CN108108695B - Fire defector recognition methods based on Infrared video image - Google Patents
Fire defector recognition methods based on Infrared video image Download PDFInfo
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Abstract
The fire defector recognition methods based on Infrared video image that the invention discloses a kind of, this method is first with infrared camera scan Infrared video image, former frame and this frame infrared light image are obtained, then extracts the doubtful flame region of adjacent two field pictures respectively using luminance threshold side；Object matching is carried out to the doubtful flame region of adjacent two frame again；Target is carried out to object matching result again and deletes the correlation progress flame object identification for determining, and utilizing the objective degrees of confidence and adjacent two frames same target that set.This method can effectively and rapidly identify flame object, also can guarantee the identification under night-environment to flame object, delete the consumption that can be reduced in algorithm operational process to calculator memory to the dynamic of target memory in identification process.
Description
Technical field
The present invention relates to technical field of computer vision, especially a kind of fire defector identification based on Infrared video image
Method.
Background technique
In recent years, Large Space Building Fires, mine fire, forest fire, tunnel fire hazard etc. frequently occur not only to make the mankind
Life and property by massive losses, great destruction also is caused to human ecological environment.With the continuous progress of science, people
Start to be conceived to the research of intelligent video analysis to take precautions against fire, fire defector and recognition methods based on image/video analysis
Quick popularization is obtained.
Fire defector and recognition methods based on image/video analysis normally comprise extraction and the fire of doubtful flame region
Flame identification.The extraction of doubtful flame region is the premise of flame identification, and it is that fire is visited that flame image is separated from background
The basis of survey is related to the accuracy of the reliability and target identification of subsequent characteristics extraction.Using the difference based on background model
The doubtful conflagration area of method extracts, and the algorithm is by realizing effective detection to flame, bond area cluster based on background model
The algorithm of growth, finally realizes extracted region.These methods assume that initial background does not include the training sequence of moving target,
Limit the use condition of background model.
There are also some algorithms, and the motion detection of flame color model often to be combined to carry out interference source exclusion, and sensitivity is by Image Acquisition
The limitation of equipment quality and motion detection algorithm superiority and inferiority, and the flame color model of general visible images is just for partially red, partially yellow
Flame color design, limitation is larger.
Fire defector based on video image can realize flame identification using features such as movement, color, the time-frequencies of flame.Its
In, it merely with the flame identification method of the static natures such as color, is easy to be interfered by similar with flame color scenery, affects and be
The robustness of system.Phollips et al. carries out flame knowledge using the grey level histogram intensity of flame and the time change of consecutive frame
Not, relatively good detection environment (the nonflame light of less movement interferes) is also needed, and its experimental data is oneself
What subjectivity determined, if input data changes, effect can have a greatly reduced quality.Yamagishi et al. proposes a kind of based on mind
The calculation amount of flame detecting method through network, algorithm is bigger.Meanwhile certain nights are affected, and not can guarantee complete
Weather monitoring.
Summary of the invention
To overcome the deficiencies in the prior art, the present invention provides a kind of fire defector knowledge based on Infrared video image
Other method, this method is by extracting the object matching of doubtful flame region and the adjacent doubtful flame region of two frames, further according to setting
The correlation of fixed objective degrees of confidence and adjacent two frames same target region carries out flame object, can effectively and rapidly identify
Flame object can be reduced in algorithm operational process the dynamic deletion of target memory in identification process and disappear to calculator memory
Consumption, while the physical characteristic of infrared light image is utilized, so that also can successfully identify flame object under night-environment.
To realize the above-mentioned technical purpose, the present invention adopts the following technical scheme:
A kind of fire defector recognition methods based on Infrared video image, comprising the following steps:
S1 utilizes infrared camera scan Infrared video image, obtains former frame and this frame infrared light image.In order to timely
It identifies flame object, needs to according to the methods below while acquiring image to handle image.
S2 extracts the doubtful flame region in former frame and this frame infrared light image respectively；
S3 carries out object matching to the doubtful flame region of former frame and this frame infrared light image；
The deletion judgement of each target of the doubtful flame region of S4 this frame infrared light image and flame object identification；
S5 inputs the infrared light image of new next frame, continues with step S2-S4 to complete the flame object of a new frame
Identification.
By carrying out the image segmentation based on brightness of image to the infrared light image acquired in S1 in S2 of the present invention, to mention
Take out doubtful flame region.Specifically includes the following steps:
S2.1 assumes that infrared light image maximum gradation value is Max, then choosesMax is the seed point of region growing.
The average gray value of pixel in neighborhood centered on S2.2 solution seed point, by each picture in seed neighborhood of a point
The absolute value of the difference of this average gray value of the sum of the grayscale values of vegetarian refreshments is compared with the threshold value T of setting.
If S2.3 is less than the threshold value T of setting, which is merged with seed point, and as new seed point；If
More than or equal to the threshold value T of setting, then give up；Continue to determine next pixel.
S2.4 is repeated in step S2.2 and S2.3, meets step S2.2 and step S2.3 until all in infrared light image
The pixel of middle requirement is all merged into some region, and this region is exactly doubtful flame region.
Doubtful flame region in former frame and this frame infrared light image is extracted using method of the S2.1 into S2.4 respectively.
S3 of the present invention the following steps are included:
S3.1 marks each target of the doubtful flame region of adjacent two field pictures by 8 neighborhood connected component labeling methods respectively
And obtain the boundary rectangle of each target.
S3.2 records the upper left point A of the boundary rectangle of each target in adjacent two frames infrared light image1, lower-left point A2, upper right
Point A3, lower-right most point A4And the central point O of boundary rectangle.
If the point A of the boundary rectangle of some target in S3.3 this frame infrared light image1, point A2, point A3, point A4And point O
This five points in, there are some point or certain several point in the boundary rectangle of some target in former frame infrared light image,
With regard to initial decision, the two targets of this adjacent two frames infrared light image are same target.
If more than two targets exist in the target and former frame infrared light image in S3.4 this frame infrared light image
It the case where situation in step S3.3, i.e., adjacent two frames infrared light image matches there are multiple targets, then needs to carry out secondary
Matching；The principle of Secondary Match are as follows: be included according to above-mentioned five points of the boundary rectangle of the target in this frame infrared light image
The center of the boundary rectangle of number and two targets in the boundary rectangle of another target in former frame infrared light image
The distance of point judged, i.e., the number comprising point at most and the distance between two central points recently, then illustrate the two mesh
It is designated as same target.Here, the distance of two central points uses Euclidean distance, if O1(x1,y1) and O2(x2,y2) it is respectively two targets
The central point of boundary rectangle, then the Euclidean distance calculation method of two central points are as follows:
D=sqrt ((x1-x2)2+(y1-y2)2) (1)
If the point A of the boundary rectangle of either objective in S3.5 this frame infrared light image1, point A2, point A3, point A4And point O
This five points in, there is no in the boundary rectangle of the either objective in former frame infrared light image, i.e. this frame infrared light
Each target of doubtful flame region all mismatches in each target of doubtful flame region and former frame infrared light image in image, says
This bright target is emerging target, then records the position of the target, gives goal-setting existence confidence level believe, initially
30, and setting flame confidence level are turned to, is initialized as 0, doubtful flame object number adds 1.
S4 of the present invention the following steps are included:
S4.1 is obtained the same target of former frame infrared light image and this frame infrared light image by the object matching of step S3,
If the target has been labeled as flame object before former frame infrared light image or former frame infrared light image, to the mesh
Mark carries out delete operation.
S4.1.1 is obtained the identical mesh of former frame infrared light image and this frame infrared light image by the object matching of step S3
Mark, for the target area with same target in former frame infrared light image and this frame infrared light image, if the target exists
It has been determined as flame object before former frame infrared light image or former frame infrared light image, has judged this frame infrared light image
In whether there is also bright areas for the target area；Wherein bright areas refers to that the gray value that there is pixel in this region is big
In or be equal toMax, then the region is bright areas.
If the target area in the S4.1.2 former frame infrared light image and this frame infrared light image with same target is deposited
In bright areas, then the existence confidence level believe of the target area adds 2, then determines whether its confidence level believe that survives is big
In 200 or less than 0, if so, deleting this target, the memory of the target is discharged；Otherwise, continue to retain this target.
If the target area in the S4.1.3 former frame infrared light image and this frame infrared light image with same target is not
There are bright areas, then the existence confidence level believe of the target area subtracts 2, then whether determine its existence confidence level believe
Greater than 200 or less than 0, if so, deleting this target, the memory of the target is discharged；Otherwise continue to retain this target.
S4.2 is obtained the same target of former frame infrared light image and this frame infrared light image by the object matching of step S3,
If the target is not denoted as flame object before former frame infrared light image and former frame infrared light image, to its into
The identification of row flame object.
S4.2.1 is obtained the identical mesh of former frame infrared light image and this frame infrared light image by the object matching of step S3
Mark, if being not flagged as flame object and the mesh before the same target of former frame infrared light image and this frame infrared light image
The fresh target that the not doubtful flame region for being designated as judging in step S3 occurs, according to the target in this frame infrared light image
The doubtful flame information of location updating, and same target in the doubtful flame region of two adjacent two frames infrared light images of calculating
Correlation, the correlation calculations formula of same target are as follows:
In above formula, X1(n1,n2) be former frame infrared light image in some target certain point (n1,n2) pixel value, X2
(n1,n2) be this frame infrared light image identical point pixel value；M1And M2For the horizontal and vertical pixel of single frames infrared light image
Points；n1And n2For the coordinate that certain in image is put, m1And m2For offset.
The influence of noise may make two frames false matches phenomenon occur, in order to eliminate this influence, to C (m1,m2) make normalizing
Change processing, is positioned as after normalization
Wherein,WithIndicate that the same target region of former frame infrared light image and this frame infrared light image is (i.e. previous
With the target area of same target in frame infrared light image and this frame infrared light image) average pixel value intensity, it may be assumed that
If S4.2.2 related coefficientGreater than the threshold value T of setting, then this target existence confidence level believe subtracts
1 and flame confidence level score subtracts 1；Whether the existence confidence level believe of target is greater than 200 or less than 0, if then deleting
Except this target, the memory of the target is discharged.
If S4.2.3 related coefficientLess than the threshold value T of setting, then confidence level of surviving score adds 1,
The value of believe adds 1, and updates flame information, judges whether score at this time is greater than 10, if so, determining that this target is
Flame object；If score is not more than 10, judge whether the existence confidence level believe of target is greater than 200 or less than 0, if
It is to delete this target, discharges the memory of the target.
Compared with prior art, the invention has the following advantages:
1) present invention carries out processing to adjacent two frames infrared image respectively using luminance threshold method and obtains two images respectively
Doubtful flame region, each connected domain in doubtful flame region is marked by connected component labeling method, then pass through phase
The doubtful flame region of adjacent two frames carries out object matching, the successful match to adjacent two frame and have been marked as the target of flame into
Row, which is deleted, to be determined, i.e., when whether target existence confidence level believe is greater than 200 or less than 0, if then deleting this target,
The memory of the target is discharged, can be reduced the occupancy to calculator memory of algorithm in the process of running in this way.
2) present invention is during the doubtful flame region of adjacent two frame carries out object matching, it is contemplated that multiple targets
Similar situation has carried out Secondary Match and has obtained two most preferably close targets.
3) present invention determines that this method passes through red using the correlation and confidence level memory flame of adjacent two frame target area
Outer video image can effectively and rapidly identify flame object, and the physical characteristic of infrared image is utilized, so that in night ring
Also flame object can be successfully identified under border, while dynamic delete target memory during flame identification, can reduce algorithm
Consumption of the operational process to calculator memory.
Detailed description of the invention
Fig. 1 is flow chart of the invention；
Fig. 2 is the object matching flow chart of the doubtful flame region of adjacent two frame of the embodiment of the present invention；
Fig. 3 is that the target of the embodiment of the present invention deletes decision flow chart；
Fig. 4 is the flame object identification process figure of the embodiment of the present invention.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached drawing to embodiment party of the present invention
Formula is described in further detail.
Referring to Fig. 1, for the present invention is based on the flow chart of the fire defector recognition methods of Infrared video image, the present invention includes
Following steps:
A kind of fire defector recognition methods based on Infrared video image, comprising the following steps:
S1 utilizes infrared camera scan Infrared video image, obtains former frame and this frame infrared light image.In order to timely
It identifies flame object, needs to according to the methods below while acquiring image to handle image.
S2 extracts the doubtful flame region in former frame and this frame infrared light image respectively；
Infrared radiation is a kind of most commonly used electromagenetic wave radiation existing for nature, it is based on any object normal
Itself molecule and the random movement of atom can all be generated under rule environment, do not stop eradiation and go out thermal infrared energy, molecule and
Atomic motion is more violent, and the energy of radiation is bigger, otherwise the energy of radiation is smaller.Thermal camera is according to object emission or reflection
Infrared imaging, the flame of different flame colors all has higher brightness in Infrared video image.The process that flame occurs is adjoint
It is luminous, fever the phenomenon that, the temperature of flame generation area will be apparently higher than the temperature of ambient enviroment.
Directly proportional to temperature height in view of the Luminance Distribution of its thermography, the present invention passes through to the infrared light collected
Image carries out the image segmentation based on brightness of image, so that high temp objects region is tentatively extracted, high temp objects region, that is, doubtful
Flame region.Specific step is as follows:
S2.1 assumes that infrared light image maximum gradation value is Max, then choosesMax is the seed point of region growing；
S2.2 solves the average gray value of neighborhood (for example 3 × 3 window neighborhoods) interior pixel centered on seed point, will plant
The absolute value of the difference of the sum of the grayscale values of each pixel this average gray value in sub- neighborhood of a point and the threshold value T of setting are compared
Compared with；
If S2.3 is less than the threshold value T of setting, which is merged with seed point, and as new seed point；If
More than or equal to the threshold value T of setting, then give up；Continue to determine next pixel.
S2.4 is repeated in step S2.2 and S2.3 until all in infrared light image meet the requirements (meets step S2.2
Required in step S2.3) pixel be all merged into some region, and this region is exactly doubtful flame region.
Doubtful flame region in former frame and this frame infrared light image is extracted using method of the S2.1 into S2.4 respectively.
S3 carries out object matching to the doubtful flame region of former frame and this frame infrared light image；It is adjacent two referring to Fig. 2
The object matching flow chart of the doubtful flame region of frame infrared light image, comprising the following steps:
S3.1 marks each target of the doubtful flame region of adjacent two field pictures by 8 neighborhood connected component labeling methods respectively
And obtain the boundary rectangle of each target；
S3.2 records the upper left point A of the boundary rectangle of each target in adjacent two frames infrared light image1, lower-left point A2, upper right
Point A3, lower-right most point A4And the central point O of boundary rectangle；
If the point A of the boundary rectangle of some target in S3.3 this frame infrared light image1, point A2, point A3, point A4And point O
This five points in, there are some point or certain several point in the boundary rectangle of some target in former frame infrared light image,
Can the two targets of initial decision this adjacent two frames infrared light image be same target；
If more than two targets exist in the target and former frame infrared light image in S3.4 this frame infrared light image
It the case where situation in step S3.3, i.e., adjacent two frames infrared light image matches there are multiple targets, then needs to carry out secondary
Matching.The thought of Secondary Match are as follows: according to above-mentioned five points of the boundary rectangle of the target in this frame infrared light image (target
The upper left point A of boundary rectangle1, lower-left point A2, upper right point A3, lower-right most point A4And the central point O of boundary rectangle) included in previous
The central point of the boundary rectangle of number and two targets in the boundary rectangle of another target in frame infrared light image
Distance judged, i.e., the number comprising point is more and the distance between central point is closer, then illustrates that the two targets are phase
Same target.
It calculates the distance between two o'clock and uses Euclidean distance.Assuming that O1(x1,y1) and O2(x2,y2) it is respectively that two targets are external
The central point of rectangle, then Euclidean distance are as follows:
D=sqrt ((x1-x2)2+(y1-y2)2) (1)
If some target of S3.5 former frame infrared light image is according to each mesh in method in step S3.3 and former frame
Mark is matched, there is no it is occurring in step S3.3 as a result, i.e. in this frame doubtful flame region each target and former frame
In each target of doubtful flame region all mismatch, illustrate that this target is emerging target, then record the position of the target, give
Goal-setting existence confidence level believe is initialized as 30, and setting flame confidence level, is initialized as 0, doubtful flame
Target numbers add 1.
The deletion judgement of each target of the doubtful flame region of S4 this frame infrared light image and flame object identification；
S4.1 is obtained the same target of former frame infrared light image and this frame infrared light image by the object matching of step S3,
If the target (i.e. the same target of former frame infrared light image and this frame infrared light image) in former frame infrared light image or
Flame object is had been labeled as before former frame infrared light image, then delete operation is carried out to the target；Fig. 3 is that target deletion is sentenced
Determine operational flowchart.
S4.1.1 is obtained the identical mesh of former frame infrared light image and this frame infrared light image by the object matching of step S3
Mark, for the target area with same target in former frame infrared light image and this frame infrared light image, if the target exists
It has been determined as flame object before former frame infrared light image or former frame infrared light image, has judged this frame infrared light image
In whether there is also bright areas for the target area；Wherein bright areas refers to that the gray value that there is pixel in this region is big
In or be equal toMax, then the region is bright areas；
If the target area in the S4.1.2 former frame infrared light image and this frame infrared light image with same target is deposited
In bright areas, then the existence confidence level believe of the target area adds 2, then determines whether its confidence level believe that survives is big
In 200 or less than 0, if so, deleting this target, the memory of the target is discharged；Otherwise, continue to retain this target.
If the target area in the S4.1.3 former frame infrared light image and this frame infrared light image with same target is not
There are bright areas, then the existence confidence level believe of the target area subtracts 2, then whether determine its existence confidence level believe
Greater than 200 or less than 0, if so, deleting this target, the memory of the target is discharged；Otherwise continue to retain this target.
S4.2 is obtained the same target of former frame infrared light image and this frame infrared light image by the object matching of step S3,
If the target is not denoted as flame object before former frame infrared light image and former frame infrared light image, to its into
The identification of row flame object；
Judge with the presence or absence of flame object in doubtful flame region, to carry out alarm response.Due to flame so by when
The volume of gas plume inhales the influence of characteristic and air flowing, and burned flame shows ceaselessly oscillating characteristic, and this oscillation is special
Property can use the correlation of image to realize flame fire identification.Fig. 4 is flame object identification process figure, present invention employs
The flame determination method of correlation and confidence level based on target is mentioned, realizes that process is as follows:
S4.2.1 is obtained the identical mesh of former frame infrared light image and this frame infrared light image by the object matching of step S3
Mark, if being not flagged as flame object and the mesh before the same target of former frame infrared light image and this frame infrared light image
The fresh target that the not doubtful flame region for being designated as judging in step S3 occurs, according to the target in this frame infrared light image
The doubtful flame information of location updating, and same target in the doubtful flame region of two adjacent two frames infrared light images of calculating
Correlation, the correlation calculations formula of same target are as follows:
In above formula, X1(n1,n2) be former frame infrared light image in some target certain point (n1,n2) pixel value, X2
(n1,n2) be this frame infrared light image identical point pixel value；M1And M2For the horizontal and vertical pixel of single frames infrared light image
Points；n1And n2For the coordinate that certain in image is put, m1And m2For offset.
The influence of noise may make two frames false matches phenomenon occur, in order to eliminate this influence, to C (m1,m2) make normalizing
Change processing, is positioned as after normalization
Wherein,WithThe same target region of expression former frame infrared light image and this frame infrared light image is (before i.e.
With the target area of same target in one frame infrared light image and this frame infrared light image) average pixel value intensity, it may be assumed that
If S4.2.2 related coefficientGreater than the threshold value T of setting, then this target existence confidence level believe subtracts
1 and flame confidence level score subtracts 1；Whether the existence confidence level believe of target is greater than 200 or less than 0, if then deleting
Except this target, the memory of the target is discharged；
If S4.2.3 related coefficientLess than the threshold value T of setting, then confidence level of surviving score adds 1,
The value of believe adds 1, and updates flame information, judges whether score at this time is greater than 10, if so, determining that this target is
Flame object；If score is not more than 10, then judge whether the existence confidence level believe of target is greater than 200 or less than 0,
If then deleting this target, the memory of the target is discharged.
S5 inputs the infrared light image of new next frame, continues with step S2-S4 to complete the flame object of a new frame
Identification.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (6)
1. a kind of fire defector recognition methods based on Infrared video image, which comprises the following steps:
S1 utilizes infrared camera scan Infrared video image, obtains former frame and this frame infrared light image；
S2 extracts the doubtful flame region in former frame and this frame infrared light image respectively；
S3 carries out object matching to the doubtful flame region of former frame and this frame infrared light image, the method is as follows:
S3.1 marked respectively by 8 neighborhood connected component labeling methods each target of the doubtful flame region of adjacent two field pictures with
And obtain the boundary rectangle of each target；
S3.2 records the upper left point A of the boundary rectangle of each target in adjacent two frames infrared light image1, lower-left point A2, upper right point
A3, lower-right most point A4And the central point O of boundary rectangle；
If the point A of the boundary rectangle of some target in S3.3 this frame infrared light image1, point A2, point A3, point A4And point O this
In five points, there are some points or certain several point in the boundary rectangle of some target in former frame infrared light image, just just
Beginning judges the two targets of this adjacent two frames infrared light image for same target；
If there are steps for more than two targets in the target and former frame infrared light image in S3.4 this frame infrared light image
It the case where situation in S3.3, i.e., adjacent two frames infrared light image matches there are multiple targets, then needs to carry out Secondary Match；
The principle of Secondary Match are as follows: former frame is included according to above-mentioned five points of the boundary rectangle of the target in this frame infrared light image
The central point of the boundary rectangle of number and two targets in the boundary rectangle of another target in infrared light image away from
From being judged, i.e., the number comprising point at most and the distance between two central points recently, then illustrate that the two targets are phase
Same target；
If the point A of the boundary rectangle of either objective in S3.5 this frame infrared light image1, point A2, point A3, point A4And point O this
In five points, it is not present in the boundary rectangle of the either objective in former frame infrared light image, i.e. this frame infrared light image
In each target of doubtful flame region and each target of doubtful flame region in former frame infrared light image all mismatch, illustrate this
Target is emerging target, then records the position of the target, gives goal-setting existence confidence level believe, is initialized as
30, and setting flame confidence level, it is initialized as 0, doubtful flame object number adds 1；
The deletion judgement of each target of the doubtful flame region of S4 this frame infrared light image and flame object identification, the method is as follows:
S4.1 is obtained the same target of former frame infrared light image and this frame infrared light image by the object matching of step S3, if
The target has been labeled as flame object before former frame infrared light image or former frame infrared light image, then to the target
Carry out delete operation；
S4.2 is obtained the same target of former frame infrared light image and this frame infrared light image by the object matching of step S3, if
The target is not denoted as flame object before former frame infrared light image and former frame infrared light image, then carries out to it
Flame object identification；
S5 inputs the infrared light image of new next frame, continues with step S2-S4 to complete the flame object of a new frame and know
Not.
2. the fire defector recognition methods according to claim 1 based on Infrared video image, which is characterized in that lead in S2
It crosses and the image segmentation based on brightness of image is carried out to the infrared light image acquired in S1, to extract doubtful flame region.
3. the fire defector recognition methods according to claim 2 based on Infrared video image, which is characterized in that S2 includes
Following steps:
S2.1 assumes that infrared light image maximum gradation value is Max, then choosesFor the seed point of region growing；
The average gray value of pixel in neighborhood centered on S2.2 solution seed point, by each pixel in seed neighborhood of a point
The absolute value of the difference of this average gray value of the sum of the grayscale values of point is compared with the threshold value T of setting；
If S2.3 is less than the threshold value T of setting, which is merged with seed point, and as new seed point；If more than
Or the threshold value T equal to setting, then give up；Continue to determine next pixel；
S2.4 is repeated in step S2.2 and S2.3, meets in step S2.2 and step S2.3 until all in infrared light image
It is required that pixel be all merged into some region, and this region is exactly doubtful flame region；
Doubtful flame region in former frame and this frame infrared light image is extracted using method of the S2.1 into S2.4 respectively.
4. the fire defector recognition methods according to claim 1 based on Infrared video image, which is characterized in that S3.4
In, the distance of two central points uses Euclidean distance, if O1(x1,y1) and O2(x2,y2) be respectively two target boundary rectangles center
Point, then the Euclidean distance calculation method of two central points are as follows:
D=sqrt ((x1-x2)2+(y1-y2)2) (1)。
5. the fire defector recognition methods according to claim 1 based on Infrared video image, which is characterized in that S4.1 packet
Include following steps:
S4.1.1 is obtained the same target of former frame infrared light image and this frame infrared light image by the object matching of step S3,
For the target area with same target in former frame infrared light image and this frame infrared light image, if the target is previous
Flame object has been determined as it before frame infrared light image or former frame infrared light image, judging should in this frame infrared light image
Whether there is also bright areas for target area；Wherein bright areas refer to the gray value that there is pixel in this region be greater than or
It is equal toThen the region is bright areas；
If there are bright for the target area in the S4.1.2 former frame infrared light image and this frame infrared light image with same target
Bright area, then the existence confidence level believe of the target area adds 2, then determines whether its confidence level believe that survives is greater than
200 or less than 0, if so, deleting this target, discharge the memory of the target；Otherwise, continue to retain this target；
If the target area in the S4.1.3 former frame infrared light image and this frame infrared light image with same target is not present
Bright areas, then the existence confidence level believe of the target area subtracts 2, then determines whether its confidence level believe that survives is greater than
200 or less than 0, if so, deleting this target, discharge the memory of the target；Otherwise continue to retain this target.
6. the fire defector recognition methods according to claim 1 based on Infrared video image, which is characterized in that S4.2 packet
Include following steps:
S4.2.1 is obtained the same target of former frame infrared light image and this frame infrared light image by the object matching of step S3,
If being not flagged as flame object and the target before the same target of former frame infrared light image and this frame infrared light image
For the fresh target that not doubtful flame region occurs judged in step S3, according to the position of the target in this frame infrared light image
It sets and updates doubtful flame information, and calculate the phase of same target in the doubtful flame regions of two adjacent two frames infrared light images
Guan Xing, the correlation calculations formula of same target are as follows:
In above formula, X1(n1,n2) be former frame infrared light image in some target certain point (n1,n2) pixel value, X2(n1,n2)
For the pixel value of this frame infrared light image identical point；M1And M2For the points of the horizontal and vertical pixel of single frames infrared light image；n1
And n2For the coordinate that certain in image is put, m1And m2For offset；
The influence of noise may make two frames false matches phenomenon occur, in order to eliminate this influence, to C (m1,m2) make at normalization
Reason, is positioned as after normalization
Wherein,WithRespectively indicate being averaged for the same target region of former frame infrared light image and this frame infrared light image
Pixel intensity value, it may be assumed that
If S4.2.2 related coefficientGreater than the threshold value T of setting, then this target existence confidence level believe subtracts 1,
And flame confidence level score subtracts 1；Whether the existence confidence level believe of target is greater than 200 or less than 0, if then deleting
This target discharges the memory of the target；
If S4.2.3 related coefficientLess than the threshold value T of setting, then confidence level of surviving score adds 1, believe's
Value plus 1, and flame information is updated, judge whether score at this time is greater than 10, if so, determining this target for flame object；
If score is not more than 10, judge whether the existence confidence level believe of target is greater than 200 or less than 0, if then deleting
This target discharges the memory of the target.
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| CN109147254B (en) * | 2018-07-18 | 2021-05-18 | 武汉大学 | Video field fire smoke real-time detection method based on convolutional neural network |
| 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 |
| CN110717419A (en) * | 2019-09-25 | 2020-01-21 | 浙江万胜智能科技股份有限公司 | Method for extracting flame characteristics from video image |
| CN110648490B (en) * | 2019-09-26 | 2021-07-27 | 华南师范大学 | Multi-factor flame identification method suitable for embedded platform |
| CN112465852B (en) * | 2020-12-03 | 2024-01-30 | 国网山西省电力公司晋城供电公司 | Improved region growing method for infrared image segmentation of power equipment |
| CN112560657B (en) * | 2020-12-12 | 2023-05-30 | 南方电网调峰调频发电有限公司 | Method, device, computer device and storage medium for identifying smoke and fire |
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