CN110427808A - Police uniform recognition methods based on video stream data - Google Patents
Police uniform recognition methods based on video stream data Download PDFInfo
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- CN110427808A CN110427808A CN201910543624.0A CN201910543624A CN110427808A CN 110427808 A CN110427808 A CN 110427808A CN 201910543624 A CN201910543624 A CN 201910543624A CN 110427808 A CN110427808 A CN 110427808A
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Abstract
The invention discloses the police uniform recognition methods based on video stream data, comprising the following steps: Step 1: obtaining the prison prisoner zone of action video stream data in prison；Step 2: moving target is extracted；Step 3: human body target matches；Step 4: police uniform color-match；Step 5: police uniform characteristic matching, judges whether it is police uniform style complies with set.The present invention is based on the police uniform recognition methods of video stream data to replace manually carrying out specified region policeman on duty detection on the scene, region prison guard's personal management are enhanced, to ensure that prison takes the personal safety and stabilization of personnel into custody.
Description
Technical field
The present invention relates to prison field of security technologies, particularly relate to a kind of police uniform identification based on video stream data
Method.
Background technique
Prison is the place for putting in prison and being transformed criminal, all the time, ensures the personal safety of the personnel that taken into custody and steady
It surely is the matter of utmost importance in prison.With the continuous renewal of the gradual perfection and prison political affairs facility of prison administration system, prison prevention and
The ability for controlling various security incidents greatly enhances.In addition to grasp the basic of each controlled area personnel under detention in prison in real time
Situation, effectively prevent running away for personnel under detention, reduces criminal and cliques the probability made trouble, and secret monitors high-risk personnel under detention, traces
And the generation of follow-up incident of violence, the personal safety of administrative staff and personnel under detention are ensured to greatest extent.In addition, also needing automatic
It identifies policeman's information on duty in specified region, guarantees that specified region policeman on duty is on the scene, not only increase region prison guard people in this way
Member's management, and ensure that prison takes the personal safety and stabilization of personnel into custody.
Summary of the invention
To solve the problems mentioned above in the background art, the purpose of the present invention is to provide one kind to be based on video stream data
Police uniform recognition methods.
To achieve the above object, the technical scheme adopted by the invention is as follows:
The police uniform recognition methods based on video stream data that the present invention provides a kind of, comprising the following steps:
Step 1: video stream data obtains
Camera is arranged in prison prisoner zone of action at the prison, obtains camera video stream, and to video stream data into
Row RGB conversion, makes it be converted to corresponding color image；
Step 2: moving target is extracted
By carrying out background modeling to the n frame picture obtained in video, then the moving target in n+1 frame picture is carried out
Frame is poor, and n+1 frame pixel value I (x, y) is subtracted to the average value u (x, y) of same position pixel in background model, obtains difference d
Difference d (x, y) is then compared by (x, y) with threshold value TH, when difference d (x, y) is greater than threshold value TH, then before being labeled as
Sight spot；Otherwise, it is labeled as background dot；
Judge whether the moving target continuously moves by the continuous frame in foreground point, if it is continuous to occur, if being not achieved
Continuous N frame occurs, then filters；Conversely, the continuous N frame of the moving target occurs, and the X, Y coordinates of moving target are greater than i picture in N frame
Vegetarian refreshments is then judged as persistent movement, obtains the foreground picture of moving target；Wherein, [1,200] N=, the size of N value, is reflected as
The time span of object observing, this value is smaller, then the reaction time for providing judgement is faster, sensitiveer；
Step 3: human body target matches
It is judged as that the foreground picture of moving target is matched with characteristics of human body's model in interception step 2, if more than acquaintance
M is spent, then judges there is human body target in foreground picture, and is entered in next step；Conversely, then judging there is no human body in object to be measured image
Target, and return step two continues the extraction operation of moving target；Wherein [0,1] M=, M value is bigger, indicates that target is behaved
A possibility that it is higher；
Step 4: police uniform color-match
Color reduction is carried out to the human body target picture being truncated in step 3 by YUV color algorithm, and by area
Similar similar color point is merged connection by the monitoring of block；If black, blue after monitoring black, blue block and/or merging
Block region is greater than L pixel, then judges that clothes color is matched with police uniform, into next step；On the contrary then return step two；Wherein, L picture
Element is police uniform minimum pixel required value under different resolution；Under 1080 × 720 resolution ratio, L pixel adjusting range be 100~
1600 pixels correspond to the rectangle of 10 × 10~40 × 40 pixels；
Step 5: police uniform characteristic matching
The human region picture of the police uniform color-match got in step 4 is matched with police uniform characteristic model, if
Phase knowledge and magnanimity are greater than P and are then judged as police uniform style complies with set, and on the contrary then return step two, wherein the value range of P is [0,1],
Required precision is higher, then closer to 1；
In above-mentioned technical proposal, characteristics of human body's model in step 3 is by neural network model training classifier
What training and identification obtained, method particularly includes:
When training, a large amount of human body pictures are inputted as positive sample, inputs largely without human body picture as negative sample, passes through mind
It is trained through network model training classifier and learns and obtain characteristics of human body's model；
When identification, the foreground picture of input motion target is instructed by the foreground picture and neural network model of moving target
The characteristics of human body's model practiced in classifier carries out identification matching, if more than phase knowledge and magnanimity S, then judges there is human body mesh in foreground picture
Mark, S=[0,1], S are higher to show that target more meets characteristics of human body.
In above-mentioned technical proposal, police uniform characteristic model described in step 5 is by neural network model training classifier instruction
What white silk and identification obtained, method particularly includes:
When training, a large amount of police uniform pictures are inputted as positive sample, inputs largely without police uniform picture as negative sample, passes through mind
It is trained through network model training classifier and learns and obtain police uniform characteristic model；
When identification, input meets the region picture of police uniform color characteristic, by training in classifier with neural network model
Police uniform characteristic model carry out identification matching, if more than phase knowledge and magnanimity T, then judge region picture for police uniform target, wherein T=[0,
1], T value is higher shows that target more meets police uniform feature.
Compared with prior art, the beneficial effects of the present invention are:
It is on the scene to replace manually carrying out specified region policeman on duty that the present invention is based on the police uniform recognition methods of video stream data
Detection, region prison guard's personal management is enhanced, to ensure that prison takes the personal safety and stabilization of personnel into custody.
Detailed description of the invention
Fig. 1 is the flow chart of the police uniform recognition methods provided by the invention based on video stream data；
Fig. 2 is stream of the characteristics of human body's model of the present invention by neural network model training classifier training and identification
Cheng Tu；
Fig. 3 is flow chart of the police uniform type of the present invention by SVM training aids training and identification.
Specific embodiment
To be easy to understand the technical means, the creative features, the aims and the efficiencies achieved by the present invention, below with reference to
The drawings and specific embodiments, how the present invention is further explained implements.
The police uniform recognition methods based on video stream data that the present invention provides a kind of, comprising the following steps:
Step 1: video stream data obtains
Camera is arranged in prison prisoner zone of action at the prison, obtains camera video stream, and to video stream data into
Row RGB conversion, makes it be converted to corresponding color image；
Step 2: moving target is extracted
By carrying out background modeling to the n frame picture obtained in video, then the moving target in n+1 frame picture is carried out
Frame is poor, and n+1 frame pixel value I (x, y) is subtracted to the average value u (x, y) of same position pixel in background model, obtains difference d
Difference d (x, y) is then compared by (x, y) with threshold value TH, when difference d (x, y) is greater than threshold value TH, then before being labeled as
Sight spot；Otherwise, it is labeled as background dot；
Judge whether the moving target continuously moves by the continuous frame in foreground point, if it is continuous to occur, if being not achieved
Continuous N frame occurs, then filters；Conversely, the continuous N frame of the moving target occurs, and the X, Y coordinates of moving target are greater than i picture in N frame
Vegetarian refreshments is then judged as persistent movement, obtains the foreground picture of moving target；Wherein, [1,200] N=, the size of N value, is reflected as
The time span of object observing, this value is smaller, then the reaction time for providing judgement is faster, sensitiveer；
Step 3: human body target matches
It is judged as that the foreground picture of moving target is matched with characteristics of human body's model in interception step 2, if more than acquaintance
M is spent, then judges there is human body target in foreground picture, and is entered in next step；Conversely, then judging there is no human body in object to be measured image
Target, and return step two continues the extraction operation of moving target；Wherein [0,1] M=, M value is bigger, indicates that target is behaved
A possibility that it is higher；
Step 4: police uniform color-match
Color reduction is carried out to the human body target picture being truncated in step 3 by YUV color algorithm, and by area
Similar similar color point is merged connection by the monitoring of block；If black, blue after monitoring black, blue block and/or merging
Block region is greater than L pixel, then judges that clothes color is matched with police uniform, into next step；On the contrary then return step two；Wherein, L picture
Element is police uniform minimum pixel required value under different resolution；Under 1080 × 720 resolution ratio, L pixel adjusting range be 100~
1600 pixels correspond to the rectangle of 10 × 10~40 × 40 pixels；
Step 5: police uniform characteristic matching
The human region picture of the police uniform color-match got in step 4 is matched with police uniform characteristic model, if
Phase knowledge and magnanimity are greater than P and are then judged as police uniform style complies with set, and on the contrary then return step two, wherein the value range of P is [0,1],
Required precision is higher, then closer to 1；
In above-mentioned technical proposal, characteristics of human body's model in step 3 is by neural network model training classifier
What training and identification obtained, method particularly includes:
When training, a large amount of human body pictures are inputted as positive sample, inputs largely without human body picture as negative sample, passes through mind
It is trained through network model training classifier and learns and obtain characteristics of human body's model；
When identification, the foreground picture of input motion target is instructed by the foreground picture and neural network model of moving target
The characteristics of human body's model practiced in classifier carries out identification matching, if more than phase knowledge and magnanimity S, then judges there is human body mesh in foreground picture
Mark, S=[0,1], S are higher to show that target more meets characteristics of human body.
In above-mentioned technical proposal, police uniform characteristic model described in step 5 is by neural network model training classifier instruction
What white silk and identification obtained, method particularly includes:
When training, a large amount of police uniform pictures are inputted as positive sample, inputs largely without police uniform picture as negative sample, passes through mind
It is trained through network model training classifier and learns and obtain police uniform characteristic model；
When identification, input meets the region picture of police uniform color characteristic, by training in classifier with neural network model
Police uniform characteristic model carry out identification matching, if more than phase knowledge and magnanimity T, then judge region picture for police uniform target, wherein T=[0,
1], T value is higher shows that target more meets police uniform feature.
Finally, it is stated that the above examples are only used to illustrate the technical scheme of the present invention and are not limiting, although referring to compared with
Good embodiment describes the invention in detail, those skilled in the art should understand that, it can be to skill of the invention
Art scheme is modified or replaced equivalently, and without departing from the objective and range of technical solution of the present invention, should all be covered at this
In the scope of the claims of invention.
Claims (3)
1. the police uniform recognition methods based on video stream data, which comprises the following steps:
Step 1: video stream data obtains
Camera is arranged in prison prisoner zone of action at the prison, obtains camera video stream, and carry out RGB to video stream data
Conversion, makes it be converted to corresponding color image；
Step 2: moving target is extracted
By carrying out background modeling to the n frame picture obtained in video, frame then is carried out to the moving target in n+1 frame picture
N+1 frame pixel value I (x, y) is subtracted the average value u (x, y) of same position pixel in background model by difference, obtain difference d (x,
Y), then difference d (x, y) is compared with threshold value TH, when difference d (x, y) is greater than threshold value TH, is then labeled as prospect
Point；Otherwise, it is labeled as background dot；
Judge whether the moving target continuously moves by the continuous frame in foreground point, if it is continuous to occur, if continuous N is not achieved
Frame occurs, then filters；Conversely, the continuous N frame of the moving target occurs, and the X, Y coordinates of moving target are greater than i pixel in N frame,
Then it is judged as persistent movement, obtains the foreground picture of moving target；Wherein, [1,200] N=, the size of N value are reflected as observing
The time span of target, this value is smaller, then the reaction time for providing judgement is faster, sensitiveer；I is expressed as both horizontally and vertically
On position amount of pixels, the value range [1,20] of i, i is smaller, detect it is sensitiveer；
Step 3: human body target matches
It is judged as that the foreground picture of moving target is matched with characteristics of human body's model in interception step 2, if more than phase knowledge and magnanimity M,
Then judge there is human body target in foreground picture, and enters in next step；Conversely, then judging there is no human body mesh in object to be measured image
Mark, and return step two continues the extraction operation of moving target；Wherein [0,1] M=, M value is bigger, indicates that target is people's
Possibility is higher；
Step 4: police uniform color-match
Color reduction is carried out to the human body target picture being truncated in step 3 by YUV color algorithm, and by block
Similar similar color point is merged connection by monitoring；If black, the blue block area after monitoring black, blue block and/or merging
Domain is greater than L pixel, then judges that clothes color is matched with police uniform, into next step；On the contrary then return step two；Wherein, L pixel is
Police uniform minimum pixel required value under different resolution, under 1080 × 720 resolution ratio, L pixel adjusting range is 100~1600
A pixel corresponds to the rectangle of 10 × 10~40 × 40 pixels；
Step 5: police uniform characteristic matching
The human region picture of the police uniform color-match got in step 4 is matched with police uniform characteristic model, if acquaintance
Degree is greater than P and is then judged as police uniform style complies with set, and on the contrary then return step two, wherein the value range of P is [0,1], precision
It is required that it is higher, then closer to 1.
2. the police uniform recognition methods according to claim 1 based on video stream data, it is characterised in that: the institute in step 3
Stating characteristics of human body's model is obtained by neural network model training classifier training and identification, method particularly includes:
When training, a large amount of human body pictures are inputted as positive sample, inputs largely without human body picture as negative sample, passes through nerve net
Network model training classifier, which is trained, to be learnt and obtains characteristics of human body's model；
When identification, the foreground picture of input motion target passes through foreground picture and the neural network model training point of moving target
Characteristics of human body's model in class device carries out identification matching, if more than phase knowledge and magnanimity S, then judges there is human body target, S=in foreground picture
[0,1], S is higher to show that target more meets characteristics of human body.
3. the police uniform recognition methods of video stream data according to claim 1, which is characterized in that police uniform described in step 5
Characteristic model is obtained by neural network model training classifier training and identification, method particularly includes:
When training, a large amount of police uniform pictures are inputted as positive sample, inputs largely without police uniform picture as negative sample, passes through nerve net
Network model training classifier, which is trained, to be learnt and obtains police uniform characteristic model；
When identification, input meets the region picture of police uniform color characteristic, by training the police in classifier with neural network model
Take characteristic model and carry out identification matching, if more than phase knowledge and magnanimity T, then judge region picture for police uniform target, wherein [0,1] T=, T
Value is higher to show that target more meets police uniform feature.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112949367A (en) * | 2020-07-07 | 2021-06-11 | 南方电网数字电网研究院有限公司 | Method and device for detecting color of work clothes based on video stream data |
| CN113067845A (en) * | 2020-12-06 | 2021-07-02 | 泰州市朗嘉馨网络科技有限公司 | On-duty detection platform applying numerical analysis |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103745226A (en) * | 2013-12-31 | 2014-04-23 | 国家电网公司 | Dressing safety detection method for worker on working site of electric power facility |
| CN104063722A (en) * | 2014-07-15 | 2014-09-24 | 国家电网公司 | Safety helmet identification method integrating HOG human body target detection and SVM classifier |
| CN105069466A (en) * | 2015-07-24 | 2015-11-18 | 成都市高博汇科信息科技有限公司 | Pedestrian clothing color identification method based on digital image processing |
| CN105488490A (en) * | 2015-12-23 | 2016-04-13 | 天津天地伟业数码科技有限公司 | Judge dressing detection method based on video |
| CN106599781A (en) * | 2016-11-08 | 2017-04-26 | 国网山东省电力公司威海供电公司 | Electric power business hall dressing normalization identification method based on color and Hu moment matching |
| CN107909580A (en) * | 2017-11-01 | 2018-04-13 | 深圳市深网视界科技有限公司 | A kind of pedestrian wears color identification method, electronic equipment and storage medium clothes |
| CN108052900A (en) * | 2017-12-12 | 2018-05-18 | 成都睿码科技有限责任公司 | A kind of method by monitor video automatic decision dressing specification |
| CN108319934A (en) * | 2018-03-20 | 2018-07-24 | 武汉倍特威视系统有限公司 | Safety cap wear condition detection method based on video stream data |
| CN108460358A (en) * | 2018-03-20 | 2018-08-28 | 武汉倍特威视系统有限公司 | Safety cap recognition methods based on video stream data |
| CN109101922A (en) * | 2018-08-10 | 2018-12-28 | 广东电网有限责任公司 | Operating personnel device, assay, device and electronic equipment |
| CN109214467A (en) * | 2018-10-17 | 2019-01-15 | 广东电网有限责任公司 | Consider power transformation operation personnel's dressing Robust identifying method of classifier output susceptibility |
| CN109543542A (en) * | 2018-10-24 | 2019-03-29 | 杭州叙简科技股份有限公司 | A kind of determination method whether particular place personnel dressing standardizes |
-
2019
- 2019-06-21 CN CN201910543624.0A patent/CN110427808A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103745226A (en) * | 2013-12-31 | 2014-04-23 | 国家电网公司 | Dressing safety detection method for worker on working site of electric power facility |
| CN104063722A (en) * | 2014-07-15 | 2014-09-24 | 国家电网公司 | Safety helmet identification method integrating HOG human body target detection and SVM classifier |
| CN105069466A (en) * | 2015-07-24 | 2015-11-18 | 成都市高博汇科信息科技有限公司 | Pedestrian clothing color identification method based on digital image processing |
| CN105488490A (en) * | 2015-12-23 | 2016-04-13 | 天津天地伟业数码科技有限公司 | Judge dressing detection method based on video |
| CN106599781A (en) * | 2016-11-08 | 2017-04-26 | 国网山东省电力公司威海供电公司 | Electric power business hall dressing normalization identification method based on color and Hu moment matching |
| CN107909580A (en) * | 2017-11-01 | 2018-04-13 | 深圳市深网视界科技有限公司 | A kind of pedestrian wears color identification method, electronic equipment and storage medium clothes |
| CN108052900A (en) * | 2017-12-12 | 2018-05-18 | 成都睿码科技有限责任公司 | A kind of method by monitor video automatic decision dressing specification |
| CN108319934A (en) * | 2018-03-20 | 2018-07-24 | 武汉倍特威视系统有限公司 | Safety cap wear condition detection method based on video stream data |
| CN108460358A (en) * | 2018-03-20 | 2018-08-28 | 武汉倍特威视系统有限公司 | Safety cap recognition methods based on video stream data |
| CN109101922A (en) * | 2018-08-10 | 2018-12-28 | 广东电网有限责任公司 | Operating personnel device, assay, device and electronic equipment |
| CN109214467A (en) * | 2018-10-17 | 2019-01-15 | 广东电网有限责任公司 | Consider power transformation operation personnel's dressing Robust identifying method of classifier output susceptibility |
| CN109543542A (en) * | 2018-10-24 | 2019-03-29 | 杭州叙简科技股份有限公司 | A kind of determination method whether particular place personnel dressing standardizes |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112949367A (en) * | 2020-07-07 | 2021-06-11 | 南方电网数字电网研究院有限公司 | Method and device for detecting color of work clothes based on video stream data |
| CN113067845A (en) * | 2020-12-06 | 2021-07-02 | 泰州市朗嘉馨网络科技有限公司 | On-duty detection platform applying numerical analysis |
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Application publication date: 20191108 |