoqiang Inventor before: He Tiejun Inventor before: Feng Xiaoqiang |
|
| COR | Change of bibliographic data |
Free format text: CORRECT: INVENTOR; FROM: HE TIEJUN FENG XIAOQIANG TO: HE TIEJUN CHEN WEILONG FENG XIAOQIANG |
|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |