CN108337443A - A method of based on exposure value and scene learning algorithm control IRCUT and infrared lamp - Google Patents
A method of based on exposure value and scene learning algorithm control IRCUT and infrared lamp Download PDFInfo
- Publication number
- CN108337443A CN108337443A CN201810037912.4A CN201810037912A CN108337443A CN 108337443 A CN108337443 A CN 108337443A CN 201810037912 A CN201810037912 A CN 201810037912A CN 108337443 A CN108337443 A CN 108337443A
- Authority
- CN
- China
- Prior art keywords
- exposure value
- ircut
- value
- infrared lamp
- learning algorithm
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/73—Circuitry for compensating brightness variation in the scene by influencing the exposure time
Abstract
The invention discloses a kind of methods controlling IRCUT and infrared lamp based on exposure value and scene learning algorithm, include the following steps：It is initialized as day mode, the exposure value of picture after the imaging of sampling the last time SENSOR, and M EV sample values are recorded in memory card；EV values reach night threshold value, are switched to night pattern, the exposure value of picture after the imaging of sampling the last time SENSOR, and n times EV sample values are recorded in memory card；Compare nearest multiple exposure value sampled point, and removes maximum value and minimum value；According to day mode and night pattern sampled data, exposure value is divided into linear change section and nonlinear change section, in nonlinear change section, quantify the variation of illumination using the difference between dynamic calculating exposure value, one is fitted perfectly using illumination, reflecting rate, distance as the function of independent variable, and accurate control is reached to IRCUT and infrared lamp；The adaptation scene of video camera is more flexible reliable, has saved cost, equipment is more beautiful and generous.
Description
Technical field
It is specifically a kind of to be controlled based on exposure value and scene learning algorithm the present invention relates to a kind of method for processing video frequency
The method of IRCUT and infrared lamp.
Background technology
According to the system division methods of computer system input, processing, output, the night vision switching control of security monitoring camera
System processed divides as follows：
1 input：Photo resistance
2 processing：Software control algorithm
3 outputs：Infrared lamp, IRCUT
1st generation IRCUT controls, it is photosensitive by reading, incude the illumination (unit Lux) of external environment, low-light (level) (is less than
Open infrared lamp when 3Lux), IRCUT opens full impregnated light optical filter, when high illumination (being more than 5Lux), closes infrared lamp, IRCUT opens filter
Feux rouges optical filter.
2nd generation IRCUT control, eliminates photosensitive, passes through the EV values (Exposure of picture after reading SENSOR imagings
Values exposure values), it then converts EV values to corresponding illumination, IRCUT and infrared lamp are controlled.
1st generation IRCUT algorithms have following deficiency because having used photosensitive component：
1 increases hardware cost and increases installation step.
2 have greater difference in photosensitive photosurface and imaging picture, photosensitive accurately to characterize image under backlighting environment
Illumination.
3 in starlight grade video camera, under low-light (level), the photosensitive phenomenon that will appear precision deficiency.
4 in the northern morning and evening temperature difference compared in overall situation, it is photosensitive to have temperature drift phenomenon, it may appear that the characterization value of same illumination sooner or later
The larger phenomenon of gap.
2nd generation IRCUT algorithms, under low-illumination scene, after infrared unlatching, EV values and illumination not direct proportionality,
It is embodied in：
1 distance is closer, and reflective more to concentrate, EV values are bigger.Such as camera lens, close to desktop, EV values can be very big, can be mistaken for
Daytime.
Object reflecting rate is higher (white highest, black are minimum) in 2 pictures, and EV values are bigger.
There is moving object in 3 pictures, causes EV values to shake, IRCUT is caused accidentally to cut.
The scene adaptability of 4 algorithms, current consumer video camera have the demand of mobile context.
Invention content
The purpose of the present invention is to provide a kind of sides controlling IRCUT and infrared lamp based on exposure value and scene learning algorithm
Method, to solve the problems mentioned in the above background technology.
To achieve the above object, the present invention provides the following technical solutions：
A method of based on exposure value and scene learning algorithm control IRCUT and infrared lamp, include the following steps：
Step 1：It is initialized as day mode, the exposure value of picture after the imaging of sampling the last time SENSOR, and storing
M EV sample values are recorded in card；
Step 2：EV values reach night threshold value, are switched to night pattern, picture after the imaging of sampling the last time SENSOR
Exposure value, and n times EV sample values are recorded in memory card；
Step 3：Compare nearest multiple exposure value sampled point, and removes maximum value and minimum value；According to day mode and
Exposure value is divided into linear change section and nonlinear change section by night pattern sampled data, in nonlinear change section, using dynamic
State calculates the difference between exposure value to quantify the variation of illumination, fits one perfectly with illumination, reflecting rate, distance for change certainly
The function of amount, to reach accurate control to IRCUT and infrared lamp.
As a further solution of the present invention：The number M of exposure value sampled point in the step 1 is at most 20 times.
As further scheme of the invention：The times N of exposure value sampled point in the step 2 is at most 15 times.
As further scheme of the invention：The time interval of exposure value sampled point in the step 2 is 2.5 seconds.
Compared with prior art, the beneficial effects of the invention are as follows：The present invention is based on when day mode, EV values must react ring
This advantage of border illumination, learns different static environments, and carries out trial and error, and dynamic adjusts inner parameter, right
Quickly change and mobile context in light, quickly judged by the difference of EV values, with this 2 points fit one it is perfect
Using illumination, reflecting rate, distance as the function of independent variable, to reach accurate control to IRCUT and infrared lamp；Video camera is fitted
It answers scene more flexible reliable, has not only saved cost, but also after improved structure, equipment is more beautiful and generous.
Description of the drawings
Fig. 1 is a kind of algorithm flow based in exposure value and the method for scene learning algorithm control IRCUT and infrared lamp
Schematic diagram.
Specific implementation mode
Technical scheme of the present invention is described in more detail With reference to embodiment.
Embodiment
A method of based on exposure value and scene learning algorithm control IRCUT and infrared lamp, include the following steps：
Step 1：By the exposure value of picture after SENSOR imaging of reading, and record data in memory card；
Step 2：Compare nearest multiple exposure value sampled point, and removes maximum value and minimum value；
Step 3：Exposure value is divided into linear change section and nonlinear change section, in nonlinear change section, uses dynamic
The difference between exposure value is calculated to quantify the variation of illumination, fits one perfectly using illumination, reflecting rate, distance as independent variable
Function, to reaching accurate control to IRCUT and infrared lamp.
The number M of exposure value sampled point in the step 1 is at most 20 times.
The times N of exposure value sampled point in the step 2 is at most 15 times.
The time interval of exposure value sampled point in the step 2 is 2.5 seconds.
Algorithm steps：
Step 1：Init state is day mode, and under this pattern, infrared lamp closes, and IRCUT opens filter feux rouges optical filter.This
EV values energy accurate response ambient light illumination under pattern.If ev<Ev_3lux reaches 3 times, enters step 2；
Step 2：Picture EV is unstable when being switched based on picture, ignores preceding 10 second data.It is collected since the 11st second every
Data.The screening that step 3 arrives step 6 is carried out respectively；
Step 3：If between the 11st second to the 35th second, the maximum value in ev_white is more than 3 times of ev_3lux, and ev>3*
Ev_6lux, and ev<Ev_ceiling records ev_time, enters step 7；
Step 4：Under normal total darkness environment, ev>Ev_6lux reaches 3 times, records ev_time, enters step 7；
Step 5：It is low it is bright, under bright, highlighted environment, ev<Ev_env*90%/x_black reaches 3 times, shows at this point, having
People makes picture start to zoom out or ajust in adjustment camera lens, and most bright light in the case of someone records ev_time, into step
Rapid 7；
Step 6：It is low it is bright, under bright, highlighted environment, ev>Ev_env*110%*x_black reaches 3 times, show light by
Gradually turn bright, records ev_time, enter step 7；
Step 7：It checks that 2 night vision modes turn the time interval of day mode in ev_time, or is less than 120 seconds, then show
Misjudgment, regulation coefficient x_black reset coefficient x_black if the regulation coefficient time reaches 5 hours.Enter step 1.
Mutual exclusion is carried out to scene not repeat to classify
Ev_3lux is the corresponding EV values of 3LUX under day mode.
Ev_6lux is the corresponding EV values of 6LUX under night vision mode.
Ev_normal is under night vision mode, and incandescent lamp is bright, and video camera is directed at common living scene, and (object is reflective in picture
Rate is moderate), 3 meters of video camera and picture is apart from corresponding EV values.
Ev_ceiling be night vision mode under, incandescent lamp is bright, video camera be aligned ceiling (in picture object reflecting rate compared with
It is high), 3 meters of video camera and picture is apart from corresponding EV values.
Ev_extrem is under night vision mode, and incandescent lamp is bright, and half is that (object is reflective in picture for desktop in video camera dough sheet
Rate is higher), 1.5 meters of video camera and picture is apart from corresponding EV values.
Data explanation
Ev_white is under day mode, and 20 times nearest EV sample value set, is amounted to 120 seconds, and scene switching is suitable for
Express scene；
Ev_black is under night vision mode, and 6 times nearest EV sample value set, is amounted to 15 seconds；
Ev_sta is under night vision mode, and since the 11st second, 3 EV sampled the average value of value set；
Ev_env is the average value of minimum 3 EV sampling value sets under night vision mode；
ev_env>=ev_extrem is highlighted environment；
ev_env<ev_extrem&&ev_env>=ev_ceiling is middle bright ring border；
ev_env<ev_ceiling&&ev_env>=ev_normal is low-light environment；
ev_env<ev_normal&&ev_env>=ev_6lux is super low-light environment；
ev_env<Ev_6lux is normal total darkness environment；
Ev_time is the time set that night vision mode cuts day mode；
Ev is newest EV sampled values；
X_black is EV environment sensitive coefficients, more bigger more insensitive, it is ultralow it is bright, it is low it is bright, in bright, highlighted initialize respectively
It is 1,0.99,0.97,0.95, raises 15% every time.
The present invention operation principle be：The present invention is based on when day mode, EV values must reaction environment illumination this is advantageous
Condition learns different static environments, and carries out trial and error, and dynamic adjusts inner parameter, and light is quickly changed
And mobile context, quickly judged by the difference of EV values, with this 2 points fit one perfectly with illumination, reflecting rate,
Distance is the function of independent variable, to reach accurate control to IRCUT and infrared lamp.
The better embodiment of the present invention is explained in detail above, but the present invention is not limited to above-mentioned embodiment party
Formula, one skilled in the relevant art within the scope of knowledge, can also be without departing from the purpose of the present invention
Various changes can be made.
Claims (4)
1. a kind of method controlling IRCUT and infrared lamp based on exposure value and scene learning algorithm, which is characterized in that including as follows
Step：
Step 1：It is initialized as day mode, the exposure value of picture after the imaging of sampling the last time SENSOR, and in memory card
Record M EV sample values；
Step 2：EV values reach night threshold value, are switched to night pattern, the exposure of picture after the imaging of sampling the last time SENSOR
Value, and n times EV sample values are recorded in memory card；
Step 3：Compare nearest multiple exposure value sampled point, and removes maximum value and minimum value；According to day mode and night
Exposure value is divided into linear change section and nonlinear change section by pattern sampled data, in nonlinear change section, is counted using dynamic
The difference between exposure value is calculated to quantify the variation of illumination, fits one perfectly using illumination, reflecting rate, distance as independent variable
Function, to reach accurate control to IRCUT and infrared lamp.
2. a kind of method that IRCUT and infrared lamp are controlled based on exposure value and scene learning algorithm according to claim 1,
It is characterized in that, the number M of the exposure value sampled point in the step 1 is at most 20 times.
3. a kind of method that IRCUT and infrared lamp are controlled based on exposure value and scene learning algorithm according to claim 1,
It is characterized in that, the times N of the exposure value sampled point in the step 2 is at most 15 times.
4. a kind of one kind as described in claim 2 is any is based on exposure value and scene learning algorithm control IRCUT and infrared lamp
Method, which is characterized in that the time interval of the exposure value sampled point in the step 2 be 2.5 seconds.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810037912.4A CN108337443A (en) | 2018-01-16 | 2018-01-16 | A method of based on exposure value and scene learning algorithm control IRCUT and infrared lamp |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810037912.4A CN108337443A (en) | 2018-01-16 | 2018-01-16 | A method of based on exposure value and scene learning algorithm control IRCUT and infrared lamp |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108337443A true CN108337443A (en) | 2018-07-27 |
Family
ID=62924291
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810037912.4A Pending CN108337443A (en) | 2018-01-16 | 2018-01-16 | A method of based on exposure value and scene learning algorithm control IRCUT and infrared lamp |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108337443A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108900783A (en) * | 2018-09-03 | 2018-11-27 | 北京控制工程研究所 | A kind of automatic explosion method suitable for big temperature difference operative scenario |
| US11233948B2 (en) | 2018-08-22 | 2022-01-25 | Shenzhen Heytap Technology Corp., Ltd. | Exposure control method and device, and electronic device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080180553A1 (en) * | 2007-01-05 | 2008-07-31 | Object Video, Inc. | Video-based sensing for daylighting controls |
| CN104301616A (en) * | 2014-10-31 | 2015-01-21 | 苏州科达科技股份有限公司 | Method and system for controlling day-to-night switching mode of camera and method and system for controlling night-to-day switching mode of camera |
| CN104580896A (en) * | 2014-12-25 | 2015-04-29 | 深圳市锐明视讯技术有限公司 | Method and device for switching day and night modes of camera |
| CN106454145A (en) * | 2016-09-28 | 2017-02-22 | 湖南优象科技有限公司 | Automatic exposure method with scene self-adaptivity |
| CN106534700A (en) * | 2016-12-20 | 2017-03-22 | 济南中维世纪科技有限公司 | Method for realizing soft photosensitivity based on automatic exposure and automatic white balance algorithm |
-
2018
- 2018-01-16 CN CN201810037912.4A patent/CN108337443A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080180553A1 (en) * | 2007-01-05 | 2008-07-31 | Object Video, Inc. | Video-based sensing for daylighting controls |
| CN104301616A (en) * | 2014-10-31 | 2015-01-21 | 苏州科达科技股份有限公司 | Method and system for controlling day-to-night switching mode of camera and method and system for controlling night-to-day switching mode of camera |
| CN104580896A (en) * | 2014-12-25 | 2015-04-29 | 深圳市锐明视讯技术有限公司 | Method and device for switching day and night modes of camera |
| CN106454145A (en) * | 2016-09-28 | 2017-02-22 | 湖南优象科技有限公司 | Automatic exposure method with scene self-adaptivity |
| CN106534700A (en) * | 2016-12-20 | 2017-03-22 | 济南中维世纪科技有限公司 | Method for realizing soft photosensitivity based on automatic exposure and automatic white balance algorithm |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11233948B2 (en) | 2018-08-22 | 2022-01-25 | Shenzhen Heytap Technology Corp., Ltd. | Exposure control method and device, and electronic device |
| CN108900783A (en) * | 2018-09-03 | 2018-11-27 | 北京控制工程研究所 | A kind of automatic explosion method suitable for big temperature difference operative scenario |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109005366B (en) | Night scene shooting processing method and device for camera module, electronic equipment and storage medium | |
| ES2348059T3 (en) | WHITE BALANCE CONTROL CIRCUIT IN AN IMAGE CAPTURE APPARATUS. | |
| CN109194882B (en) | Image processing method, image processing device, electronic equipment and storage medium | |
| US8970716B2 (en) | Image-capturing apparatus and control method of the image-capturing apparatus | |
| CN101115149B (en) | Image processing method | |
| WO2013121073A1 (en) | Method and apparatus for enhanced automatic adjustment of focus, exposure and white balance in digital photography | |
| CN102055911A (en) | Imaging apparatus and imaging apparatus control method | |
| KR101322829B1 (en) | Closed circuit television system using time of sunrise and sunset | |
| CN108337443A (en) | A method of based on exposure value and scene learning algorithm control IRCUT and infrared lamp | |
| US5568195A (en) | Image pickup device with white balance function | |
| Torres et al. | Optimal camera exposure for video surveillance systems by predictive control of shutter speed, aperture, and gain | |
| US7554601B2 (en) | Digital video camera with automatic white balance and a method thereof | |
| JP2899031B2 (en) | Automatic exposure control device | |
| KR20060116713A (en) | White balance controlling apparatus, method, program and image pickup apparatus | |
| CN105611189A (en) | Automatic exposure parameter adjustment method and device and user equipment | |
| CN101483717A (en) | Digital photographing apparatus and method for controlling the same | |
| JP3554069B2 (en) | Imaging device | |
| CN108881734B (en) | Image acquisition method and device | |
| US10250827B2 (en) | Imaging apparatus and control method thereof | |
| CN1751500B (en) | Electronic camera | |
| CN113994660B (en) | Intelligent flash intensity control system and method | |
| JPH08205021A (en) | Image input device | |
| KR950006239B1 (en) | Auto-iris method and apparatus for imaging device | |
| JP4958732B2 (en) | Flicker correction device | |
| US20080007628A1 (en) | Adaptive CCTV camera system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |