CN108760590A - A kind of kitchen fume Concentration Testing based on image procossing and interference elimination method - Google Patents
A kind of kitchen fume Concentration Testing based on image procossing and interference elimination method Download PDFInfo
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- CN108760590A CN108760590A CN201810191908.3A CN201810191908A CN108760590A CN 108760590 A CN108760590 A CN 108760590A CN 201810191908 A CN201810191908 A CN 201810191908A CN 108760590 A CN108760590 A CN 108760590A
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- 238000000034 method Methods 0.000 title claims abstract description 23
- 239000003517 fume Substances 0.000 title claims abstract description 16
- 230000008030 elimination Effects 0.000 title claims abstract description 15
- 238000003379 elimination reaction Methods 0.000 title claims abstract description 15
- 238000012360 testing method Methods 0.000 title claims abstract description 15
- 239000000779 smoke Substances 0.000 claims abstract description 60
- 238000001514 detection method Methods 0.000 claims abstract description 11
- 230000009466 transformation Effects 0.000 claims abstract description 4
- 238000003708 edge detection Methods 0.000 claims description 6
- 238000005530 etching Methods 0.000 claims description 4
- 230000011218 segmentation Effects 0.000 claims description 4
- 238000003752 polymerase chain reaction Methods 0.000 claims description 3
- 238000012163 sequencing technique Methods 0.000 claims description 2
- 238000011897 real-time detection Methods 0.000 abstract 1
- 238000005516 engineering process Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 235000019504 cigarettes Nutrition 0.000 description 1
- 238000010411 cooking Methods 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000007717 exclusion Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 239000003595 mist Substances 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- 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—
Abstract
A kind of kitchen fume Concentration Testing based on image procossing and interference elimination method, include the following steps：Oil smoke image above acquisition hearth in real time；Image processing unit carries out frame difference operation to collected front and back frame image, obtains the dynamic area image after frame difference；Image processing unit carries out opening operation to the image after frame difference, removes image noise；Using wavelet transformation, the edge of detection frame difference figure highlight regions is simultaneously marked；Using Image Smoothness and the method for gray value threshold value comprehensive descision come exclusive PCR, oil smoke moving region is identified；Statistics of histogram is carried out to the oil smoke region identified, judges oil smoke concentration grade.It is an object of the invention to propose a kind of kitchen fume Concentration Testing based on image procossing and interference elimination method, after the algorithm provided through the invention excludes human interference, the influence of hardly examined distance, the non-contact real-time detection that oil smoke concentration can be achieved, has many advantages, such as high accuracy and real-time.
Description
Technical field
The present invention relates to oil smoke detection technique field more particularly to a kind of kitchen fume Concentration Testings based on image procossing
With interference elimination method.
Background technology
It is directed to the detection of kitchen fume concentration at this stage, mainly there is infrared projection method and physical measure.Infrared Detection Method
One end emits infrared light, and the other end receives, and judges oil smoke concentration size by the infrared luminous intensity received, but oil smoke drifts
With uncertainty, the interference that also human hand blocks, so needing just to can guarantee in the multiple infrared transmitters of different location installation
Oil smoke detects relatively accurate, and cost is higher, requires installation site also higher.Physical measure is similar to smoke alarm
Principle judges oil smoke concentration by floating particle number in detection air, but there are two disadvantages for this method, first, must be connect when oil smoke
Contacting can just be detected when alarm, can not achieve remote detection；Second is that when what is floated in air is not oil smoke but water
It can not just be detected when mist.
Invention content
It is an object of the invention to solve the above problems propose a kind of kitchen fume Concentration Testing based on image procossing with
Interference elimination method.
In order to reach this purpose, the present invention uses following technical scheme：
A kind of kitchen fume Concentration Testing based on image procossing and interference elimination method, include the following steps：
Step A1 acquires the oil smoke image above hearth in real time；
Step A2, image processing unit carry out frame difference operation to collected front and back frame image, obtain the dynamic after frame difference
Area image；
Step A3, image processing unit carry out opening operation to the image after frame difference, remove image noise；
Step A4, using wavelet transformation, the edge of detection frame difference figure highlight regions is simultaneously marked, the region that will be marked
It is set as area-of-interest；
Step A5 identifies oil smoke using Image Smoothness and the method for gray value threshold value comprehensive descision come exclusive PCR
Moving region；
Step A6 carries out statistics of histogram to the oil smoke region identified, judges oil smoke concentration grade.
More preferably, it is camera oil smoke image to be acquired in the step A1, and the camera is mounted on kitchen ventilator ontology.
More preferably, image processing unit can be utilized according to the sequencing of the gray level image received in the step A2
A later frame image makes the difference with previous frame image.
More preferably, further comprising the steps of in the step A3：
Step B1 carries out etching operation to image, eliminates the noise in image and tiny spine, disconnect narrow company
It connects；
Step B2 carries out expansive working to the image corroded, restores the obvious characteristic on former frame difference image.
More preferably, the step A4 is further comprising the steps of：
Step C1 traverses frame difference image according to the filter of one 3*3 size of feature-set at edge with filter；
Step C2, calculate each position central pixel point in field in the gray value and filter of eight pixels it is corresponding
Value be multiplied and seek the edge detection value of pixel centered on summation；
Step C3, if the edge detection value differs larger with the pixel gray value more than half in field, by this
One pixel is determined as marginal point, and is marked；
Step C4, after device to be filtered has traversed image, the edge of highlight regions can be detected and be marked, as next
Walk the object of interest of processing.
More preferably, the step A5 exclusive PCRs region includes the following steps：
Step D1 finds out the segmentation threshold of oil smoke region and interference region, is set when the gray average of area-of-interest is more than
When fixed gray threshold, judgement area-of-interest is that may interfere with region；When the gray average of area-of-interest is less than setting
When gray threshold, judgement area-of-interest is possible oil smoke region；
Step D2 calculates the smoothness of each area-of-interest on the basis of area grayscale mean value, if some region of interest
When the variance in domain is greater than the set value, judgement area-of-interest is that may interfere with region；If the variance of some area-of-interest is less than
When setting value, judgement area-of-interest is possible oil smoke region；
Step D3, when step D1 and step D2 be all possible oil smoke region when, then judge area-of-interest for oil smoke region,
Other regions are all determined as interference region.
It is an object of the invention to propose a kind of kitchen fume Concentration Testing based on image procossing and interference elimination method,
After the algorithm that provides through the invention excludes human interference, the influence of hardly examined distance, it can be achieved that oil smoke concentration it is non-
Contact detection in real time, has many advantages, such as high accuracy and real-time.
Description of the drawings
Fig. 1 is the flow chart of one embodiment of the present of invention；
Fig. 2 is the schematic diagram of the oil smoke region recognition of one embodiment of the present of invention.
Specific implementation mode
The technical solution further illustrated the present invention below in conjunction with the accompanying drawings and by specific embodiment mode.
As shown in Figure 1, a kind of kitchen fume Concentration Testing based on image procossing and interference elimination method, including following step
Suddenly：
Step A1 acquires the oil smoke image above hearth in real time；
Step A2, image processing unit carry out frame difference operation to collected front and back frame image, obtain the dynamic after frame difference
Area image；
Step A3, image processing unit carry out opening operation to the image after frame difference, remove image noise；
Step A4, using wavelet transformation, the edge of detection frame difference figure highlight regions is simultaneously marked, the region that will be marked
It is set as area-of-interest；
Step A5 identifies oil smoke using Image Smoothness and the method for gray value threshold value comprehensive descision come exclusive PCR
Moving region；
Step A6 carries out statistics of histogram to the oil smoke region identified, judges oil smoke concentration grade.
Further description, acquisition oil smoke image is camera in the step A1, and the camera is mounted on kitchen ventilator
On ontology.Camera fields of view can cover entire hearth, and through the real-time gray level image of lens protection glass acquisition hearth oil smoke
And it is transmitted to image processing unit.
Further description, image processing unit can be suitable according to the priority of the gray level image received in the step A2
Sequence is made the difference using a later frame image with previous frame image.Since static region is constant, dynamic area in front and back two field pictures
(such as oil smoke drifts, and human hand is brandished) is variation, so black is presented in static region after frame difference, table after the frame difference of dynamic area
It is now the highlight regions of edge blurry, so the highlighted frame difference image in dynamic area can be obtained by frame difference.
Further description, it is further comprising the steps of in the step A3：
Step B1 carries out etching operation to image, eliminates the noise in image and tiny spine, disconnect narrow company
It connects；
Step B2 carries out expansive working to the image corroded, restores the obvious characteristic on former frame difference image.
The noise of frame difference image is removed using the method for opening operation, concrete operations are first to corrode reflation.First to image into
Row etching operation can eliminate the noise in image and tiny spine, disconnect narrow connection.Expansion is the antithesis behaviour of corrosion
Make, expansive working is carried out to the image corroded, restores the obvious characteristic on former frame difference image.Figure can be eliminated using opening operation
As noise, the separating objects at very thin point, smooth larger object boundary, while can ensure highlight regions in original image
Area is basically unchanged, and ensures that the accuracy of subsequent detection is unaffected.
Further description, the step A4 are further comprising the steps of：
Step C1 traverses frame difference image according to the filter of one 3*3 size of feature-set at edge with filter；
Step C2, calculate each position central pixel point in field in the gray value and filter of eight pixels it is corresponding
Value be multiplied and seek the edge detection value of pixel centered on summation；
Step C3, if the edge detection value differs larger with the pixel gray value more than half in field, by this
One pixel is determined as marginal point, and is marked；
Step C4, after device to be filtered has traversed image, the edge of highlight regions can be detected and be marked, as next
Walk the object of interest of processing.
Further description, the step A5 exclusive PCRs region include the following steps：
Step D1 finds out the segmentation threshold of oil smoke region and interference region, is set when the gray average of area-of-interest is more than
When fixed gray threshold, judgement area-of-interest is that may interfere with region；When the gray average of area-of-interest is less than setting
When gray threshold, judgement area-of-interest is possible oil smoke region；
Step D2 calculates the smoothness of each area-of-interest on the basis of area grayscale mean value, if some region of interest
When the variance in domain is greater than the set value, judgement area-of-interest is that may interfere with region；If the variance of some area-of-interest is less than
When setting value, judgement area-of-interest is possible oil smoke region；
Step D3, when step D1 and step D2 be all possible oil smoke region when, then judge area-of-interest for oil smoke region,
Other regions are all determined as interference region.
Because people is when cooking operation, hand can be brandished always, can include that oil smoke and human hand are grasped in the image after frame difference is complete
The interference region for the moving objects such as making, needs the influence in exclusive PCR region before carrying out oil smoke concentration identification, but oil smoke
The direction of motion have randomness, human hand, the direction of motion of slice are relatively unambiguous, to as shown in Figure 2：A, the image after frame difference
Upper oil smoke moving region is lower than the brightness of human hand, slice moving region, so the gray value mean value in corresponding oil smoke region is also low
Gray average in the moving region of human hand, slice；B, the grey value profile of oil smoke moving region relatively collects on the image after frame difference
In, and the gray value of the motion region boundary of human hand, slice is larger compared with the jump of the central area in region, so the image in the region
Not smooth enough, the variance of corresponding gray value is larger.Feature according to A, we are largely tested, and find out oil smoke area
The segmentation threshold in domain and interference region judges the region when the gray average of area-of-interest is more than the gray threshold of setting
To may interfere with region；When the gray average of area-of-interest is less than the gray threshold of setting, judge the region for possible oil
Cigarette district domain.Feature according to B calculates the smoothness of each area-of-interest on the basis of area grayscale mean value, the present invention
It is middle to be indicated with gray value variance, if the variance of some area-of-interest is greater than the set value, judge that the region is that may interfere with area
Domain；If the variance of some area-of-interest is less than setting value, judge the region for possible oil smoke region.Only judge when twice
When (gray average and variance) is all possible oil smoke region, then the region is judged for oil smoke region, other area-of-interests are all sentenced
It is set to interference region.Complete the exclusion of the identification and interference region in oil smoke region.
The method that the present invention utilizes statistics of histogram delimit oil smoke concentration grade.Grey level histogram is about gray scale
The function of grade distribution, is the statistics to grey level distribution in image.Grey level histogram is to press all pixels in digital picture
According to the size of gray value, the frequency of its appearance is counted.The concentration scale quantity divided as needed, can use 10 is siding-to-siding block length,
The pixel number in each gray scale interval is counted, reaches the grade classification scheme set and then divides oil smoke as corresponding concentration etc.
Grade.
The technical principle of the present invention is described above in association with specific embodiment.These descriptions are intended merely to explain the present invention's
Principle, and it cannot be construed to limiting the scope of the invention in any way.Based on the explanation herein, the technology of this field
Personnel would not require any inventive effort the other specific implementation modes that can associate the present invention, these modes are fallen within
Within protection scope of the present invention.
Claims (6)
1. a kind of kitchen fume Concentration Testing based on image procossing and interference elimination method, which is characterized in that including following step
Suddenly：
Step A1 acquires the oil smoke image above hearth in real time；
Step A2, image processing unit carry out frame difference operation to collected front and back frame image, obtain the dynamic area after frame difference
Image；
Step A3, image processing unit carry out opening operation to the image after frame difference, remove image noise；
Step A4, using wavelet transformation, the edge of detection frame difference figure highlight regions is simultaneously marked, and the region marked is set as
Area-of-interest；
Step A5 identifies that oil smoke moves using Image Smoothness and the method for gray value threshold value comprehensive descision come exclusive PCR
Region；
Step A6 carries out statistics of histogram to the oil smoke region identified, judges oil smoke concentration grade.
2. a kind of kitchen fume Concentration Testing based on image procossing according to claim 1 and interference elimination method,
It is characterized in that：It is camera that oil smoke image is acquired in the step A1, and the camera is mounted on kitchen ventilator ontology.
3. a kind of kitchen fume Concentration Testing based on image procossing according to claim 1 and interference elimination method,
It is characterized in that：Image processing unit can utilize a later frame according to the sequencing of the gray level image received in the step A2
Image makes the difference with previous frame image.
4. a kind of kitchen fume Concentration Testing based on image procossing according to claim 1 and interference elimination method,
It is characterized in that：It is further comprising the steps of in the step A3：
Step B1 carries out etching operation to image, eliminates the noise in image and tiny spine, disconnect narrow connection；
Step B2 carries out expansive working to the image corroded, restores the obvious characteristic on former frame difference image.
5. a kind of kitchen fume Concentration Testing based on image procossing according to claim 1 and interference elimination method,
It is characterized in that：The step A4 is further comprising the steps of：
Step C1 traverses frame difference image according to the filter of one 3*3 size of feature-set at edge with filter；
Step C2 calculates the gray value value corresponding in filter of eight pixels in each position central pixel point and field
It is multiplied and asks the edge detection value of pixel centered on summation；
Step C3, if the edge detection value differs larger with the pixel gray value more than half in field, by this picture
Vegetarian refreshments is determined as marginal point, and is marked；
Step C4, after device to be filtered has traversed image, the edge of highlight regions can be detected and be marked, in next step
The object of interest of reason.
6. a kind of kitchen fume Concentration Testing based on image procossing according to claim 1 and interference elimination method,
It is characterized in that：The step A5 exclusive PCRs region includes the following steps：
Step D1 finds out the segmentation threshold of oil smoke region and interference region, when the gray average of area-of-interest is more than setting
When gray threshold, judgement area-of-interest is that may interfere with region；When the gray average of area-of-interest is less than the gray scale of setting
When threshold value, judgement area-of-interest is possible oil smoke region；
Step D2 calculates the smoothness of each area-of-interest on the basis of area grayscale mean value, if some area-of-interest
When variance is greater than the set value, judgement area-of-interest is that may interfere with region；If the variance of some area-of-interest is less than setting
When value, judgement area-of-interest is possible oil smoke region；
Step D3, when step D1 and step D2 be all possible oil smoke region when, then judge area-of-interest for oil smoke region, other
Region is all determined as interference region.
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| CN201810191908.3A CN108760590B (en) | 2018-03-08 | 2018-03-08 | Kitchen oil smoke concentration detection and interference elimination method based on image processing |
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| CN201810191908.3A CN108760590B (en) | 2018-03-08 | 2018-03-08 | Kitchen oil smoke concentration detection and interference elimination method based on image processing |
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| CN108760590A true CN108760590A (en) | 2018-11-06 |
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Cited By (7)
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| CN109210600A (en) * | 2018-11-30 | 2019-01-15 | 林丽 | Oil smoke electro-mechanical force on-off system |
| CN109657640A (en) * | 2018-12-29 | 2019-04-19 | 佛山市云米电器科技有限公司 | It is a kind of can according to use food materials carry out Health Category division kitchen ventilator |
| CN109655585A (en) * | 2018-12-29 | 2019-04-19 | 佛山市云米电器科技有限公司 | A kind of kitchen ventilator that can identify kitchen air quality |
| CN109669007A (en) * | 2018-12-29 | 2019-04-23 | 佛山市云米电器科技有限公司 | A kind of equipment of the online food detection of household non-invasive |
| CN109798565A (en) * | 2018-12-29 | 2019-05-24 | 佛山市云米电器科技有限公司 | A kind of oil absorption system with harmful substance function in identification oil smoke |
| CN109827612A (en) * | 2018-12-29 | 2019-05-31 | 佛山市云米电器科技有限公司 | A kind of smoke machine changeable type polycyclic aromatic hydrocarbon detection device |
| CN116758489A (en) * | 2023-08-17 | 2023-09-15 | 山东传奇新力科技有限公司 | Intelligent kitchen lampblack detection and identification method based on image processing |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109210600A (en) * | 2018-11-30 | 2019-01-15 | 林丽 | Oil smoke electro-mechanical force on-off system |
| CN109210600B (en) * | 2018-11-30 | 2020-01-21 | 中山市浩帆电子电器有限公司 | Electric power on-off system of range hood |
| CN109657640A (en) * | 2018-12-29 | 2019-04-19 | 佛山市云米电器科技有限公司 | It is a kind of can according to use food materials carry out Health Category division kitchen ventilator |
| CN109655585A (en) * | 2018-12-29 | 2019-04-19 | 佛山市云米电器科技有限公司 | A kind of kitchen ventilator that can identify kitchen air quality |
| CN109669007A (en) * | 2018-12-29 | 2019-04-23 | 佛山市云米电器科技有限公司 | A kind of equipment of the online food detection of household non-invasive |
| CN109798565A (en) * | 2018-12-29 | 2019-05-24 | 佛山市云米电器科技有限公司 | A kind of oil absorption system with harmful substance function in identification oil smoke |
| CN109827612A (en) * | 2018-12-29 | 2019-05-31 | 佛山市云米电器科技有限公司 | A kind of smoke machine changeable type polycyclic aromatic hydrocarbon detection device |
| CN109655585B (en) * | 2018-12-29 | 2021-08-31 | 佛山市云米电器科技有限公司 | Range hood capable of identifying kitchen air quality |
| CN109669007B (en) * | 2018-12-29 | 2023-09-22 | 佛山市云米电器科技有限公司 | Household non-invasive on-line food detection equipment |
| CN109827612B (en) * | 2018-12-29 | 2024-02-23 | 佛山市云米电器科技有限公司 | Replaceable polycyclic aromatic hydrocarbon detection device for smoke machine |
| CN116758489A (en) * | 2023-08-17 | 2023-09-15 | 山东传奇新力科技有限公司 | Intelligent kitchen lampblack detection and identification method based on image processing |
| CN116758489B (en) * | 2023-08-17 | 2023-10-27 | 山东传奇新力科技有限公司 | Intelligent kitchen lampblack detection and identification method based on image processing |
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