CN108520615A - A kind of fire identification system and method based on image - Google Patents
A kind of fire identification system and method based on image Download PDFInfo
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- CN108520615A CN108520615A CN201810364398.5A CN201810364398A CN108520615A CN 108520615 A CN108520615 A CN 108520615A CN 201810364398 A CN201810364398 A CN 201810364398A CN 108520615 A CN108520615 A CN 108520615A
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- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000012360 testing method Methods 0.000 claims abstract description 8
- 238000012545 processing Methods 0.000 claims description 34
- 230000009466 transformation Effects 0.000 claims description 26
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 claims description 19
- 238000005286 illumination Methods 0.000 claims description 12
- 238000012544 monitoring process Methods 0.000 claims description 6
- 239000000126 substance Substances 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 5
- 238000009434 installation Methods 0.000 claims description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 1
- 238000012806 monitoring device Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
Abstract
The present invention provides a kind of fire identification system and method based on image, circumferential images are acquired in real time using CCD camera, brightness recognition unit carries out brightness identification to image, judge whether that there is highlighted object, when detecting highlighted object, it is calculated using the unit that tests the speed and highlights object movement speed, and comprehensively utilized the information such as weather data, CCD camera place geographical coordinate, CCD camera rotation angle and the local time in CCD camera location and judge to highlight whether object is flame.
Description
Technical field
The invention belongs to technical field of image processing more particularly to a kind of fire identification systems and method based on image.
Background technology
Forest zone is difficult by it has been found that China is historical great several times gloomy in fire early period of origination due to meagrely-populated
Forest fires calamity is just found after fire spread to certain scale.Often hill path is rugged, vegetation is luxuriant due to forest zone, traffic not
Convenient, fire fighting service is difficult to transport to scene of fire, this puts out to forest fire brings high difficulty.
Currently, being after obtaining video image, to divide to the main operational principle that forest fire is monitored based on video technique
Color and the brightness for analysing image, to judge whether there is fire.However, since the color and shape of flame is with prodigious
Uncertainty, monitoring device can not distinguish the flame of the light sources such as the sun, the moon, lightning, car bulb and fire early period of origination
It comes, is easy wrong report dangerous situation.
Invention content
The present invention provides a kind of fire identification system and method based on image, it is intended to solve above-mentioned technical problem.
A kind of fire identification system based on image, which is characterized in that including：
CCD camera, CCD camera acquire forest image around installation upright bar 360 degree rotation in real time.
CCD camera rotation control unit, the rotary speed for controlling CCD camera.
Image acquisition unit obtains the present image of the video monitoring regional of CCD camera.
Whether brightness recognition unit, identifying has highlighted object in present image.When recognizing highlighted object, CCD camera shootings
Head rotation control unit control CCD camera stops rotating, and orientation where CCD camera alignment highlights object is continuously shot figure
Picture.
Test the speed unit, for being tracked to the highlighted object recognized, calculates and highlights object movement speed, if speed
More than threshold value, then judge that the highlighted object is not flame, CCD camera restores rotation.
Weather data reading unit, the real-time weather data for transferring CCD camera location in meteorological system.
CCD camera rotation angle acquiring unit, video monitor unit rotation angle when taking highlighted object for obtaining
Degree.
Central processing unit excludes if the weather data that weather data reading unit is read is cloudy day or rainy day
The highlighted object is the possibility of the sun or the moon, and central processing unit sends out alarm command to alarm unit；If real-time day
Gas is fine day or cloudy, CCD camera rotation angle when the acquisition of CCD camera rotation angle acquiring unit takes highlighted object
Degree, central processing unit is according to geographical coordinate, CCD camera rotation angle and CCD camera location where CCD camera
Local time, calculate the Sun and the Moon relative to orientation where CCD camera, and the Sun and the Moon is taken the photograph relative to CCD
Orientation and highlighted object place orientation are matched as where head, if misaligned, central processing unit is sent out to alarm unit
Instruction, if overlapped, it is celestial body light source that this is highlighted substance markers by central processing unit, and CCD camera restores rotation.
Alarm unit, for obtaining alarm command that central processing unit is sent out and sending out fire alarm signal.
Further, the fire identification system based on image further includes image pre-processing unit, single for being obtained to image
The image that member obtains reject the pretreatment of illumination.To the image that image acquisition unit obtains, coloured image is converted first
For gray level image, extra illumination is then rejected using the method for gamma transformation, the wherein threshold value of gamma transformation is schemed by calculating
The maximum value of pixel grey scale is dynamically determined as in；
The citation form of gamma transformation is：
S=crγ
Coloured image is converted to gray level image, then traverses entire image, finds highest gray value in all pixels
G, i.e.,
G=max { g1, g2 ..., gi}
Then the deformation formula of gamma transformation is used：
S=c (r-g)γ
And
S=c (r+L-1-g)γ
Wherein r is input picture gray value, and s is output gray value of image, and c and γ are normal number, and L is grayscale image
Number of greyscale levels, giIndicate the gray value of ith pixel point in image.
A kind of method for recognizing fire disaster based on image, includes the following steps；
S1, CCD camera rotation control unit control control under, CCD camera surround mounting rod 360 degree rotation,
Forest image is acquired in real time.
S2, image acquisition unit obtain the present image of the video monitoring regional of CCD camera.
Whether there is highlighted object, when recognizing highlighted object, CCD in S3, brightness recognition unit identification present image
Camera rotation control unit control CCD camera stops rotating, and orientation where CCD camera alignment highlights object is continuously shot
Image.
S4, the unit that tests the speed are tracked the highlighted object recognized, calculate and highlight object movement speed, if speed is big
In threshold value, then judge that the highlighted object is not flame, CCD camera restores rotation.
If S5, highlighted object movement speed are less than threshold value, the real-time of CCD camera location in meteorological system is transferred
Weather data.
If the weather data that S6, weather data reading unit are read is cloudy day or rainy day, the highlighted object is excluded
It is the possibility of the sun or the moon, central processing unit sends out alarm command to alarm unit, and alarm unit gets centre
It manages the alarm command that unit is sent out and sends out fire alarm signal；If real-time weather is fine day or cloudy, CCD camera rotation
CCD camera rotation angle when the acquisition of gyration acquiring unit takes highlighted object, central processing unit is according to CCD camera
The local time of place geographical coordinate, CCD camera rotation angle and CCD camera location, calculate the Sun and the Moon
Relative to orientation where CCD camera, and by the Sun and the Moon relative to orientation where CCD camera and highlighted object place side
Position is matched, if misaligned, central processing unit sends out instruction to alarm unit, and alarm unit obtains central processing unit
The alarm command that sends out simultaneously sends out fire alarm signal, if overlapped, it is celestial light that this is highlighted substance markers by central processing unit
Source, CCD camera restore rotation.
Further, further include image preprocessing step between step S2 and S3, for being obtained to image acquisition unit
Image carry out reject illumination pretreatment.To the image that image acquisition unit obtains, coloured image is converted into gray scale first
Then image rejects extra illumination using the method for gamma transformation, wherein the threshold value of gamma transformation is by calculating picture in image
The maximum value of plain gray scale is dynamically determined.
The citation form of gamma transformation is：
S=crγ
Coloured image is converted to gray level image, then traverses entire image, finds highest gray value in all pixels
G, i.e.,
G=max { g1, g2..., gi
Then the deformation formula of gamma transformation is used：
S=c (r-g)γ
And
S=c (r+L-1-g)γ
Wherein r is input picture gray value, and s is output gray value of image, and c and γ are normal number, and L is grayscale image
Number of greyscale levels, giIndicate the gray value of ith pixel point in image.
Description of the drawings
Fig. 1 is a kind of fire identification system work flow diagram based on image.
Specific implementation mode
Below in conjunction with the accompanying drawings, it elaborates to embodiment.
Fig. 1 shows a kind of fire identification system work flow diagram based on image of the present invention, a kind of base of the invention
In the fire identification system of image, including：CCD camera, CCD camera surround mounting rod 360 degree rotation, to forest image into
Row acquisition in real time.
CCD camera rotation control unit, the rotary speed for controlling CCD camera.
Image acquisition unit obtains the present image of the video monitoring regional of CCD camera.
Whether brightness recognition unit, identifying has highlighted object in present image.When recognizing highlighted object, CCD camera shootings
Head rotation control unit control CCD camera stops rotating, and orientation where CCD camera alignment highlights object is continuously shot figure
Picture.
Test the speed unit, for being tracked to the highlighted object recognized, calculates and highlights object movement speed.If speed
More than threshold value, then judge that the highlighted object is not flame；The highlighted object is that lightning, car bulb etc. fast move light source, CCD
Camera restores rotation.
Weather data reading unit, the real-time weather for transferring CCD camera location in meteorological system by network
Data.If highlighted object movement speed is less than threshold value, the real-time weather number in CCD camera location in meteorological system is transferred
According to.
CCD camera rotation angle acquiring unit, video monitor unit rotation angle when taking highlighted object for obtaining
Degree.
Central processing unit excludes if the weather data that weather data reading unit is read is cloudy day or rainy day
The highlighted object is the possibility of the sun or the moon, and central processing unit sends out alarm command to alarm unit；If real-time day
Gas is fine day or cloudy, CCD camera rotation angle when the acquisition of CCD camera rotation angle acquiring unit takes highlighted object
Degree, central processing unit is according to geographical coordinate, CCD camera rotation angle and CCD camera location where CCD camera
Local time, calculate the Sun and the Moon relative to orientation where CCD camera, and the Sun and the Moon is taken the photograph relative to CCD
Orientation and highlighted object place orientation are matched as where head, if misaligned, central processing unit is sent out to alarm unit
Instruction, if overlapped, it is celestial body light source that this is highlighted substance markers by central processing unit, and CCD camera restores rotation.
Alarm unit, for obtaining alarm command that central processing unit is sent out and sending out fire alarm signal.
Further, further include image pre-processing unit, the image for being obtained to image acquisition unit carries out rejecting light
According to pretreatment.To the image that image acquisition unit obtains, coloured image is converted into gray level image first, then uses gamma
The method of transformation rejects extra illumination, and wherein the threshold value of gamma transformation is moved by calculating the maximum value of pixel grey scale in image
State determines.
In order to reduce the influence of illumination.Using the method for gamma transformation (also referred to as power transform) come the current figure to acquisition
As being handled.
The citation form of gamma transformation is：
S=crγ
Coloured image is converted to gray level image, then traverses entire image, finds highest gray value in all pixels
G, i.e.,
G=max { g1, g2..., gi}
Then the deformation formula of gamma transformation is used：
S=c (r-g)γ
And
S=c (r+L-1-g)γ
Wherein r is input picture gray value, and s is output gray value of image, and c and γ are normal number, and L is grayscale image
Number of greyscale levels, giIndicate the gray value of ith pixel point in image.
The present invention also provides a kind of fire identification sides based on image using the above-mentioned fire identification system based on image
Method includes the following steps.
S1, CCD camera rotation control unit control control under, CCD camera surround mounting rod 360 degree rotation,
Forest image is acquired in real time.
S2, image acquisition unit obtain the present image of the video monitoring regional of CCD camera.
Whether there is highlighted object in S3, brightness recognition unit identification present image.When recognizing highlighted object, CCD
Camera rotation control unit control CCD camera stops rotating, and orientation where CCD camera alignment highlights object is continuously shot
Image.
S4, the unit that tests the speed are tracked the highlighted object recognized, calculate and highlight object movement speed.If speed is big
In threshold value, then judge that the highlighted object is not flame；The highlighted object is that lightning, car bulb etc. fast move light source, and CCD takes the photograph
As head restores rotation.
S5, weather data reading unit transfer the real-time weather number in CCD camera location in meteorological system by network
According to.If highlighted object movement speed is less than threshold value, the real-time weather number in CCD camera location in meteorological system is transferred
According to.
If the weather data that S6, weather data reading unit are read is cloudy day or rainy day, the highlighted object is excluded
It is the possibility of the sun or the moon, central processing unit sends out alarm command to alarm unit；If real-time weather be fine day or
Person is cloudy, CCD camera rotation angle when the acquisition of CCD camera rotation angle acquiring unit takes highlighted object, centre
When managing unit according to CCD camera place geographical coordinate, CCD camera rotation angle and the locality in CCD camera location
Between, the Sun and the Moon is calculated relative to orientation where CCD camera, and by the Sun and the Moon relative to where CCD camera
Orientation where orientation and highlighted object is matched, if misaligned, central processing unit sends out instruction to alarm unit, if
It overlaps, it is celestial body light source that this is highlighted substance markers by central processing unit, and CCD camera restores rotation.
S7, alarm unit obtain the alarm command that central processing unit is sent out and send out fire alarm signal.
Further, further include image preprocessing step between step S2 and S3, for being obtained to image acquisition unit
Image carry out reject illumination pretreatment.To the image that image acquisition unit obtains, coloured image is converted into gray scale first
Then image rejects extra illumination using the method for gamma transformation, wherein the threshold value of gamma transformation is by calculating picture in image
The maximum value of plain gray scale is dynamically determined.
In order to reduce the influence of illumination, using the method for gamma transformation (also referred to as power transform) come the current figure to acquisition
As being handled, the citation form of gamma transformation is：
S=crγ
Coloured image is converted to gray level image, then traverses entire image, finds highest gray value in all pixels
G, i.e.,
G=max { g1, g2..., gi}
Then the deformation formula of gamma transformation is used：
S=c (r-g)γ
And
S=c (r+L-1-g)γ
Wherein r is input picture gray value, and s is output gray value of image, and c and γ are normal number, and L is grayscale image
Number of greyscale levels, giIndicate the gray value of ith pixel point in image.
Above-described embodiment is merely preferred embodiments of the present invention, but protection scope of the present invention is not limited to
This, any one skilled in the art in the technical scope disclosed by the present invention, the variation that can readily occur in or replaces
It changes, should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with the protection model of claim
Subject to enclosing.
Claims (4)
1. a kind of fire identification system based on image, which is characterized in that including：
CCD camera, CCD camera acquire surrounding forest image around installation upright bar 360 degree rotation in real time；
CCD camera rotation control unit, the rotary speed for controlling CCD camera；
Image acquisition unit obtains the present image of the video monitoring regional of CCD camera；
Brightness recognition unit, whether in present image that image acquisition unit obtain have highlighted object, recognize highlighted if identifying
When object, brightness recognition unit sends out signal to CCD camera rotation control unit, the control of CCD camera rotation control unit
CCD camera stops rotating, orientation continuously shot images where CCD camera alignment highlights object；
Test the speed unit, for being tracked to the highlighted object recognized, calculates and highlights object movement speed, if speed is more than
Threshold value then judges that the highlighted object is not flame, and the unit that tests the speed sends out signal to CCD camera rotation control unit, CCD camera shootings
Head rotation control unit control CCD camera restores rotation；
Weather data reading unit, the real-time weather data for transferring CCD camera location in meteorological system by network；
CCD camera rotation angle acquiring unit, video monitor unit rotation angle number of degrees when taking highlighted object for obtaining
According to；
Central processing unit excludes the height if the weather data that weather data reading unit is read is cloudy day or rainy day
Bright object is the possibility of the sun or the moon, and central processing unit sends out alarm command to alarm unit；If real-time weather is
Fine day is cloudy, CCD camera rotation angle when the acquisition of CCD camera rotation angle acquiring unit takes highlighted object,
Central processing unit is according to CCD camera place geographical coordinate, CCD camera rotation angle and CCD camera location
Local time calculates the Sun and the Moon relative to orientation where CCD camera, and the Sun and the Moon is imaged relative to CCD
Orientation where orientation where head and highlighted object is matched, if misaligned, central processing unit sends out finger to alarm unit
It enables, if overlapped, it is celestial body light source that this is highlighted substance markers by central processing unit, and CCD camera restores rotation；
Alarm unit, for obtaining alarm command that central processing unit is sent out and sending out fire alarm signal.
2. a kind of fire identification system based on image according to claim 1, which is characterized in that further include that image is located in advance
Unit is managed, the image for being obtained to image acquisition unit reject the pretreatment of illumination, image acquisition unit is obtained first
The coloured image taken is converted into gray level image, and extra illumination, wherein gamma transformation are then rejected using the method for gamma transformation
Threshold value be dynamically determined by calculating the maximum value of pixel grey scale in image；
The citation form of gamma transformation is：
S=crγ
Coloured image is converted to gray level image, then traverses entire image, finds highest gray value g in all pixels, i.e.,
G=max { g1, g2..., gi}
Then the deformation formula of gamma transformation is used：
S=c (r-g)γ
And
S=c (r+L-1-g)γ
Wherein r is input picture gray value, and s is output gray value of image, and c and γ are normal number, and L is the gray scale of grayscale image
Series, giIndicate the gray value of ith pixel point in image.
3. a kind of method for recognizing fire disaster based on image, which is characterized in that include the following steps；
S1, CCD camera rotation control unit control control under, CCD camera surround mounting rod 360 degree rotation, to gloomy
Woods image is acquired in real time；
S2, image acquisition unit obtain the present image of the video monitoring regional of CCD camera；
Whether there is highlighted object in S3, brightness recognition unit identification present image, when recognizing highlighted object, CCD camera shootings
Head rotation control unit control CCD camera stops rotating, and orientation where CCD camera alignment highlights object is continuously shot figure
Picture；
S4, the unit that tests the speed are tracked the highlighted object recognized, calculate and highlight object movement speed, if speed is more than threshold
Value then judges that the highlighted object is not flame, and CCD camera restores rotation；
If S5, highlighted object movement speed are less than threshold value, the real-time weather in CCD camera location in meteorological system is transferred
Data；
If the weather data that S6, weather data reading unit are read is cloudy day or rainy day, it is too to exclude the highlighted object
The possibility of sun or the moon, central processing unit send out alarm command to alarm unit, and alarm unit gets central processing list
Alarm command that member is sent out simultaneously sends out fire alarm signal；If real-time weather is fine day or cloudy, CCD camera rotation angle
CCD camera rotation angle when degree acquiring unit acquisition takes highlighted object, central processing unit is according to where CCD camera
The local time of geographical coordinate, CCD camera rotation angle and CCD camera location, it is opposite to calculate the Sun and the Moon
The orientation where the CCD camera, and by the Sun and the Moon relative to orientation where orientation where CCD camera and highlighted object into
Row matching, if misaligned, central processing unit sends out instruction to alarm unit, and alarm unit obtains central processing unit and sends out
Alarm command and send out fire alarm signal, if overlap, central processing unit by this highlight substance markers be celestial body light source,
CCD camera restores rotation.
4. according to a kind of method for recognizing fire disaster based on image described in claim 3, which is characterized in that in step S2 and S3
Between further include image preprocessing step, the image for being obtained to image acquisition unit reject the pretreatment of illumination, first
The image that image acquisition unit obtains first is converted into gray level image, extra light is then rejected using the method for gamma transformation
According to wherein the threshold value of gamma transformation is dynamically determined by calculating the maximum value of pixel grey scale in image；
The citation form of gamma transformation is：
S=crγ
Coloured image is converted to gray level image, then traverses entire image, finds highest gray value g in all pixels, i.e.,
G=max { g1, g2..., gi}
Then the deformation formula of gamma transformation is used：
S=c (r-g)γ
And
S=c (r+L-1-g)γ
Wherein r is input picture gray value, and s is output gray value of image, and c and γ are normal number, and L is the gray scale of grayscale image
Series, giIndicate the gray value of ith pixel point in image.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113436406A (en) * | 2021-08-25 | 2021-09-24 | 广州乐盈信息科技股份有限公司 | Sound-light alarm system |
| CN115641516A (en) * | 2022-02-24 | 2023-01-24 | 李学广 | Unmanned aerial vehicle remote control display method |
Citations (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4567367A (en) * | 1983-01-13 | 1986-01-28 | Brown De Colstoun Francois | Method for detecting a source of heat, more particularly a forest fire in a watched area, and system for carrying out said method |
| JPS63102484A (en) * | 1986-10-17 | 1988-05-07 | Miyata Kogyo Kk | Abnormality monitoring device |
| JPH0520560A (en) * | 1991-07-16 | 1993-01-29 | Hochiki Corp | Fire point detecting device |
| JPH0540894A (en) * | 1991-08-06 | 1993-02-19 | Hochiki Corp | Monitoring device |
| JPH10172077A (en) * | 1996-12-12 | 1998-06-26 | Fujitsu Ltd | Fire monitor device and computer readable medium with fire monitor program recorded |
| US5936245A (en) * | 1996-06-03 | 1999-08-10 | Institut Francais Du Petrole | Method and system for remote sensing of the flammability of the different parts of an area flown over by an aircraft |
| US20030044042A1 (en) * | 2001-05-11 | 2003-03-06 | Detector Electronics Corporation | Method and apparatus of detecting fire by flame imaging |
| CN101393603A (en) * | 2008-10-09 | 2009-03-25 | 浙江大学 | Method for recognizing and detecting tunnel fire disaster flame |
| US7541938B1 (en) * | 2006-03-29 | 2009-06-02 | Darell Eugene Engelhaupt | Optical flame detection system and method |
| CN101458865A (en) * | 2008-05-09 | 2009-06-17 | 丁国锋 | Fire disaster probe system and method |
| CN101527073A (en) * | 2009-02-17 | 2009-09-09 | 丁国锋 | Fire detection system and method thereof |
| CN101577033A (en) * | 2009-05-26 | 2009-11-11 | 官洪运 | Multiband infrared image-type fire detecting system and fire alarm system thereof |
| CN101609589A (en) * | 2008-06-17 | 2009-12-23 | 侯荣琴 | Multi-frequency image fire detection system |
| CN101625789A (en) * | 2008-07-07 | 2010-01-13 | 北京东方泰坦科技有限公司 | Method for monitoring forest fire in real time based on intelligent identification of smoke and fire |
| CN101650866A (en) * | 2009-09-22 | 2010-02-17 | 华南理工大学 | Fire detecting system applied to unmanned helicopter and fire detecting method thereof |
| CN102236947A (en) * | 2010-04-29 | 2011-11-09 | 中国建筑科学研究院 | Flame monitoring method and system based on video camera |
| CN102497509A (en) * | 2011-12-14 | 2012-06-13 | 哈尔滨工业大学 | Forest fire point disturbance-removing single point positioning device and positioning method based on the same |
| CN102622845A (en) * | 2012-03-31 | 2012-08-01 | 哈尔滨工业大学 | Background interference elimination device and elimination method based on forest flash point de-disturbance point positioning device |
| CN104537792A (en) * | 2014-12-26 | 2015-04-22 | 浙江大学 | Transmission line wildfire satellite monitoring method based on background information |
| CN106157518A (en) * | 2015-03-24 | 2016-11-23 | 青岛浩海网络科技股份有限公司 | A kind of forest fire protection far infrared anti-false-alarm system and method |
| CN106503480A (en) * | 2016-12-14 | 2017-03-15 | 中国科学院遥感与数字地球研究所 | A kind of fixed statellite fire remote-sensing monitoring method |
| US9686513B2 (en) * | 2011-03-02 | 2017-06-20 | Disicon | Forest fire video monitoring system and method |
| EP3030935A4 (en) * | 2013-08-09 | 2017-09-27 | Thermal Imaging Radar LLC | Methods for analyzing thermal image data using a plurality of virtual devices and methods for correlating depth values to image pixels |
-
2018
- 2018-04-20 CN CN201810364398.5A patent/CN108520615B/en active Active
Patent Citations (24)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4567367A (en) * | 1983-01-13 | 1986-01-28 | Brown De Colstoun Francois | Method for detecting a source of heat, more particularly a forest fire in a watched area, and system for carrying out said method |
| JPS63102484A (en) * | 1986-10-17 | 1988-05-07 | Miyata Kogyo Kk | Abnormality monitoring device |
| JPH0520560A (en) * | 1991-07-16 | 1993-01-29 | Hochiki Corp | Fire point detecting device |
| JPH0540894A (en) * | 1991-08-06 | 1993-02-19 | Hochiki Corp | Monitoring device |
| US5936245A (en) * | 1996-06-03 | 1999-08-10 | Institut Francais Du Petrole | Method and system for remote sensing of the flammability of the different parts of an area flown over by an aircraft |
| US5777548A (en) * | 1996-12-12 | 1998-07-07 | Fujitsu Limited | Fire monitoring apparatus and computer readable medium recorded with fire monitoring program |
| JPH10172077A (en) * | 1996-12-12 | 1998-06-26 | Fujitsu Ltd | Fire monitor device and computer readable medium with fire monitor program recorded |
| US20030044042A1 (en) * | 2001-05-11 | 2003-03-06 | Detector Electronics Corporation | Method and apparatus of detecting fire by flame imaging |
| US7541938B1 (en) * | 2006-03-29 | 2009-06-02 | Darell Eugene Engelhaupt | Optical flame detection system and method |
| CN101458865A (en) * | 2008-05-09 | 2009-06-17 | 丁国锋 | Fire disaster probe system and method |
| CN101609589A (en) * | 2008-06-17 | 2009-12-23 | 侯荣琴 | Multi-frequency image fire detection system |
| CN101625789A (en) * | 2008-07-07 | 2010-01-13 | 北京东方泰坦科技有限公司 | Method for monitoring forest fire in real time based on intelligent identification of smoke and fire |
| CN101393603A (en) * | 2008-10-09 | 2009-03-25 | 浙江大学 | Method for recognizing and detecting tunnel fire disaster flame |
| CN101527073A (en) * | 2009-02-17 | 2009-09-09 | 丁国锋 | Fire detection system and method thereof |
| CN101577033A (en) * | 2009-05-26 | 2009-11-11 | 官洪运 | Multiband infrared image-type fire detecting system and fire alarm system thereof |
| CN101650866A (en) * | 2009-09-22 | 2010-02-17 | 华南理工大学 | Fire detecting system applied to unmanned helicopter and fire detecting method thereof |
| CN102236947A (en) * | 2010-04-29 | 2011-11-09 | 中国建筑科学研究院 | Flame monitoring method and system based on video camera |
| US9686513B2 (en) * | 2011-03-02 | 2017-06-20 | Disicon | Forest fire video monitoring system and method |
| CN102497509A (en) * | 2011-12-14 | 2012-06-13 | 哈尔滨工业大学 | Forest fire point disturbance-removing single point positioning device and positioning method based on the same |
| CN102622845A (en) * | 2012-03-31 | 2012-08-01 | 哈尔滨工业大学 | Background interference elimination device and elimination method based on forest flash point de-disturbance point positioning device |
| EP3030935A4 (en) * | 2013-08-09 | 2017-09-27 | Thermal Imaging Radar LLC | Methods for analyzing thermal image data using a plurality of virtual devices and methods for correlating depth values to image pixels |
| CN104537792A (en) * | 2014-12-26 | 2015-04-22 | 浙江大学 | Transmission line wildfire satellite monitoring method based on background information |
| CN106157518A (en) * | 2015-03-24 | 2016-11-23 | 青岛浩海网络科技股份有限公司 | A kind of forest fire protection far infrared anti-false-alarm system and method |
| CN106503480A (en) * | 2016-12-14 | 2017-03-15 | 中国科学院遥感与数字地球研究所 | A kind of fixed statellite fire remote-sensing monitoring method |
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