CN109028169A - A kind of stove and oil smoke concentration detection method with flame-out visual spatial attention function - Google Patents
A kind of stove and oil smoke concentration detection method with flame-out visual spatial attention function Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 121
- 239000000779 smoke Substances 0.000 title claims abstract description 55
- 230000000007 visual effect Effects 0.000 title claims abstract description 29
- 238000011897 real-time detection Methods 0.000 claims abstract description 12
- 239000011159 matrix material Substances 0.000 claims description 47
- 230000007797 corrosion Effects 0.000 claims description 18
- 238000005260 corrosion Methods 0.000 claims description 18
- 239000007789 gas Substances 0.000 claims description 18
- 238000000034 method Methods 0.000 claims description 18
- 238000003708 edge detection Methods 0.000 claims description 12
- 230000037081 physical activity Effects 0.000 claims description 12
- 238000003384 imaging method Methods 0.000 claims description 10
- 230000002093 peripheral effect Effects 0.000 claims description 10
- 239000003517 fume Substances 0.000 claims description 9
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- 239000000567 combustion gas Substances 0.000 claims description 4
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24C—DOMESTIC STOVES OR RANGES ; DETAILS OF DOMESTIC STOVES OR RANGES, OF GENERAL APPLICATION
- F24C3/00—Stoves or ranges for gaseous fuels
- F24C3/12—Arrangement or mounting of control or safety devices
- F24C3/126—Arrangement or mounting of control or safety devices on ranges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
- G01N15/075—Investigating concentration of particle suspensions by optical means
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Abstract
A kind of stove with flame-out visual spatial attention function is provided with vision-based detection module and stove body, and vision-based detection module is assemblied in hearth region and the visual field is electrically connected towards hearth, vision-based detection module and stove body.Stove body is provided with for controlling flame-out control device, and control device is assemblied in stove body and is electrically connected with vision-based detection module.Vision-based detection module is provided with the flame detection unit of real-time detection flame conditions, and flame detection unit is electrically connected with control device.The flame in flame detection unit identification hearth region obtains flame indication signal, then transmits flame indication signal to control device.The stove with flame-out visual spatial attention function, which has, carries out auto extinguishing when abnormal service condition generates flame, effectively prevent fire, improves the intelligence of stove.A kind of oil smoke concentration detection method, the influence of hardly examined distance, it can be achieved that oil smoke concentration non-contact real-time detection, have many advantages, such as high accuracy and real-time.
Description
Technical field
The present invention relates to stove field, in particular to a kind of stove and oil smoke concentration inspection with flame-out visual spatial attention function
Survey method.
Background technique
In the modern life, many families are all cooked using stove, but existing stove can not regard hearth
Feel monitoring, cannot more be stopped working by vision monitoring, hinder the intelligence of stove significantly.
Therefore in view of the shortcomings of the prior art, providing a kind of stove with flame-out visual spatial attention function and oil smoke concentration detection
Method is very necessary to solve prior art deficiency.
Summary of the invention
One of purpose of the invention is to avoid the deficiencies in the prior art place and provide a kind of with flame-out vision
The stove of control function.This has the advantages that the stove of flame-out visual spatial attention function has according to vision monitoring and auto extinguishing.
Above-mentioned purpose of the invention is realized by following technical measures:
One kind is provided and is provided with vision-based detection module and stove body, vision-based detection module is assemblied in hearth region and the visual field
Towards hearth, vision-based detection module and stove body electrical connection.
The stove body is provided with for controlling flame-out control device, control device be assemblied in stove body and with view
Feel detection module electrical connection.
The vision-based detection module is provided with the flame detection unit of real-time detection flame conditions, flame detection unit and control
Device electrical connection processed.
The flame in flame detection unit identification hearth region obtains flame indication signal, then transmits fire to control device
Flame indication signal.
Preferably, above-mentioned vision-based detection module, which is provided with, is additionally provided with real-time detection hearth and hearth peripheral region manpower
The human bioequivalence unit of operation or physical activity situation, human bioequivalence unit are electrically connected with control device.
Preferably, the picture of above-mentioned human bioequivalence unit acquisition hearth and hearth peripheral region, then identify hearth with
And hearth peripheral region manpower operates perhaps physical activity and obtains standby signal, people when no manpower operates or physical activity
Body recognition unit simultaneously will be prompted to signal and be sent to control device, and control device receives standby signal.
Preferably, the flame-out component of above-mentioned stove body setting, flame-out component be electrically connecteds with control device, flame-out component and
Gas pipeline connection.
Preferably, above-mentioned control device is provided with the timing unit for timing, and timing unit is electrically connected with flame-out component.
Control device real-time reception to the flame indication signal of flame detection unit and the standby signal of human bioequivalence unit,
Timing unit starts timing simultaneously, when flame detection unit persistently sends the prompt letter of flame indication signal and human bioequivalence unit
Number time simultaneously when being more than threshold value, timing unit sends misfire signals to flame-out component again, and the component that stops working receives misfire signals
The combustion gas operation of cutting gas pipeline is carried out afterwards.
Preferably, the value range of above-mentioned threshold value is 10~100 seconds.
Preferably, above-mentioned vision-based detection module is handled and is serialized by the initial pictures acquired, is passed sequentially through
The initial pictures of frame and the initial pictures of previous frame are handled afterwards, and obtain the moment locating for each rear frame initial pictures works as forward galley
Oil smoke concentration.
Preferably, above-mentioned vision-based detection module is provided with apparatus main body, vision-based detection portion and prevents oil smoke or steam close
The positive splenium in vision-based detection portion, vision-based detection portion and positive laminate section are not assemblied in apparatus main body.
Preferably, above-mentioned apparatus main body is provided with wind cavity portion, and vision-based detection portion is defined as top towards shooting area, depending on
Feel that test section is assemblied in the lower section of wind cavity portion.
Preferably, the vision lens in above-mentioned vision-based detection portion pass through the through-hole and upward of wind cavity portion.
Preferably, above-mentioned positive splenium is assemblied in the top of wind cavity portion and the small air outlet of positive splenium towards wind cavity portion.
Preferably, above-mentioned wind cavity portion, which is provided with, generates the first wind chamber of air-flow and for from for accommodating positive splenium
The second wind chamber that the gas that one wind chamber air-flow enters raises speed, positive splenium are assemblied in the first wind chamber, vision lens position
In the second wind chamber interior, the first wind chamber and the second wind chamber.
Preferably, above-mentioned apparatus main body is additionally provided with upper cover and lower cover, top of the upper cover fixing buckle together in wind cavity portion, lower cover
It is assemblied in the bottom in vision-based detection portion.
Preferably, above-mentioned upper cover is provided with the small air inlet matched with positive splenium and small air outlet, vision lens pass through
Small air inlet and with the surface of upper cover maintain an equal level.
The stove with flame-out visual spatial attention function of the invention, is provided with vision-based detection module and stove body, vision
Detection module is assemblied in hearth region and the visual field is electrically connected towards hearth, vision-based detection module and stove body.The stove master
Body is provided with for controlling flame-out control device, and control device is assemblied in stove body and is electrically connected with vision-based detection module；
The vision-based detection module is provided with the flame detection unit of real-time detection flame conditions, flame detection unit and control device electricity
Connection.The flame in flame detection unit identification hearth region obtains flame indication signal, then transmits flame to control device
Indication signal.The stove with flame-out visual spatial attention function, which has, carries out automatic extinguishing when abnormal service condition generates flame
Fire effectively prevent fire, improves the intelligence of stove.
Another goal of the invention of the invention is to avoid the deficiencies in the prior art place and provide a kind of oil smoke concentration detection
Method.The oil smoke concentration detection method has the characteristics that detection is real-time, oil smoke concentration testing result accuracy is high.
A kind of oil smoke concentration detection method is provided, the stove with flame-out visual spatial attention function with such as features described above,
Vision-based detection module is handled based on the initial pictures that imaging device acquires, and initial pictures are grayscale image, is acquired
Initial pictures be serialized, the initial pictures of the initial pictures and previous frame that pass sequentially through rear frame are handled, obtain it is each after
The current kitchen fume concentration at moment locating for frame initial pictures.
It is handled every time by the initial pictures of rear frame and the initial pictures of previous frame, when obtaining locating for rear frame initial pictures
The step process for the current kitchen fume concentration carved is as follows:
(1) initial pictures of rear frame and the initial pictures of previous frame frame difference is carried out to handle to obtain frame difference image；
(2) denoising is carried out to frame difference image in a manner of opening operation, obtains denoising image；
(3) edge detection is carried out to denoising image, marker motion region is as initial area-of-interest；
(4) gray average calculating is carried out to initial area-of-interest and segment smoothing degree calculates, it is equal gray scale will to be met simultaneously
The region of value and smoothness requirements is as next step area-of-interest, and other regions are as interference elimination；
(5) area-of-interest extracted to step (4) carries out statistics of histogram respectively, is divided according to statistical result
Oil smoke concentration grade.
In step (1), to collected initial pictures carry out frame difference operate to obtain frame difference image be specifically:
Vision-based detection module does a later frame image with previous frame image according to the sequencing of the initial pictures received
Difference obtains the highlighted frame difference image in dynamic area；
Preferably, above-mentioned steps (2) carry out denoising using opening operation to frame difference image, obtain denoising image, specifically
It carries out in the following way: etching operation first being carried out to frame difference image, to eliminate noise and the tiny spine in image, disconnect narrow
Small connection；Expansive working is carried out to the image after corrosion again, restores the smoke characteristics in former frame difference image.
Preferably, above-mentioned steps (3) carry out edge detection to denoising image, and marker motion region is as initial region of interest
Domain, specifically: utilizing wavelet transformation, detect the edge of frame difference image highlight regions and be marked, the region marked is made
For initial area-of-interest.
Preferably, above-mentioned steps (4) are specifically to carry out gray average, segment smoothing degree meter to each initial area-of-interest
It calculates, obtains the corresponding gray average of each initial area-of-interest and gray scale smoothness, the gray scale being calculated will be met simultaneously
Mean value is less than gray threshold, gray scale smoothness is less than the initial area-of-interest of gray scale smoothness threshold as area-of-interest,
Other initial area-of-interests are determined as interference region.
Preferably, the area-of-interest extracted in above-mentioned steps (5) to step (4) carries out grey level histogram system respectively
Meter divides oil smoke concentration grade according to statistical result, specifically.
By all pixels in region of interest area image, according to the size of gray value, the frequency of its appearance is counted；
Further according to the concentration scale quantity that needs divide, 10 are taken as siding-to-siding block length, counts the pixel in each gray scale interval
Number is put, the corresponding oil smoke that divides of the pixel number in each gray scale interval is corresponding concentration scale.
The target area of imaging device acquisition indicates that any one frame initial pictures are the imaging of corresponding region S with region S.
Initial pictures are made of m*n pixel.
The gray value of the pixel of frame initial pictures A is indicated afterwards with matrix A H, AH={ ahi,j, ahi,jFrame initial graph after representative
As the i-th row, the corresponding gray value of jth column pixel in A, i is the row where pixel, and j is the column where pixel, 1≤i≤m, 1≤j
≤n；The subregion in frame initial pictures A where the i-th row, jth column pixel is AS afterwardsi,j。
The gray value of the pixel of previous frame initial pictures B indicates with matrix B H, BH={ bhi,j, bhi,jRepresent previous frame initial graph
As the i-th row, the corresponding gray value of jth column pixel in B, the subregion in previous frame initial pictures B where the i-th row, jth column pixel is
BSi,j。
The grey scale pixel value of frame difference image D indicates with matrix D H, DH={ dhi,j}={ ahi,j-bhi,j, dhi,jRepresent frame
I-th row, the corresponding gray value of jth column pixel in difference image D, the subregion in frame difference image D where the i-th row, jth column pixel are
DSi,j。
In frame difference image, | dhi,j|=0 region is in black；|dhi,j| ≠ 0 region is in be highlighted.
Etching operation is carried out to frame difference image in step (2), is specifically comprised the following steps:
2-11 arbitrarily defines a convolution kernel θ；
Convolution kernel θ and frame difference image are carried out convolution by 2-12；When convolution kernel θ traverses frame difference image, convolution kernel institute is extracted
The pixel grey scale minimum value p of the convolution results and pixel C being overlapped with convolution kernel center in overlay area；
The gray scale of pixel C passes through Matrix C H={ ck,qIndicate, k, q are the row serial number and column serial number of pixel C,
Obtain the convolution results minimum value pixel matrix P obtained in convolution kernel θ traversal frame difference image process, minimum value
The gray scale of pixel matrix P passes through matrix PH={ pk,qIndicate；
The corresponding imparting pixel C of the gray scale of pixel matrix P is obtained corrosion image by 2-13；
Expansive working is carried out to corrosion image in step (2), is specifically comprised the following steps:
2-21 arbitrarily defines a convolution kernel β；
Convolution kernel β and corrosion image are carried out convolution by 2-22；When convolution kernel β traverses corrosion image, convolution kernel institute is extracted
The pixel grey scale maximum value o of the convolution results and pixel R being overlapped with convolution kernel center in overlay area；
The gray scale of pixel R passes through matrix RH={ rl,vIndicate, l, v are the row serial number and column serial number of pixel R,
Obtain the convolution results maximum value pixel matrix O obtained in convolution kernel β traversal corrosion image process, maximum value
The gray scale of pixel matrix O passes through matrix OH={ ol,vIndicate；
The corresponding imparting pixel R of the gray scale of maximum value pixel matrix O is obtained expanding image, obtained expansion by 2-13
Image is to denoise image.
Preferably, above-mentioned steps (3) carry out as follows:
3-1 defines a filter Y, and filter is t*t matrix, and t is odd number；
3-2 makes filter Y traversal denoising image, calculates filter and go where the central pixel point at each position
It makes an uproar the gray values of other pixels in the gray value and center pixel vertex neighborhood of image, and filter is calculated according to formula (I)
The edge detection value X of central pixel point at each positionz, z is label when filter Y traversal denoises image,
F, g is the matrix serial number of pixel, the pixel institute that 1≤f≤t, 1≤g≤t, e are filter at each position
Denoising image gray value；α is weight coefficient, corresponding with filter location；
3-3, by central pixel point edge detection value X of the filter at each positionzWith center pixel vertex neighborhood its
The gray value of its pixel subtracts each other, and judges whether the absolute value of difference is greater than threshold value Δ；
Statistics is greater than the quantity of threshold value, if quantity is more thanDetermine the central pixel point pair of filter present position
The pixel position for the denoising image answered is marginal point, and is marked；
3-4, complete denoising image of filter traversal, obtains the markd marginal point of institute, obtains preliminary area-of-interest.
Preferably, above-mentioned t is 3.
Oil smoke concentration detection method of the invention provides a kind of one kind for being different from infrared projection method and physical measure
Oil smoke concentration detection method.The oil smoke concentration detection method, the influence of hardly examined distance, it can be achieved that oil smoke concentration it is non-
Real-time detection is contacted, has many advantages, such as high accuracy and real-time.
Detailed description of the invention
Using attached drawing, the present invention is further illustrated, but the content in attached drawing is not constituted to any limit of the invention
System.
Fig. 1 is that a kind of stove signal with flame-out visual spatial attention function of the present invention transmits relationship.
Fig. 2 is the schematic cross-section of the vision-based detection module of embodiment 2.
Fig. 3 is vision-based detection module decomposition diagram.
Fig. 4 is the air current flow direction schematic diagram in Fig. 2.
Fig. 5 is the oil smoke region of method segmentation of the invention and the schematic diagram of interference region.
Fig. 1 includes into Fig. 5:
Vision-based detection module 1,
Apparatus main body 11,
Wind cavity portion 111, the first wind chamber 1111, the second wind chamber 1112,
Upper cover 112, small air inlet 1121, small air outlet 1122,
Lower cover 113,
Positive splenium 12,
Vision-based detection portion 13, vision lens 131.
Specific embodiment
Technical solution of the present invention is described further with the following Examples.
Embodiment 1.
A kind of stove with flame-out visual spatial attention function, is provided with vision-based detection module 1 and stove master as shown in Figure 1
Body, vision-based detection module 1 is assemblied in hearth region and the visual field is electrically connected towards hearth, vision-based detection module and stove body.
Stove body is provided with for controlling flame-out control device, and control device is assemblied in stove body and examines with vision
Module 1 is surveyed to be electrically connected.
Vision-based detection module 1 is provided with the flame detection unit of real-time detection flame conditions, flame detection unit and control
Device electrical connection.
The flame in flame detection unit identification hearth region obtains flame indication signal, then refers to control device transmission flame
Show signal.
Vision-based detection module 1, which is provided with, is additionally provided with real-time detection hearth and the operation of hearth peripheral region manpower or people
The human bioequivalence unit of body activity condition, human bioequivalence unit are electrically connected with control device.
Human bioequivalence unit acquires the picture of hearth and hearth peripheral region, then identifies hearth and hearth peripheral region
Domain manpower operates perhaps physical activity and obtains standby signal when no manpower operates or physical activity, and human bioequivalence unit is simultaneously
It will be prompted to signal and be sent to control device, control device receives standby signal.
The flame-out component of stove body setting, flame-out component are electrically connected with control device, and flame-out component and gas pipeline connect
It connects.
Control device is provided with the timing unit for timing, and timing unit is electrically connected with flame-out component.
Control device real-time reception to the flame indication signal of flame detection unit and the standby signal of human bioequivalence unit,
Timing unit starts timing simultaneously, when flame detection unit persistently sends the prompt letter of flame indication signal and human bioequivalence unit
Number time simultaneously when being more than threshold value, timing unit sends misfire signals to flame-out component again, and the component that stops working receives misfire signals
The combustion gas operation of cutting gas pipeline is carried out afterwards.
The value range of threshold value of the present invention is 10~100 seconds.The value of the threshold value of the present embodiment is 40 seconds.It should be noted that this
The value of the threshold value of invention can be 40 seconds, or any number within the scope of 10~100 seconds, specific embodiment according to
Depending on actual conditions.
Vision-based detection module 1 is handled and is serialized by the initial pictures acquired, and the initial of rear frame is passed sequentially through
Image and the initial pictures of previous frame are handled, and the current kitchen fume concentration at moment locating for each rear frame initial pictures is obtained.
Process of the invention is as follows: when flame detection unit has found flame, flame detection unit is passed to control device
Defeated flame indication signal；When the operation of no manpower or physical activity, human bioequivalence unit obtains standby signal, human bioequivalence list
Member simultaneously will be prompted to signal and be sent to control device, and control device receives standby signal.Timing unit starts timing simultaneously, works as flame
Detection unit persistently sends the time of the standby signal of flame indication signal and human bioequivalence unit while when more than 40 second, timing
Unit sends misfire signals to flame-out component, and the combustion gas operation of cutting gas pipeline is carried out after flame-out component reception misfire signals.
It is most of under normal circumstances, stove can all have the blocking of cookware when cooking, and vision-based detection module will not be direct
Monitor open fire, and when user forgets that Guan Huohou, the lasting excessive high-temp combustion of cookware can generate open fire.Human body is known simultaneously
Other unit detection hearth and the operation of hearth peripheral region manpower perhaps physical activity when there is no manpower to operate or physical activity
When, determine the culinary art of non-user and cookware generates flame, when the two to the time that control device sends signal be more than simultaneously threshold value,
It is judged as empty burning or dry-fire condition, stove is detected by flame detection unit and carries out quenching operations, and fire can be effectively prevented
Generation.
This has the stove of flame-out visual spatial attention function, is provided with vision-based detection module 1 and stove body, vision-based detection mould
Block 1 is assemblied in hearth region and the visual field is electrically connected towards hearth, vision-based detection module 1 and stove body.The stove body is set
It is equipped with for controlling flame-out control device, control device is assemblied in stove body and is electrically connected with vision-based detection module 1；It is described
Vision-based detection module 1 is provided with the flame detection unit of real-time detection flame conditions, and flame detection unit is electrically connected with control device
It connects.The flame in flame detection unit identification hearth region obtains flame indication signal, then refers to control device transmission flame
Show signal.The stove with flame-out visual spatial attention function, which has, carries out automatic extinguishing when abnormal service condition generates flame
Fire effectively prevent fire, improves the intelligence of stove.
Embodiment 2.
A kind of stove with flame-out visual spatial attention function, as shown in Figures 2 to 4, other features are same as Example 1, no
Be with place: vision-based detection module 1 is provided with apparatus main body 11, vision-based detection portion 13 and prevents oil smoke or steam close to vision
The positive splenium 12 of test section 13, vision-based detection portion 13 and positive splenium 12 are assemblied in apparatus main body 11 respectively.
Apparatus main body 11 is provided with wind cavity portion 111, and vision-based detection portion 13 is defined as top, vision inspection towards shooting area
Survey portion 13 is assemblied in the lower section of wind cavity portion 111.
The vision lens 131 in vision-based detection portion 13 pass through the through-hole and upward of wind cavity portion 111.Positive splenium 12 is assemblied in
The small air outlet 1122 of the top of wind cavity portion 111 and positive splenium 12 is towards wind cavity portion 111.
Wind cavity portion 111, which is provided with, generates the first wind chamber 1111 of air-flow and for from first for accommodating positive splenium 12
The second wind chamber 1112 that the gas that 1111 air-flow of wind chamber enters raises speed, positive splenium 12 are assemblied in the first wind chamber
1111, vision lens 131 are located inside the second wind chamber 1112, and the first wind chamber 1111 is connected to the second wind chamber 1112.
Apparatus main body 11 is additionally provided with upper cover 112 and lower cover 113,112 fixing buckle of upper cover together in wind cavity portion 111 top,
Lower cover 113 is assemblied in the bottom in vision-based detection portion 13.
Upper cover 112 is provided with the small air inlet 1121 and small air outlet 1122 matched with positive splenium 12, vision lens 131
Maintain an equal level across small air inlet 1121 and with the surface of upper cover 112.
The air-flow flow process of vision-based detection module 1 of the invention is as follows: small air inlet of the positive splenium 12 from upper cover 112
1121 sucking gases, positive splenium 12 again arrange gas to the first wind cavity, and gas flows into the second wind chamber from the first wind chamber 1111
Room 1112, because the unappropriated volume of the second wind chamber 1112 is less than the unappropriated volume of the second wind chamber 1112,
Gas is raised speed in the second wind chamber 1112, gap of the gas to be raised speed using vision lens 131 and cone structure, gas
Body finally at full throttle leaves the positive pressure anti-soil type sighting device, and gas is formed centainly between vision lens 131 and smog
Positive pressure, so that smog can not contact vision lens 131.
Compared with Example 1, the positive splenium 12 of the vision-based detection module 1 of the present embodiment stove generates gas high speed from vision
The surface of the vision lens 131 of detection module 1 is flowed through, to form certain positive pressure between vision lens 131 and smog, is made
Vision lens 131 can not be contacted by obtaining smog.The vision-based detection module 1 can prevent the attachment of oil smoke or steam.
Embodiment 3.
A kind of oil smoke concentration detection method, vision-based detection module 1 based on the initial pictures that imaging device acquires into
Row processing, initial pictures are grayscale image, and initial pictures collected are serialized, and pass sequentially through the initial pictures and previous frame of rear frame
Initial pictures handled, obtain it is each after the moment locating for frame initial pictures current kitchen fume concentration.In this way,
The oil smoke concentration situation that can also obtain the present frame moment in real time also can according to need even if monitoring each moment current frame image
Oil smoke concentration situation.
It is handled every time by the initial pictures of rear frame and the initial pictures of previous frame, when obtaining locating for rear frame initial pictures
The step process for the current kitchen fume concentration carved is as follows:
(1) initial pictures of rear frame and the initial pictures of previous frame frame difference is carried out to handle to obtain frame difference image；
(2) denoising is carried out to frame difference image in a manner of opening operation, obtains denoising image；
(3) edge detection is carried out to denoising image, marker motion region is as initial area-of-interest；
(4) gray average calculating is carried out to initial area-of-interest and segment smoothing degree calculates, it is equal gray scale will to be met simultaneously
The region of value and smoothness requirements is as next step area-of-interest, and other regions are as interference elimination；
(5) area-of-interest extracted to step (4) carries out statistics of histogram respectively, is divided according to statistical result
Oil smoke concentration grade.Statistical method can be statistics of histogram, also can choose other statistical methods.
In step (1), to collected initial pictures carry out frame difference operate to obtain frame difference image be specifically: vision-based detection mould
A later frame image is made the difference with previous frame image according to the sequencing of the initial pictures received, obtains dynamic area height by block 1
Bright frame difference image.Due in the two field pictures of front and back static region be it is constant, (such as oil smoke drifts, and manpower is waved for dynamic area
Move) it is variation, so black is presented in static region after frame difference, the highlight bar of edge blurry is shown as after dynamic area frame difference
Domain, therefore the frame difference image highlighted by the available dynamic area of frame difference.
The target area of imaging device acquisition indicates that any one frame initial pictures are the imaging of corresponding region S with region S；
Initial pictures are made of m*n pixel.
The gray value of the pixel of frame initial pictures A is indicated afterwards with matrix A H, AH={ ahi,j, ahi,jFrame initial graph after representative
As the i-th row, the corresponding gray value of jth column pixel in A, i is the row where pixel, and j is the column where pixel, 1≤i≤m, 1≤j
≤n；The subregion in frame initial pictures A where the i-th row, jth column pixel is AS afterwardsi,j。
The gray value of the pixel of previous frame initial pictures B indicates with matrix B H, BH={ bhi,j, bhi,jRepresent previous frame initial graph
As the i-th row, the corresponding gray value of jth column pixel in B, the subregion in previous frame initial pictures B where the i-th row, jth column pixel is
BSi,j。
The grey scale pixel value of frame difference image D indicates with matrix D H, DH={ dhi,j}={ ahi,j-bhi,j, dhi,jRepresent frame
I-th row, the corresponding gray value of jth column pixel in difference image D, the subregion in frame difference image D where the i-th row, jth column pixel are
DSi,j；
In frame difference image, | dhi,j|=0 region is in black；|dhi,j| ≠ 0 region is in be highlighted.
After the operation of frame difference, (2) are entered step.Denoising is carried out using opening operation to frame difference image, obtains denoising image,
It is carried out especially by such as under type: etching operation first being carried out to frame difference image, to eliminate noise and the tiny spine in image, broken
Open narrow connection；Expansive working is carried out to the image after corrosion again, restores the smoke characteristics in former frame difference image.
Etching operation is carried out to frame difference image in step (2), is specifically comprised the following steps:
2-11 arbitrarily defines a convolution kernel θ；
Convolution kernel θ and frame difference image are carried out convolution by 2-12；When convolution kernel θ traverses frame difference image, convolution kernel institute is extracted
The pixel grey scale minimum value p of the convolution results and pixel C being overlapped with convolution kernel center in overlay area；
The gray scale of pixel C passes through Matrix C H={ ck,qIndicate, k, q are the row serial number and column serial number of pixel C,
Obtain the convolution results minimum value pixel matrix P obtained in convolution kernel θ traversal frame difference image process, minimum value
The gray scale of pixel matrix P passes through matrix PH={ pk,qIndicate；
The corresponding imparting pixel C of the gray scale of pixel matrix P is obtained corrosion image by 2-13.
Expansive working is carried out to corrosion image in step (2), is specifically comprised the following steps:
2-21 arbitrarily defines a convolution kernel β；
Convolution kernel β and corrosion image are carried out convolution by 2-22；When convolution kernel β traverses corrosion image, convolution kernel institute is extracted
The pixel grey scale maximum value o of the convolution results and pixel R being overlapped with convolution kernel center in overlay area；
The gray scale of pixel R passes through matrix RH={ rl,vIndicate, l, v are the row serial number and column serial number of pixel R,
Obtain the convolution results maximum value pixel matrix O obtained in convolution kernel β traversal corrosion image process, maximum value
The gray scale of pixel matrix O passes through matrix OH={ ol,vIndicate；
The corresponding imparting pixel R of the gray scale of maximum value pixel matrix O is obtained expanding image, obtained expansion by 2-13
Image is to denoise image.
Image noise can be eliminated using opening operation, the separating objects at very thin point, smooth biggish object boundary, simultaneously
Also it can guarantee that the area of highlight regions in original image is basically unchanged, guarantee that the accuracy of subsequent detection is unaffected.
Step (3) carries out edge detection to denoising image, and marker motion region is as initial area-of-interest, specifically:
Using wavelet transformation, the edge for detecting frame difference image highlight regions is simultaneously marked, using the region marked as initially feeling emerging
Interesting region.
Since the gray value of image border and the gray value of neighbor pixel can generate biggish gray value gradient, according to side
This feature of edge sets a filter, traverses frame difference image with the filter.Step (3) carries out as follows:
3-1 defines a filter Y, and filter is t*t matrix, and t is odd number.Filter selects odd matrix, to ensure
Only one central point, preferably 3*3 matrix, have the characteristics that calculation amount is small.
3-2 makes filter Y traversal denoising image, calculates filter and go where the central pixel point at each position
It makes an uproar the gray values of other pixels in the gray value and center pixel vertex neighborhood of image, and filter is calculated according to formula (I)
The edge detection value X of central pixel point at each positionz, z is label when filter Y traversal denoises image,
F, g is the matrix serial number of pixel, the pixel institute that 1≤f≤t, 1≤g≤t, e are filter at each position
Denoising image gray value；α is weight coefficient, corresponding with filter location.
3-3, by central pixel point edge detection value X of the filter at each positionzWith center pixel vertex neighborhood its
The gray value of its pixel subtracts each other, and judges whether the absolute value of difference is greater than threshold value Δ；
Statistics is greater than the quantity of threshold value, if quantity is more thanDetermine the central pixel point pair of filter present position
The pixel position for the denoising image answered is marginal point, and is marked；
3-4, complete denoising image of filter traversal, obtains the markd marginal point of institute, obtains preliminary area-of-interest.
Because people is when cooking operation, hand can brandished always, can include oil smoke and manpower in the image after frame difference is complete
The interference region of the moving objects such as operation, needs the influence in exclusive PCR region, this is also before carrying out oil smoke concentration identification
Where the difficult point of the invention patent.
But the direction of motion of oil smoke has randomness, the direction of motion of manpower, slice is relatively unambiguous and feature is different,
Numerically performance is exactly that grey value difference is larger, thus:
1) oil smoke moving region is lower than the brightness of manpower, slice moving region on the image after frame difference, so corresponding oil
The gray value mean value in cigarette district domain is also below manpower, the gray average of slice moving region；
2) grey value profile of oil smoke moving region is relatively concentrated on the image after frame difference, and the moving region of manpower, slice
The gray value on boundary is larger compared with the jump of the central area in region, so the image in the region is not smooth enough, corresponding gray value
Variance is larger.
Using the two characteristics, step (4) is specifically to carry out gray average, segment smoothing to each initial area-of-interest
Degree calculates, and obtains the corresponding gray average of each initial area-of-interest and gray scale smoothness, and satisfaction simultaneously is calculated
Gray average is less than gray threshold, gray scale smoothness is less than the initial area-of-interest of gray scale smoothness threshold as region of interest
Other initial area-of-interests are determined as interference region by domain.
Gray threshold, gray scale smoothness threshold magnitude can flexible setting according to specific needs, details are not described herein.Step
Suddenly (4) complete the identification in oil smoke region and the exclusion of interference region.
Fig. 5 illustrates the schematic diagram in oil smoke region and interference region that one is divided using method of the invention, it is seen then that this
The method of invention can effectively exclude interference region.
The area-of-interest extracted in step (5) to step (4) carries out statistics of histogram respectively, is tied according to statistics
Fruit divides oil smoke concentration grade, specifically:
By all pixels in region of interest area image, according to the size of gray value, the frequency of its appearance is counted；
Further according to the concentration scale quantity that needs divide, 10 are taken as siding-to-siding block length, counts the pixel in each gray scale interval
Number is put, the corresponding oil smoke that divides of the pixel number in each gray scale interval is corresponding concentration scale.
It should be noted that the selection of siding-to-siding block length is not limited to 10, other quantity also can choose.
The criteria for classifying of oil smoke concentration can specifically be set, such as setting dense smoke, medium grade cigarette or low cigarette, specific value with
Subject to actual demand, details are not described herein.
Oil smoke concentration detection method of the invention provides a kind of one kind for being different from infrared projection method and physical measure
Oil smoke concentration detection method.The oil smoke concentration detection method, the influence of hardly examined distance, it can be achieved that oil smoke concentration it is non-
Real-time detection is contacted, has many advantages, such as high accuracy and real-time.
Oil smoke concentration detection method of the present invention, can be set in external environment, acquire furnace by the imaging device of setting
Have the image in kitchen range region, and be delivered to vision-based detection module 1, vision-based detection module 1 conveys the oil smoke hierarchical organization of processing
To main control unit, main control unit controls the firepower size of stove according to oil smoke grade.More accurately kitchen fume is controlled
System processing.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention rather than protects to the present invention
The limitation of range, although the invention is described in detail with reference to the preferred embodiments, those skilled in the art should be managed
Solution, can be with modifying or equivalently replacing the technical solution of the present invention, without departing from the essence and model of technical solution of the present invention
It encloses.
Claims (10)
1. a kind of stove with flame-out visual spatial attention function, it is characterised in that: it is provided with vision-based detection module and stove body,
Vision-based detection module is assemblied in hearth region and the visual field is electrically connected towards hearth, vision-based detection module and stove body；
The stove body is provided with for controlling flame-out control device, and control device is assemblied in stove body and examines with vision
Survey module electrical connection；
The vision-based detection module is provided with the flame detection unit of real-time detection flame conditions, and flame detection unit and control fill
Set electrical connection；
The flame in flame detection unit identification hearth region obtains flame indication signal, then refers to control device transmission flame
Show signal.
2. the stove with flame-out visual spatial attention function according to claim 1, it is characterised in that: the vision-based detection mould
Block is provided with the human body knowledge for being additionally provided with real-time detection hearth and the operation of hearth peripheral region manpower or physical activity situation
Other unit, human bioequivalence unit are electrically connected with control device；
The picture of the human bioequivalence unit acquisition hearth and hearth peripheral region, then identifies hearth and hearth peripheral region
Domain manpower operates perhaps physical activity and obtains standby signal when no manpower operates or physical activity, and human bioequivalence unit is simultaneously
It will be prompted to signal and be sent to control device, control device receives standby signal.
3. the stove with flame-out visual spatial attention function according to claim 2, it is characterised in that: the stove body is set
It sets with flame-out component, the component that stops working is electrically connected with control device, and flame-out component is connect with gas pipeline；
The control device is provided with the timing unit for timing, and timing unit is electrically connected with flame-out component；
Control device real-time reception is to the flame indication signal of flame detection unit and the standby signal of human bioequivalence unit, simultaneously
Timing unit starts timing, when flame detection unit persistently sends the standby signal of flame indication signal and human bioequivalence unit
When time is more than threshold value simultaneously, timing unit sends misfire signals to flame-out component again, and it is laggard that the component that stops working receives misfire signals
The combustion gas operation of row cutting gas pipeline.
4. the stove with flame-out visual spatial attention function according to claim 3, it is characterised in that: the value model of the threshold value
Enclose is 10~100 seconds；
The vision-based detection module is handled and is serialized by the initial pictures acquired, and the initial graph of rear frame is passed sequentially through
Picture and the initial pictures of previous frame are handled, and the current kitchen fume concentration at moment locating for each rear frame initial pictures is obtained；
The vision-based detection module is provided with apparatus main body, vision-based detection portion and prevents oil smoke or steam close to vision-based detection portion
Positive splenium, vision-based detection portion and positive laminate section are not assemblied in apparatus main body.
5. the stove with flame-out visual spatial attention function according to claim 4, it is characterised in that: described device main body is set
It is equipped with wind cavity portion, vision-based detection portion is defined as top towards shooting area, vision-based detection portion is assemblied in the lower section of wind cavity portion；
The vision lens in the vision-based detection portion pass through the through-hole and upward of wind cavity portion；
The positive splenium is assemblied in the small air outlet of the top of wind cavity portion and positive splenium towards wind cavity portion.
6. the stove with flame-out visual spatial attention function according to claim 5, it is characterised in that: the wind cavity portion setting
Have and generates the first wind chamber of air-flow and for mentioning to the gas entered from the first wind chamber air-flow for accommodating positive splenium
Second wind chamber of speed, positive splenium are assemblied in the first wind chamber, and vision lens are located at the second wind chamber interior, the first wind chamber and
Second wind chamber.
7. the stove with flame-out visual spatial attention function according to claim 6, it is characterised in that: described device main body is also
It is provided with upper cover and lower cover, for upper cover fixing buckle together in the top of wind cavity portion, lower cover is assemblied in the bottom in vision-based detection portion；
The upper cover is provided with the small air inlet and small air outlet matched with positive splenium, vision lens pass through small air inlet and with
The surface of upper cover maintains an equal level.
8. a kind of oil smoke concentration detection method, which is characterized in that having with such as claim 1 to 7 any one feature is put out
The stove of fiery visual spatial attention function, vision-based detection module are handled based on the initial pictures that imaging device acquires, just
Beginning image is grayscale image, and initial pictures collected are serialized, and passes sequentially through the initial pictures of rear frame and the initial graph of previous frame
As being handled, the current kitchen fume concentration at moment locating for each rear frame initial pictures is obtained；
It is handled every time by the initial pictures of rear frame and the initial pictures of previous frame, obtains the moment locating for rear frame initial pictures
The step process of current kitchen fume concentration is as follows:
(1) initial pictures of rear frame and the initial pictures of previous frame frame difference is carried out to handle to obtain frame difference image；
(2) denoising is carried out to frame difference image in a manner of opening operation, obtains denoising image；
(3) edge detection is carried out to denoising image, marker motion region is as initial area-of-interest；
(4) gray average calculating and segment smoothing degree is carried out to initial area-of-interest to calculate, will meet simultaneously gray average and
The region of smoothness requirements is as next step area-of-interest, and other regions are as interference elimination；
(5) area-of-interest extracted to step (4) carries out statistics of histogram respectively, divides oil smoke according to statistical result
Concentration scale.
9. oil smoke concentration detection method according to claim 8, which is characterized in that in step (1), to collected initial
Image progress frame difference operates to obtain frame difference image:
Vision-based detection module makes the difference a later frame image with previous frame image according to the sequencing of the initial pictures received,
Obtain the highlighted frame difference image in dynamic area；
The step (2) carries out denoising using opening operation to frame difference image, denoising image is obtained, especially by such as under type
It carries out: etching operation first being carried out to frame difference image and disconnects narrow connection to eliminate noise and the tiny spine in image；Again
Expansive working is carried out to the image after corrosion, restores the smoke characteristics in former frame difference image；
The step (3) carries out edge detection to denoising image, and marker motion region is as initial area-of-interest, specifically:
Using wavelet transformation, the edge for detecting frame difference image highlight regions is simultaneously marked, using the region marked as initially feeling emerging
Interesting region；
The step (4) is specifically to carry out gray average, the calculating of segment smoothing degree to each initial area-of-interest, is obtained each
The initial corresponding gray average of area-of-interest and gray scale smoothness will meet the gray average being calculated simultaneously and be less than gray scale
Threshold value, gray scale smoothness are less than the initial area-of-interest of gray scale smoothness threshold as area-of-interest, by other initial senses
Interest region is determined as interference region；
The area-of-interest extracted in the step (5) to step (4) carries out statistics of histogram respectively, is tied according to statistics
Fruit divides oil smoke concentration grade, specifically:
By all pixels in region of interest area image, according to the size of gray value, the frequency of its appearance is counted；
Further according to the concentration scale quantity that needs divide, 10 are taken as siding-to-siding block length, count the pixel in each gray scale interval
It counts, the corresponding oil smoke that divides of the pixel number in each gray scale interval is corresponding concentration scale.
10. oil smoke concentration detection method according to claim 9, which is characterized in that the target area of imaging device acquisition
It is indicated with region S, any one frame initial pictures are the imaging of corresponding region S；
Initial pictures are made of m*n pixel,
The gray value of the pixel of frame initial pictures A is indicated afterwards with matrix A H, AH={ ahi,j, ahi,jFrame initial pictures A after representative
In the i-th row, the corresponding gray value of jth column pixel, i be pixel where row, j be pixel where column, 1≤i≤m, 1≤j≤
n；The subregion in frame initial pictures A where the i-th row, jth column pixel is AS afterwardsi,j；
The gray value of the pixel of previous frame initial pictures B indicates with matrix B H, BH={ bhi,j, bhi,jRepresent previous frame initial pictures B
In the i-th row, the corresponding gray value of jth column pixel, the subregion in previous frame initial pictures B where the i-th row, jth column pixel is
BSi,j；
The grey scale pixel value of frame difference image D indicates with matrix D H, DH={ dhi,j}={ ahi,j-bhi,j, dhi,jRepresent frame difference figure
As the i-th row, the corresponding gray value of jth column pixel in D, the subregion in frame difference image D where the i-th row, jth column pixel is
DSi,j；
In frame difference image, | dhi,j|=0 region is in black；|dhi,j| ≠ 0 region is in be highlighted；
Etching operation is carried out to frame difference image in step (2), is specifically comprised the following steps:
2-11 arbitrarily defines a convolution kernel θ；
Convolution kernel θ and frame difference image are carried out convolution by 2-12；When convolution kernel θ traverses frame difference image, extracts convolution kernel and covered
The pixel grey scale minimum value p of the convolution results and pixel C being overlapped with convolution kernel center in region；
The gray scale of pixel C passes through Matrix C H={ ck,qIndicate, k, q are the row serial number and column serial number of pixel C,
Obtain the convolution results minimum value pixel matrix P obtained in convolution kernel θ traversal frame difference image process, minimum value pixel
The gray scale of dot matrix P passes through matrix PH={ pk,qIndicate；
The corresponding imparting pixel C of the gray scale of pixel matrix P is obtained corrosion image by 2-13；
Expansive working is carried out to corrosion image in step (2), is specifically comprised the following steps:
2-21 arbitrarily defines a convolution kernel β；
Convolution kernel β and corrosion image are carried out convolution by 2-22；When convolution kernel β traverses corrosion image, extracts convolution kernel and covered
The pixel grey scale maximum value o of the convolution results and pixel R being overlapped with convolution kernel center in region；
The gray scale of pixel R passes through matrix RH={ rl,vIndicate, l, v are the row serial number and column serial number of pixel R,
Obtain the convolution results maximum value pixel matrix O obtained in convolution kernel β traversal corrosion image process, maximum value pixel
The gray scale of dot matrix O passes through matrix OH={ ol,vIndicate；
The corresponding imparting pixel R of the gray scale of maximum value pixel matrix O is obtained expanding image, obtained expanding image by 2-13
As denoise image；
The step (3) carries out as follows:
3-1 defines a filter Y, and filter is t*t matrix, and t is odd number；
3-2 makes filter Y traversal denoising image, calculates filter in the denoising figure where the central pixel point at each position
The gray value of other pixels in the gray value and center pixel vertex neighborhood of picture, and filter is calculated every according to formula (I)
The edge detection value X of central pixel point at one positionz, z is label when filter Y traversal denoises image,
F, g is the matrix serial number of pixel, and 1≤f≤t, 1≤g≤t, e are filter where the pixel at each position
Denoise the gray value of image；α is weight coefficient, corresponding with filter location；
3-3, by central pixel point edge detection value X of the filter at each positionzWith other pixels of center pixel vertex neighborhood
The gray value of point subtracts each other, and judges whether the absolute value of difference is greater than threshold value Δ；
Statistics is greater than the quantity of threshold value, if quantity is more thanDetermine that the central pixel point of filter present position is corresponding
The pixel position for denoising image is marginal point, and is marked；
3-4, complete denoising image of filter traversal, obtains the markd marginal point of institute, obtains preliminary area-of-interest；
The t is 3.
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