CN103702111A - Method for detecting camera video color cast - Google Patents
Method for detecting camera video color cast Download PDFInfo
- Publication number
- CN103702111A CN103702111A CN201310722639.6A CN201310722639A CN103702111A CN 103702111 A CN103702111 A CN 103702111A CN 201310722639 A CN201310722639 A CN 201310722639A CN 103702111 A CN103702111 A CN 103702111A
- Authority
- CN
- China
- Prior art keywords
- video
- frame
- colour cast
- image
- gray scale
- 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.)
- Granted
Links
Images
Landscapes
- Image Analysis (AREA)
- Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)
Abstract
The invention discloses a method for detecting camera video color cast. The method comprises the following steps: receiving a multi-frame video; judging the color cast of each frame in the video in a processing method of calling video frame colors according to frames; judging a gray level of the video by integrating a gray level of the multi-frame video; judging the video color cast by integrating a color cast value of the multi-frame video. By detecting the color cast failure of an image of the video, a set of quantitive detection indexes are established, the burden of human eye recognition can be alleviated, and errors caused by subjective judgment can be reduced.
Description
Technical field
The present invention relates to a kind of method that detects camera video colour cast, belong to technical field of video image processing.
Background technology
Along with economic development, security device has spread all over each corner of people's life gradually, video monitoring system scale is increasing, monitored picture quantity is also more and more, only depend on human eye to investigate one by one video pictures, efficiency is very low, and therefore intelligentized video failure diagnosis importance highlights day by day.
Conventionally, due to the impact of the reflection characteristic of environment light source, object itself and the factors such as sensitization coefficient of collecting device, between the color of image capture device collection image and true picture color, there are differences, i.e. colour cast phenomenon.Mainly there are following two aspects, on the one hand, digital imaging apparatus is when imaging, and the energy of storing in its sensitive component not only depends on the surface color of subject, also will be subject to the impact of the factors such as physical characteristic of extraneous light conditions at that time, sensitive component.Therefore, between the color of the digital picture that imaging device is captured and the realistic colour of subject surface, there is error to a certain degree, i.e. colour cast.If can detect exactly digital picture, whether there is colour cast, can provide for the subsequent treatment of digital picture effective reference.On the other hand.In order to save bandwidth, when transmitting, monitoring video data, more prevalent use Video Coding Compression Technology carries out Internet Transmission.Yet, at video data, carry out in transmitting procedure, not only the factor such as ageing equipment fault and transmission line can make video image produce video colour cast, and video data through encoder compresses process in, the chromatic noise that also can introduce, these chromatic noises also can cause the colour cast of video data.
In prior art, the detection method of the image color cast of employing mainly comprises gray scale world method, white portion method, neural network and priori method.Yet these methods all have certain limitation, cannot correctly detect reliably the colour cast of image.
The accuracy that the existence of colour cast phenomenon is processed to image has been brought difficulty, and therefore image being carried out to color cast detection and colour cast proofread and correct is a very crucial link.The previous work that color cast detection is proofreaied and correct as colour cast, comprises and detects in image whether have colour cast and colour cast degree, have in actual applications extremely important using value.Rely on artificial investigation not only to waste time and energy, and easily occur failing to report, people's subjective criterion is difficult to unify also to cause alarming result to be lack of consistency in addition.Therefore in the present and following all kinds of video surveillance applications, need to have the O&M system of automatic failure detection function, this function is by the necessary functions assembly becoming in video monitoring system.
A kind of detection method of image color cast is provided in the Chinese invention patent application that publication No. is CN102169585A.The method comprises: image to be detected is converted to hsv color spatial image; From described hsv color spatial image, extract S channel image; Calculate the comentropy of described S channel image; When the comentropy of described S channel image is greater than predetermined threshold value, determine that described image to be detected exists colour cast.This technical scheme can not be subject to the limitation of scene or priori, has general adaptability, has improved accuracy rate and the reliability of color cast detection simultaneously.
Summary of the invention
For the existing deficiency of prior art, technical problem to be solved by this invention is to provide a kind of method that detects camera video colour cast.The method can alleviate the burden of eye recognition, reduces the error that subjective judgement produces.
For realizing above-mentioned goal of the invention, the present invention adopts following technical scheme:
Detect a method for camera video colour cast, it is characterized in that comprising the steps:
Receive multi-frame video;
Call frame by frame frame of video color processing method each frame in video is done to colour cast judgement;
Comprehensive multi-frame video gray value is judged video gradation;
Comprehensive multi-frame video colour cast value is judged video colour cast.
Wherein more preferably, described frame of video color processing method further comprises the steps:
Receive a frame video;
Video data is changed into RGB coloured image;
Convert RGB coloured image to HSV chromaticity diagram;
Calculate color saturation value;
If color saturation value is less than saturation threshold value, judge that this image is as gray level image; If color saturation value is less than saturation threshold value, the chroma histogram of computed image;
Pick out the colourity that number of pixels is maximum interval, and calculate the ratio of the interval pixel of colourity station image;
If the ratio of the interval pixel of colourity station image is greater than the interval pixel threshold of colourity, judge that present image is as colour cast image; If the ratio of the interval pixel of colourity station image is not more than the interval pixel threshold of colourity, judge that present image is as colour cast image not.
Wherein more preferably, the mean value that described color saturation value is color saturation.
Wherein more preferably, described comprehensive multi-frame video gray value judges that the step of video gradation further comprises:
The gray scale number of frames of comprehensive multi-frame video, if the gray scale frame number of multi-frame video is greater than gray scale frame number threshold value, judges that multi-frame video is as gray scale; If the gray scale frame number of multi-frame video is not more than gray scale frame number threshold value, further judge whether multi-frame video is colour cast.
Wherein more preferably, described comprehensive multi-frame video colour cast value judges that the step of video colour cast further comprises:
The gray scale number of frames of comprehensive multi-frame video, if the gray scale frame number of multi-frame video is greater than colour cast frame number threshold value, judges that multi-frame video is as gray scale; If the gray scale frame number of multi-frame video is not more than gray scale frame number threshold value, judge that multi-frame video is as colour cast.
The method of detection camera video colour cast provided by the present invention, by detecting the colour cast fault in video image, sets up the detection index of a set of value, can alleviate the burden of eye recognition, reduces the error that subjective judgement produces.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of detection camera video colour cast method provided by the present invention;
Fig. 2 is in the present invention, the schematic flow sheet of frame of video color processing method.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail.
As shown in Figure 1, the invention provides a kind of method that detects camera video colour cast, comprise the steps: to receive multi-frame video; Call frame by frame frame of video color processing method each frame in video is done to colour cast judgement; Comprehensive multi-frame video gray value is judged video gradation; Comprehensive multi-frame video colour cast value is judged video colour cast.The present invention is launched to detailed explanation below.
As shown in Figure 1, computer receives after multi-frame video, and each frame of video of this multi-frame video is called respectively to frame of video color processing method, and the frame of video of multi-frame video is done to colour cast identifying processing.As shown in Figure 2, frame of video color processing method is launched to explanation below.
1) receive a frame video;
2) this one-frame video data receiving is changed into RGB color video two field picture;
3) convert the RGB color video two field picture after conversion to HSV color video frame images;
4) by HSV algorithm, calculate the color saturation value of HSV color video frame images; The color saturation value is here the mean value of the color saturation of all pixels;
5), according to the color saturation value of HSV color video frame images and the comparison of predefined saturation threshold value, determine whether HSV color video frame images is gray level image.If color saturation value is less than saturation threshold value, judge that this video frame images is as gray level image; If color saturation value is not less than saturation threshold value, calculate the chroma histogram of video frame images;
6) statistics Colour is picked out the colourity that number of pixels is maximum interval from HSV color video frame images, and calculates the ratio that the interval pixel of colourity accounts for the total pixel of video frame images;
7), according to the interval pixel threshold comparison of HSV color video frame images and predefined colourity, determine whether colour cast of HSV color video frame images.If the ratio that the interval pixel of colourity accounts for the total pixel of video frame images is greater than the interval pixel threshold of colourity, judge that current video two field picture is as colour cast image; If the interval pixel of colourity accounts for the ratio of the total pixel of video frame images and is not more than the interval pixel threshold of colourity, judge that current video two field picture is as colour cast image not.
As shown in Figure 1, the testing result of video frame images color exception in statistics multi-frame video a period of time, if be judged to be the ratio that the video frame images number of gray scale accounts for whole video frame images sequence, be greater than predefined gray scale frame number threshold value, so just confirm that current multi-frame video is greyscale video.If be judged to be the ratio that the video frame images number of colour cast accounts for whole video frame images sequence, be greater than predefined colour cast frame number threshold value, so just confirm that current multi-frame video exists colour cast.Wherein, the colourity of current multi-frame video colour cast be during this period of time in the mean value of video frame images colour cast numerical value, the colour cast saturation of current multi-frame video be the mean value of interior video frame images saturation during this period of time.
In sum, the present invention, by automatically detecting video image quality, has alleviated the burden of artificial judgment.The present invention further provides a kind of colour cast quality index of quantification, the difference of avoiding human eye subjective judgement to cause; Integrated using saturation and Colour algorithm, reduce and detect error.
Above the method for detection camera video colour cast provided by the present invention is had been described in detail.For one of ordinary skill in the art, any apparent change of under the prerequisite that does not deviate from connotation of the present invention, it being done, all will form infringement of patent right of the present invention, will bear corresponding legal liabilities.
Claims (5)
1. detect a method for camera video colour cast, it is characterized in that comprising the steps:
Receive multi-frame video;
Call frame by frame frame of video color processing method each frame in video is done to colour cast judgement;
Comprehensive multi-frame video gray value is judged video gradation;
Comprehensive multi-frame video colour cast value is judged video colour cast.
2. the method for detection camera video colour cast as claimed in claim 1, is characterized in that, described frame of video color processing method further comprises the steps:
Receive a frame video;
Video data is changed into RGB coloured image;
Convert RGB coloured image to HSV chromaticity diagram;
Calculate color saturation value;
If color saturation value is less than saturation threshold value, judge that this image is as gray level image; If color saturation value is less than saturation threshold value, the chroma histogram of computed image;
Pick out the colourity that number of pixels is maximum interval, and calculate the ratio of the interval pixel of colourity station image;
If the ratio of the interval pixel of colourity station image is greater than the interval pixel threshold of colourity, judge that present image is as colour cast image; If the ratio of the interval pixel of colourity station image is not more than the interval pixel threshold of colourity, judge that present image is as colour cast image not.
3. the method for detection camera video colour cast as claimed in claim 2, is characterized in that, described color saturation value is the mean value of color saturation.
4. the method for detection camera video colour cast as claimed in claim 1, is characterized in that, described comprehensive multi-frame video gray value judges that the step of video gradation further comprises:
The gray scale number of frames of comprehensive multi-frame video, if the gray scale frame number of multi-frame video is greater than gray scale frame number threshold value, judges that multi-frame video is as gray scale; If the gray scale frame number of multi-frame video is not more than gray scale frame number threshold value, further judge whether multi-frame video is colour cast.
5. the method for detection camera video colour cast as claimed in claim 1, is characterized in that, described comprehensive multi-frame video colour cast value judges that the step of video colour cast further comprises:
The gray scale number of frames of comprehensive multi-frame video, if the gray scale frame number of multi-frame video is greater than colour cast frame number threshold value, judges that multi-frame video is as gray scale; If the gray scale frame number of multi-frame video is not more than gray scale frame number threshold value, judge that multi-frame video is as colour cast.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310722639.6A CN103702111B (en) | 2013-12-24 | 2013-12-24 | A kind of method detecting camera video color cast |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310722639.6A CN103702111B (en) | 2013-12-24 | 2013-12-24 | A kind of method detecting camera video color cast |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103702111A true CN103702111A (en) | 2014-04-02 |
| CN103702111B CN103702111B (en) | 2016-01-27 |
Family
ID=50363497
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310722639.6A Expired - Fee Related CN103702111B (en) | 2013-12-24 | 2013-12-24 | A kind of method detecting camera video color cast |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103702111B (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105761285A (en) * | 2016-02-25 | 2016-07-13 | 浙江合腾信息科技有限公司 | Abnormality detection method for bluish captured image |
| CN105791817A (en) * | 2016-04-29 | 2016-07-20 | 北京牡丹视源电子有限责任公司 | Method of assessing video image color reduction degree and system thereof |
| CN106993185A (en) * | 2015-12-10 | 2017-07-28 | 青岛海信网络科技股份有限公司 | A kind of video quality diagnosing method and system |
| CN106998464A (en) * | 2016-01-26 | 2017-08-01 | 北京佳讯飞鸿电气股份有限公司 | Detect the method and device of thorn-like noise in video image |
| CN107272637A (en) * | 2017-06-06 | 2017-10-20 | 武汉瑞科兴业科技有限公司 | A kind of video monitoring system fault self-checking self- recoverage control system and method |
| CN110516725A (en) * | 2019-08-16 | 2019-11-29 | 三峡大学 | The detection method of plank fringe spacing and color based on machine vision |
| CN110662024A (en) * | 2019-10-31 | 2020-01-07 | 上海中铁通信信号测试有限公司 | Video quality diagnosis method and device based on multiple frames and electronic equipment |
| CN111225202A (en) * | 2018-11-27 | 2020-06-02 | 杭州海康威视数字技术股份有限公司 | Picture fault diagnosis method, device and system |
| CN111402189A (en) * | 2018-12-28 | 2020-07-10 | 山东华软金盾软件股份有限公司 | Video image color cast detection device and method |
| CN115278217A (en) * | 2022-07-21 | 2022-11-01 | 深圳市震有软件科技有限公司 | Image picture detection method and device, electronic equipment and storage medium |
| WO2022228032A1 (en) * | 2021-04-27 | 2022-11-03 | 青岛海尔电冰箱有限公司 | Image color cast detection method, device, and refrigerator |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006345187A (en) * | 2005-06-08 | 2006-12-21 | Canon Inc | Color processing method and device thereof |
| US20070146747A1 (en) * | 2005-12-28 | 2007-06-28 | Kwe International, Inc. | Editing (including hue editing) of digital color images |
| CN102169585A (en) * | 2011-03-31 | 2011-08-31 | 汉王科技股份有限公司 | Method and device for detecting image color cast |
| CN102395043A (en) * | 2011-11-11 | 2012-03-28 | 北京声迅电子股份有限公司 | Video quality diagnosing method |
| CN103065334A (en) * | 2013-01-31 | 2013-04-24 | 金陵科技学院 | Color cast detection and correction method and device based on HSV (Hue, Saturation, Value) color space |
| CN103402117A (en) * | 2013-08-06 | 2013-11-20 | 夏东 | Method for detecting color cast of video image based on Lab chrominance space |
-
2013
- 2013-12-24 CN CN201310722639.6A patent/CN103702111B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006345187A (en) * | 2005-06-08 | 2006-12-21 | Canon Inc | Color processing method and device thereof |
| US20070146747A1 (en) * | 2005-12-28 | 2007-06-28 | Kwe International, Inc. | Editing (including hue editing) of digital color images |
| CN102169585A (en) * | 2011-03-31 | 2011-08-31 | 汉王科技股份有限公司 | Method and device for detecting image color cast |
| CN102395043A (en) * | 2011-11-11 | 2012-03-28 | 北京声迅电子股份有限公司 | Video quality diagnosing method |
| CN103065334A (en) * | 2013-01-31 | 2013-04-24 | 金陵科技学院 | Color cast detection and correction method and device based on HSV (Hue, Saturation, Value) color space |
| CN103402117A (en) * | 2013-08-06 | 2013-11-20 | 夏东 | Method for detecting color cast of video image based on Lab chrominance space |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106993185A (en) * | 2015-12-10 | 2017-07-28 | 青岛海信网络科技股份有限公司 | A kind of video quality diagnosing method and system |
| CN106998464A (en) * | 2016-01-26 | 2017-08-01 | 北京佳讯飞鸿电气股份有限公司 | Detect the method and device of thorn-like noise in video image |
| CN106998464B (en) * | 2016-01-26 | 2019-02-26 | 北京佳讯飞鸿电气股份有限公司 | Detect the method and device of thorn-like noise in video image |
| CN105761285A (en) * | 2016-02-25 | 2016-07-13 | 浙江合腾信息科技有限公司 | Abnormality detection method for bluish captured image |
| CN105791817A (en) * | 2016-04-29 | 2016-07-20 | 北京牡丹视源电子有限责任公司 | Method of assessing video image color reduction degree and system thereof |
| CN105791817B (en) * | 2016-04-29 | 2018-10-16 | 北京牡丹视源电子有限责任公司 | A kind of method and system of test and appraisal video image color rendition degree |
| CN107272637A (en) * | 2017-06-06 | 2017-10-20 | 武汉瑞科兴业科技有限公司 | A kind of video monitoring system fault self-checking self- recoverage control system and method |
| CN107272637B (en) * | 2017-06-06 | 2019-08-30 | 武汉瑞科兴业科技有限公司 | A kind of video monitoring system fault self-checking self- recoverage control system and method |
| CN111225202B (en) * | 2018-11-27 | 2022-02-11 | 杭州海康威视数字技术股份有限公司 | Picture fault diagnosis method, device and system |
| CN111225202A (en) * | 2018-11-27 | 2020-06-02 | 杭州海康威视数字技术股份有限公司 | Picture fault diagnosis method, device and system |
| CN111402189A (en) * | 2018-12-28 | 2020-07-10 | 山东华软金盾软件股份有限公司 | Video image color cast detection device and method |
| CN111402189B (en) * | 2018-12-28 | 2023-10-31 | 山东华软金盾软件股份有限公司 | Video image color cast detection device and method |
| CN110516725A (en) * | 2019-08-16 | 2019-11-29 | 三峡大学 | The detection method of plank fringe spacing and color based on machine vision |
| CN110516725B (en) * | 2019-08-16 | 2023-08-01 | 三峡大学 | Machine vision-based wood board stripe spacing and color detection method |
| CN110662024A (en) * | 2019-10-31 | 2020-01-07 | 上海中铁通信信号测试有限公司 | Video quality diagnosis method and device based on multiple frames and electronic equipment |
| WO2022228032A1 (en) * | 2021-04-27 | 2022-11-03 | 青岛海尔电冰箱有限公司 | Image color cast detection method, device, and refrigerator |
| CN115278217A (en) * | 2022-07-21 | 2022-11-01 | 深圳市震有软件科技有限公司 | Image picture detection method and device, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103702111B (en) | 2016-01-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103702111B (en) | A kind of method detecting camera video color cast | |
| Martini et al. | Image quality assessment based on edge preservation | |
| US9076037B2 (en) | Image processing apparatus and method | |
| CN105049743B (en) | Backlighting detecting, backlight detection system, photographing device and terminal | |
| CN105791709A (en) | Automatic exposure processing method and apparatus with back-light compensation | |
| JP2014053855A (en) | Image processing device and method, and program | |
| CN102169585A (en) | Method and device for detecting image color cast | |
| CN104168478B (en) | Based on the video image color cast detection method of Lab space and relevance function | |
| CN105872399B (en) | Backlighting detecting and backlight detection system | |
| CN115065798B (en) | Big data-based video analysis monitoring system | |
| US10121453B2 (en) | Bit rate controller and a method for limiting output bit rate | |
| CN112367520B (en) | Video quality diagnosis system based on artificial intelligence | |
| CN105227843A (en) | The filming control method of terminal, the imaging control device of terminal and terminal | |
| CN107146252A (en) | A kind of big data image processing apparatus | |
| CN109461156B (en) | Threaded sealing plug assembly detection method based on vision | |
| CN107547839A (en) | Remote control table based on graphical analysis | |
| CN112489018B (en) | Intelligent line inspection method and line inspection method for power line | |
| CN103942523A (en) | Sunshine scene recognition method and device | |
| US20140327796A1 (en) | Method for estimating camera response function | |
| CN116749817A (en) | Remote control method and system for charging pile | |
| CN111160299A (en) | Living body identification method and device | |
| CN103226690A (en) | Red eye detection method and device and red eye removing method and device | |
| CN114092437B (en) | Transformer leakage oil detection method | |
| CN101483721A (en) | Video processing method and video capturing apparatus applying the method | |
| JP2008252402A (en) | Imaging system, imaging method, and imaging program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20160127 Termination date: 20201224 |