CN109373375B - Intelligent smoke machine precision lens fuzzy self-checking method - Google Patents
Intelligent smoke machine precision lens fuzzy self-checking method Download PDFInfo
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- CN109373375B CN109373375B CN201811151656.8A CN201811151656A CN109373375B CN 109373375 B CN109373375 B CN 109373375B CN 201811151656 A CN201811151656 A CN 201811151656A CN 109373375 B CN109373375 B CN 109373375B
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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
- F24C15/00—Details
- F24C15/20—Removing cooking fumes
- F24C15/2021—Arrangement or mounting of control or safety systems
Abstract
An intelligent fuzzy self-checking method for a precision lens of a cigarette machine comprises the following steps: the visual imaging module is used for continuously imaging the target area S of the cooking bench and sending video stream information of an imaging picture to the processing module; and the image processing module is used for receiving the video stream information of the imaging picture sent by the visual imaging module, judging whether the lens is fuzzy or not and outputting cleaning information according to the fuzzy condition. The camera lens fuzzy self-checking system can carry out camera lens fuzzy self-checking according to an imaging picture and timely inform of cleaning of the lens or antifogging glass in front of the lens.
Description
Technical Field
The invention relates to the technical field of kitchen oil fume treatment, in particular to an intelligent fuzzy self-inspection method for a precision lens of a range hood.
Background
The kitchen is one of the necessary configurations at home, and the effect of kitchen oil smoke treatment directly influences the quality of life of people. The traditional range hood is mainly characterized in that the range hood is opened or closed for exhausting air through a physical key, and the mode depends on manual judgment and operation and is inconvenient. The existing automatic speed regulation range hood realizes a great progress in the performance of the range hood and mainly detects based on a smoke sensor.
Establish the smog condition of shooting the lampblack absorber below in real time through the formation of image, can real-time analysis smog concentration according to the image picture, carry out fan convulsions according to smog size and adjust, this kind of mode can improve oil smoke treatment effeciency and treatment accuracy. However, the blocking of the lens by the oil smoke, the water mist and the like in the use process of the range hood can cause inaccurate detection results.
Therefore, aiming at the defects of the prior art, the fuzzy self-checking method of the precision lens of the intelligent range hood is necessary to overcome the defects of the prior art.
Disclosure of Invention
The invention aims to avoid the defects of the prior art and provides an intelligent fogger precision lens fuzzy self-checking method which can monitor the lens fuzzy condition and remind of cleaning in time.
The object of the invention is achieved by the following technical measures.
The method for fuzzy self-checking of the precision lens of the intelligent range hood is provided, and the range hood main body is provided with:
the visual imaging module is used for continuously imaging the target area S of the cooking bench and sending video stream information of an imaging picture to the processing module;
the image processing module is used for receiving video stream information of an imaging picture sent by the visual imaging module, judging whether a lens is fuzzy or not and outputting cleaning information according to the fuzzy condition;
the processing module marks the received imaging pictures according to the imaging time and the frame sequence, and the imaging time corresponding to the y-th imaging picture P is TyThe corresponding frame sequence is y, and y is a natural number;
current imaging picture P to be subjected to lens fuzzy self-inspectionηThe imaging picture with the corresponding frame sequence of eta and the frame sequence of eta-1 is the imaging picture P of the previous frame(η-1)Eta is greater than or equal to 2;
the specific process of judging whether the lens is blurred by the image processing module is as follows:
(1) let T equal to 1;
(2) selecting Q frame imaging picture as target object PkK ═ η -Q +1 to η;
(3) extracting each frame target object PkMiddle large gradient number Fk；
(4) Calculating the large gradient mean value B of the imaging picture of the Q frame,
(5) according to the formula
Calculating a parameter C, comparing the parameter C with a threshold value D, and entering the step (6) when the parameter C is greater than the threshold value D; otherwise, entering the step (9);
(6) judging whether T is smaller than psi, and psi is a natural number; if yes, entering the step (7); otherwise, entering the step (8);
(7) making T equal to T +1 and making eta equal to eta +1, and returning to the step (2);
(8) judging that the lens is fuzzy, and sending out warning for cleaning the lens or antifogging glass in front of the lens;
(9) and judging that the lens is not blurred.
Preferably, Q is greater than 5 and less than 20.
Preferably, Q is 10.
Preferably, the threshold D is 1.6 to 3.0.
Preferably, the threshold D takes a value of 1.8.
Preferably, ψ is 2 or more and 5 or less.
Preferably, ψ is equal to 3.
Preferably, each frame of the target object is composed of m × n pixels,
the gray scale values of the pixels of the target object P are represented by a matrix PH, { PH ═ PHi,j}，phi,jRepresenting gray values corresponding to pixels of an ith row and a jth column in the target object P, wherein i is a row where the pixel is located, j is a column where the pixel is located, i is more than or equal to 1 and less than or equal to m, and j is more than or equal to 1 and less than or equal to n;
the ratio of the gray value of one pixel to the gray value of another adjacent pixel is greater than the gradient threshold delta, the pixel is a large gradient pixel, and the target object P is displayed in each framekMiddle large gradient number FkEqual to target object P per framekThe number of large gradient pixels in (1).
Preferably, the gradient threshold δ is greater than 2.5 and less than 10.
Preferably, the gradient threshold δ is equal to 3.
The intelligent smoke machine precision lens fuzzy self-checking method can perform camera lens fuzzy self-checking according to the imaging picture and timely inform the cleaning of the lens or antifogging glass in front of the lens.
Drawings
The invention is further illustrated by means of the attached drawings, the content of which is not in any way limiting.
Figure 1 is a schematic diagram of the structure of an intelligent range hood for use with the present invention.
Fig. 2 is a schematic view of the structure of fig. 1 from another angle.
In fig. 1 and 2, the method includes:
the range hood comprises a range hood body 100, a camera 200, a light supplement lamp 300, a cooking bench 400 and a human body working area 500.
Detailed Description
The invention is further illustrated by the following examples.
Example 1.
An intelligent fuzzy self-checking method for a precision lens of a cigarette machine comprises the following steps:
the visual imaging module is used for continuously imaging the target area S of the cooking bench and sending video stream information of an imaging picture to the processing module;
and the image processing module is used for receiving the video stream information of the imaging picture sent by the visual imaging module, judging whether the lens is fuzzy or not and outputting cleaning information according to the fuzzy condition.
The processing module marks the received imaging pictures according to the imaging time and the frame sequence, and the imaging time corresponding to the y-th imaging picture P is TyThe corresponding frame sequence is y, and y is a natural number.
Current imaging picture P to be subjected to lens fuzzy self-inspectionηThe imaging picture with the corresponding frame sequence of eta and the frame sequence of eta-1 is the imaging picture P of the previous frame(η-1)And eta is greater than or equal to 2.
The specific process of judging whether the lens is blurred by the image processing module is as follows:
(1) let T equal to 1;
(2) selecting Q frame imaging picture as target object PkK ═ η -Q +1 to η;
(3) extracting each frame target object PkMiddle large gradient number Fk；
(4) Calculating the large gradient mean value B of the imaging picture of the Q frame,
(5) according to the formula
Calculating a parameter C, comparing the parameter C with a threshold value D, and entering the step (6) when the parameter C is greater than the threshold value D;otherwise, entering the step (9);
(6) judging whether T is smaller than psi, and psi is a natural number; if yes, entering the step (7); otherwise, entering the step (8);
(7) making T equal to T +1 and making eta equal to eta +1, and returning to the step (2);
(8) judging that the lens is fuzzy, and sending out warning for cleaning the lens or antifogging glass in front of the lens;
(9) and judging that the lens is not blurred.
Q is greater than 5 and less than 20, preferably Q is 10. The threshold D is 1.6 to 3.0, preferably 1.8. ψ is 2 or more and 5 or less, preferably ψ is 3 or more.
Specifically, each frame of the target object is formed by m × n pixels, and the grayscale value of the pixel of the target object P is represented by a matrix PH, { PH ═i,j}，phi,jRepresenting the gray values corresponding to the ith row and the jth column of pixels in the target object P, wherein i is the row where the pixel is located, j is the column where the pixel is located, i is more than or equal to 1 and less than or equal to m, and j is more than or equal to 1 and less than or equal to n.
The ratio of the gray value of one pixel to the gray value of another adjacent pixel is greater than the gradient threshold delta, the pixel is a large gradient pixel, and the target object P is displayed in each framekMiddle large gradient number FkEqual to target object P per framekThe number of large gradient pixels in (1).
The gradient threshold δ is greater than 2.5 and less than 10, preferably 3.
The camera lens fuzzy self-checking system can carry out camera lens fuzzy self-checking according to an imaging picture and timely inform of cleaning of the lens or antifogging glass in front of the lens.
Example 2.
The other characteristics of the fuzzy self-checking method for the precision lens of the intelligent range hood are the same as those of embodiment 1, except that in the embodiment, Q is 10, and the value of the threshold D is 1.8. The parameter setting can meet the detection precision and has the characteristic of small operand.
Example 3.
An intelligent fuzzy self-checking method for a precision lens of a cigarette machine is applied to the cigarette machine.
As shown in fig. 1 and 2, the cigarette maker main body 100 is provided with: and the visual imaging module is assembled on the cigarette machine main body, continuously images the target area, and sends the video stream information of the imaging picture to the processing module. The vision imaging module is provided with a camera 200, the camera 200 is arranged in the shell of the cigarette machine main body 100, the camera is provided with a 180-degree wide-angle lens, a part of vision area of the 180-degree wide-angle lens covers the area of the cooking bench 400, and a part of vision area of the 180-degree wide-angle lens covers the human body working area 500 on the outer side above the cooking bench. Through 180 wide-angle lens, can realize forming images the top of a kitchen range region and human work area, provide the wide regional imaging information of broad for lampblack absorber processing module.
The cigarette machine main body 100 is further provided with: and the image processing module is used for receiving the video stream information of the imaging picture sent by the visual imaging module, judging whether the lens is fuzzy or not and outputting cleaning information according to the fuzzy condition.
And the visual imaging module performs target area imaging and determines imaging picture effect. The vision imaging module is also provided with a light supplement lamp 300, and the irradiation area of the light supplement lamp covers the imaging view range of the camera. The light source wavelength of the light supplement lamp is preferably 850-980 nm.
The setting of light filling lamp can shine imaging area when camera 200 formation of image, and light filling lamp 300 can let the smog characteristic more obvious, detects easily in the vision. The smoke characteristics are not obvious under the irradiation condition without the fill-in light 300. The fill-in light is preferably an infrared fill-in light, but may be other fill-in lights. In this embodiment, the position of light filling lamp distributes in camera both sides, and the light filling lamp also can distribute around the camera, also can be in the same place with camera integration, also can set up to not be in the cigarette machine main part, be located other positions around the camera.
The visual imaging module is assembled on the cigarette machine main body in the embodiment, and it should be noted that the installation position of the visual imaging module is not limited to the cigarette machine main body in the embodiment, and the visual imaging module can also be assembled on a wall where a cigarette machine is installed, or assembled around a cooking bench or arranged at the surrounding positions of other cigarette machine main bodies, as long as the visual imaging module can image a target area at the corresponding position of the cooking bench.
In addition, the camera is also provided with waterproof, antifog and oil smoke-proof lenses so as to adapt to the oil smoke environment of a kitchen.
The processing module may select a chip model STM 32.
The camera lens fuzzy self-checking system can carry out camera lens fuzzy self-checking according to an imaging picture and timely inform of cleaning of the lens or antifogging glass in front of the lens.
It should be noted that, this embodiment only provides a range hood, and other forms of range hoods may be selected in practice, and are not limited to the case of this embodiment.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and not for limiting the protection scope of the present invention, and although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (9)
1. The intelligent fuzzy self-checking method for the precision lens of the cigarette machine is characterized in that the cigarette machine main body is provided with:
the visual imaging module is used for continuously imaging the target area S of the cooking bench and sending video stream information of an imaging picture to the processing module;
the image processing module is used for receiving video stream information of an imaging picture sent by the visual imaging module, judging whether a lens is fuzzy or not and outputting cleaning information according to the fuzzy condition;
the processing module marks the received imaging pictures according to the imaging time and the frame sequence, and the imaging time corresponding to the y-th imaging picture P is TyThe corresponding frame sequence is y, and y is a natural number;
current imaging picture P to be subjected to lens fuzzy self-inspectionηThe imaging picture with the corresponding frame sequence of eta and the frame sequence of eta-1 is the imaging picture P of the previous frame(η-1)Eta is greater than or equal to 2;
the specific process of judging whether the lens is blurred by the image processing module is as follows:
(1) let T equal to 1;
(2) selecting Q frame imaging pictures to doIs a target object PkK ═ η -Q +1 to η;
(3) extracting each frame target object PkMiddle large gradient number Fk；
(4) Calculating the large gradient mean value B of the imaging picture of the Q frame,
(5) according to the formula
Calculating a parameter C, comparing the parameter C with a threshold value D, and entering the step (6) when the parameter C is greater than the threshold value D; otherwise, entering the step (9);
(6) judging whether T is smaller than psi, and psi is a natural number; if yes, entering the step (7); otherwise, entering the step (8);
(7) making T equal to T +1 and making eta equal to eta +1, and returning to the step (2);
(8) judging that the lens is fuzzy, and sending out warning for cleaning the lens or antifogging glass in front of the lens;
(9) judging that the lens is not blurred;
each frame of the target object is composed of m x n pixels,
the gray scale values of the pixels of the target object P are represented by a matrix PH, { PH ═ PHi,j}，phi,jRepresenting gray values corresponding to pixels of an ith row and a jth column in the target object P, wherein i is a row where the pixel is located, j is a column where the pixel is located, i is more than or equal to 1 and less than or equal to m, and j is more than or equal to 1 and less than or equal to n;
the ratio of the gray value of one pixel to the gray value of another adjacent pixel is greater than the gradient threshold delta, the pixel is a large gradient pixel, and the target object P is displayed in each framekMiddle large gradient number FkEqual to target object P per framekThe number of large gradient pixels in (1).
2. The fuzzy self-checking method of the precision lens of the intelligent cigarette making machine according to claim 1, wherein the Q value is more than 5 and less than 20.
3. The fuzzy self-inspection method of the precision lens of the intelligent cigarette making machine according to claim 2, characterized in that the cigarette making machine main body is provided with: q is 10.
4. The fuzzy self-inspection method of the precision lens of the intelligent cigarette making machine according to claim 1, wherein the threshold value D is 1.6 to 3.0.
5. The fuzzy self-checking method of the precision lens of the intelligent cigarette making machine according to claim 4, characterized in that the threshold D takes a value of 1.8.
6. The fuzzy self-checking method of the precision lens of the intelligent cigarette making machine according to claim 1, wherein ψ is greater than or equal to 2 and less than or equal to 5.
7. The fuzzy self-checking method of the precision lens of the intelligent cigarette making machine according to claim 6, wherein ψ is equal to 3.
8. The fuzzy self-inspection method of the precision lens of the intelligent cigarette making machine according to any one of claims 1 to 7, wherein a gradient threshold value delta is greater than 2.5 and less than 10.
9. The fuzzy self-checking method of the precision lens of the intelligent cigarette making machine according to the claim 8, characterized in that the gradient threshold value δ is equal to 3.
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| CN105761261A (en) * | 2016-02-17 | 2016-07-13 | 南京工程学院 | Method for detecting artificial malicious damage to camera |
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| CN107749918A (en) * | 2017-09-14 | 2018-03-02 | 深圳天珑无线科技有限公司 | User is prompted to wipe method, mobile terminal and the storage medium of camera lens |
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| CN104093016A (en) * | 2014-06-12 | 2014-10-08 | 华南理工大学 | Camera module smudginess detection method and system |
| CN104200215A (en) * | 2014-08-27 | 2014-12-10 | 中国工程物理研究院激光聚变研究中心 | Method for identifying dust and pocking marks on surface of big-caliber optical element |
| CN105761261A (en) * | 2016-02-17 | 2016-07-13 | 南京工程学院 | Method for detecting artificial malicious damage to camera |
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