CN104392630A - Throw-out intelligent detection device and method - Google Patents
Throw-out intelligent detection device and method Download PDFInfo
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- CN104392630A CN104392630A CN201410688800.7A CN201410688800A CN104392630A CN 104392630 A CN104392630 A CN 104392630A CN 201410688800 A CN201410688800 A CN 201410688800A CN 104392630 A CN104392630 A CN 104392630A
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Abstract
Disclosed is a throw-out intelligent detection device and method. A throw-out intelligent detection device and method comprises an intelligent detection module, a display module, and a warning module. The intelligent detection module monitors and collects traffic conditions of tunnels and roads in real time, and transmits the traffic conditions to the display module, meanwhile, an internally embedded intelligent chip processor processes and judges a video image signal information through a background modeling step, a foreground detection step, a protected zone setting step, a foreground matching and updating step, and a throw-out judging step; if the throw-out exists, the display module displays the information of the throw-out in real time and sends a warning signal to the warning module, so as to remind the monitoring personnel to deal with the throw-out, thereby avoiding an accident. The throw-out intelligent detection device and method is not only able to intelligently detect the information of the throw-out, but the detection method is also able to avoid underreporting and false alarm at a certain degree, thereby providing an effective and executable solution for ensuring the traffic safety and the traffic order.
Description
Technical field
The invention belongs to intelligent video analysis monitoring field, relate to the technology such as image procossing, video analysis, pattern-recognition, intelligent monitoring, artificial intelligence.
Background technology
Along with China's expanding economy, traffic transport industry is day by day flourishing, and this makes traffic problems increasingly serious, and frequent accidents occurs, and causes the deepest concern of the country and people.Especially on tunnel, highway, vehicle flowrate is large, the speed of a motor vehicle is very fast, sometimes has object and to drop from vehicle or the vehicle that breaks down cannot process movement in time, and then cause a traffic accident.Shed formal matter part and become a traffic events taken place frequently, not only the vehicle of an accident impact is many, also second accident can be caused, the security of the lives and property of serious harm people, cause unpredictable loss sometimes, the traffic hazard caused thus and the potential safety hazard caused become problem in urgent need to solve.Therefore, shedding thing and reporting to the police on tunnel, highway how to be detected rapidly and accurately, find potential safety hazard as early as possible and get rid of in time, keep the safe and smooth of tunnel, highway etc. to become the important problem of traffic safety-security area.Thing intelligent detection device is shed in highway, tunnel can whole day free of discontinuities work in 24 hours, and the safety of moment supervision tunnel highway, protection people life property safety, has huge social benefit.At present, the development of thing Intelligent Measurement field is shed by China in highway, tunnel also immature, checkout equipment and technology a lot of defect in addition, as poor real, sheds thing and reports by mistake, fails to report, poor etc. to environmental suitability.
Summary of the invention
For solving the problem, the object of the present invention is to provide and shed thing intelligent detection device and method.This device processing speed is fast, real-time good, and to reporting by mistake and failing to report, phenomenon controls well, accuracy of detection is high, have good adaptability to the emergency case in environment.
The technical solution used in the present invention is:
This sheds thing intelligent detection device and method comprises Intelligent Measurement module, display module and alarm module.
Described Intelligent Measurement module mainly comprises color camera, protective device, infrared illumination lamp and DSP process chip.Wherein, what color camera collected is color video frequency image, and color camera to be connected with DSP process chip by netting twine and to transmit data.Color camera is by image transmitting to DSP process chip, and DSP process chip mainly algorithm unit, provides and shed thing Intelligent Measurement scheme, and color camera and DSP process chip are encapsulated in shell.The cylindrical, hollow encapsulating shell that shell is made up of Stainless steel 316 L; enclosure front end is provided with clear glass; clear glass is for the protection of color camera and DSP process chip; color camera is arranged on the side near front end clear glass; DSP process chip is arranged on the side away from front end clear glass, and color camera can carry out collection surrounding situation map picture through front glass simultaneously.Outer casing back has two wiring holes, a hole is used for connecting power line, power to color camera and DSP process chip, another one hole is used for connecting fiber cable, and the alerting signal for the video signal of color camera collection and the process of DSP process chip being obtained is transferred to hundred meters or the outer Control Room of km.Protective device is rain shade, is curved thin plate shape, is arranged on the shell of Intelligent Measurement module, can rain cover, the extension fixture time limit in serviceable life.Infrared illumination lamp provides night illumination, and detection range is 150 meters, guarantees when without background light source, and color camera normally can carry out image acquisition work.Infrared illumination lamp is encapsulated in cylindrical stainless steel protection shell, and immediately below the shell of Intelligent Measurement module, two shells are rigidly connected, and stainless steel protection shell afterbody perforate connecting power line is powered to infrared lamp.
Described display module is display screen, is arranged in Control Room, receives the video information also display in real time that color camera transmission comes.What reception DSP process chip process simultaneously obtained sheds thing information and shows.
Described alarm module is alarm, obtains shedding thing alerting signal for receiving the process of DSP process chip, and prompting monitor staff process the thing of shedding on tunnel, highway in time.
Utilize and above-mentionedly shed thing intelligent detection device and method monitoring step is:
(1) color image information of color camera collection, be transferred to display module and DSP process chip simultaneously, display module shows tunnel, highway live state information in real time, and DSP process chip receives the further Intelligent Recognition process of color video frequency image information that color camera transmission comes.
(2) the color video frequency image information received is carried out background modeling by DSP process chip, foreground detection, the setting of protection zone, prospect coupling upgrade, shed thing and judge treatment scheme, obtains shedding thing information.
(3) result is transferred to alarm module by DSP process chip, will shed thing information transmission to display module simultaneously, and demonstrate and shed thing information, and prompting monitor staff be for further processing.
This device adopt shed thing intelligent detecting method mainly comprise background modeling, foreground detection, protection zone setting, prospect coupling upgrade, shed thing judge.
Described background modeling mainly carries out pattern-recognition, Intelligent Establishment adaptive learning background model according to the color video frequency image of video acquisition module input.Utilize the lightness of video image, chrominance information sets up background model.Because algorithm carries out execution computing in embedded device, the data message that algorithm adopts is all integer parameter.Pixel in traversing graph picture successively, finds its eight neighborhood pixel to each pixel, and set up Gauss model according to Seed Points and eight neighborhood information, Gauss model parameter has lightness, colourity, saturation degree, weight, covariance information.Gauss model is set up to each Seed Points.
Lightness, the colourity of model are obtained by Seed Points and its eight neighborhood relevant information.As matrix
shown in position, middle 1 is Seed Points Pixel Information, and eight neighborhood represents with 0.To eight neighborhood pixel information according to from left to right, order is from top to bottom labeled as P successively
1, P
2, P
3, P
4, P
5, P
6, P
7, P
8, Seed Points is denoted as P
0.According to weight parameter, Gauss model is set up to Seed Points,
Wherein,
for setting up the lightness after Gauss model,
,
,
,
,
,
,
,
,
be respectively the lightness of Seed Points and its eight neighborhood.
In like manner, same method establishment Seed Points colourity and the Gauss model of saturation degree,
Wherein,
for setting up the colourity after Gauss model,
,
,
,
,
,
,
,
,
be respectively the colourity of Seed Points and its eight neighborhood.
Wherein,
for setting up the saturation degree after Gauss model,
,
,
,
,
,
,
,
,
be respectively the saturation degree of Seed Points and its eight neighborhood.
Model variance learning process is:
Wherein,
represent a new two field picture variance learning outcome,
represent the variance of current background,
represent model variance Studying factors,
,
,
represent the lightness of the Gauss model at background image Seed Points place, colourity, saturation infromation respectively.
,
,
represent the lightness of the Gauss model at current frame image and Seed Points place, background image corresponding position, colourity, saturation infromation respectively.
Model Weight record be the modeling of background Seed Points success number.When background Seed Points modeling sum reaches 1/3 of whole Seed Points quantity, background modeling success.
Described foreground detection is and detects emerging people or thing in background.The foreground detection method that the present invention adopts is the method for prospect compared with the Gauss model of background.In like manner set up the Gauss model parameter lightness of current frame image pixel Seed Points, colourity, saturation degree, weight, covariance information.Respectively corresponding with the Gauss model of background for prospect lightness, colourity, saturation degree, that variance parameter carries out respectively is poor.If difference is less than certain threshold value, so Seed Points is doubtful foreground point.Otherwise be background dot.After all Seed Points in foreground point have been contrasted, UNICOM's expansion process is carried out to Seed Points, like this, each Seed Points of same foreground object is by UNICOM, calculate the size in each UNICOM region, girth, area, center of gravity, depth-width ratio information, exclude the impact of too small false prospect noise spot, then respectively different sequence numbers is labeled as to the mask of different prospect.By the effective foreground data in the first two field picture after Background learning stored in prospect history information library, so that the prospect coupling in subsequent detection process upgrades and sheds the operations such as thing judgement.
Described protection zone be set as on tunnel or highway, vehicle travel region.By drawing two lines to indicate protection zone information along tunnel or highway edge in the picture.And setting is simultaneously shed thing warning sensitivity, is shed the long-pending monitoring restriction of object plane, depth-width ratio restriction, prevents the impact of too small stone, fruit stone etc.
Described prospect coupling renewal process mainly refers to be gone coupling with the foreground information newly detected, upgrades prospect history information library.By detecting the emerging foreground information of current frame image, according to prospect size, girth, area, center of gravity, depth-width ratio information, prospect historical data is compared, if change is less than threshold value, then think and belong to same foreground information, and upgrade prospect historical data, if do not find the historical information of coupling, be then emerging prospect, relevant new prospect is saved in historical data.
Described formal matter part of shedding judges mainly to judge whether whether whether prospect meet the demands in protected location and warning sensitivity for shedding thing and shedding thing.Deterministic process is traversal prospect history information library, judges whether the area of prospect, depth-width ratio meet threshold value setting, if met, then for shedding thing.Judge whether, in the protection zone of setting, if in protection zone, to judge whether warning sensitivity meets the demands according to prospect center of gravity information further; if meet warning sensitivity; then for shedding thing, send warning message simultaneously, and foreground information is marked out be presented on screen.
The invention has the beneficial effects as follows: this device can free of discontinuities work in 24 hours; simple and flexible; be applicable to on-the-spot changeable factor; effectively can identify and shed thing in vcehicular tunnel; and and alarm; avoid the accident of getting into an accident, protection personal safety as well as the property safety, contributes to safeguarding traffic safety and order.Shed thing intelligent detection device to be simple and easy to install, easy to operate.Shed thing Intelligent Measurement algorithm prospect, background intelligent study and update strategy, strong adaptability, has higher degree of intelligence.
Accompanying drawing explanation
Accompanying drawing is used to provide a further understanding of the present invention, and forms a part for instructions, is used from explanation the present invention, is not construed as limiting the invention with example one of the present invention.In the accompanying drawings:
Fig. 1 is apparatus of the present invention schematic diagram.
Fig. 2 is that the present invention sheds quality testing method of determining and calculating process flow diagram.
Fig. 3 is that the present invention sheds thing alarm condition key diagram.
Embodiment
Below in conjunction with instantiation, each detailed problem involved by technical solution of the present invention is described.Be to be noted that described example is only intended to be convenient to the understanding of the present invention, therefore do not limit protection scope of the present invention.
Be illustrated in figure 1 this and shed thing intelligent detection device figure, this device comprises Intelligent Measurement module 9, display module 7 and alarm module 8.
Described Intelligent Measurement module 9 mainly comprises color camera 2, protective device 1, infrared illumination lamp 6 and DSP process chip 4.Wherein, what color camera 2 collected is color video frequency image, and color camera 2 to be connected with DSP process chip 4 by netting twine and to transmit data.Image transmitting to DSP process chip 4, DSP process chip 4 mainly algorithm unit, provides and sheds thing Intelligent Measurement scheme by color camera 2, and color camera 2 and DSP process chip 4 are encapsulated in shell 3.The cylindrical, hollow encapsulating shell that shell 3 is made up of Stainless steel 316 L; shell 3 interior forward end is provided with clear glass; clear glass is for the protection of color camera 2 and DSP process chip 4; color camera 2 is arranged on the side near front end clear glass; DSP process chip 4 is arranged on the side away from front end clear glass, and color camera 2 can carry out collection surrounding situation map picture through front glass simultaneously.Shell 3 rear end has two wiring holes, a hole is used for connecting power line, power to color camera 2 and DSP process chip 4, another one hole is used for connecting fiber cable, processes the alerting signal obtained be transferred to Control Room outside hundred meters or km for the video signal that gathered by color camera 2 and DSP process chip 4.Protective device 1 is rain shade, is curved thin plate shape, is arranged on the shell 3 of Intelligent Measurement module, can rain cover, the extension fixture time limit in serviceable life.Infrared illumination lamp 6 provides night illumination, and detection range is 150 meters, guarantees when without background light source, and color camera 2 normally can carry out image acquisition work.Infrared illumination lamp 6 is encapsulated in cylindrical stainless steel protection shell 5, and immediately below the shell 3 of Intelligent Measurement module 9, two shells 5,3 are rigidly connected, and stainless steel protection shell 5 afterbody perforate connecting power line is powered to infrared lamp.
Described display module is display screen 7, is arranged in Control Room, receives color camera 2 and transmits the video information also display in real time come.What reception DSP process chip 4 process simultaneously obtained sheds thing information and shows.
Described alarm module is alarm 8, for receive DSP process chip 4 process obtain shed thing alerting signal, prompting monitor staff in time the thing of shedding on tunnel, highway is processed.
Utilize and above-mentionedly shed thing intelligent detection device and method monitoring step is:
(4) color image information of color camera 2 collection, be transferred to display module 7 and DSP process chip 4 simultaneously, display module 7 shows tunnel, highway live state information in real time, and DSP process chip 4 receives the further Intelligent Recognition process of color video frequency image information that color camera transmission comes.
(5) the color video frequency image information received is carried out background modeling by DSP process chip 4, foreground detection, the setting of protection zone, prospect coupling upgrade, shed thing and judge treatment scheme, obtains shedding thing information.
(6) result is transferred to alarm module 8 by DSP process chip 4, will shed thing information transmission to display module 7 simultaneously, and demonstrate and shed thing information, and prompting monitor staff be for further processing.
Be illustrated in figure 2 this and shed thing Intelligent Measurement process flow diagram, employing shed thing intelligent detecting method mainly comprise background modeling, foreground detection, protection zone setting, prospect coupling upgrade, shed thing judge.
The color video frequency image that described background modeling mainly inputs according to color camera 2 carries out pattern-recognition, Intelligent Establishment adaptive learning background model.Utilize the lightness of video image, chrominance information sets up background model.Because algorithm carries out execution computing in embedded device, the data message that algorithm adopts is all integer parameter.Pixel in traversing graph picture successively, finds its eight neighborhood pixel to each pixel, and set up Gauss model according to Seed Points and eight neighborhood information, Gauss model parameter has lightness, colourity, saturation degree, weight, covariance information.Gauss model is set up to each Seed Points.
Lightness, the colourity of model are obtained by Seed Points and its eight neighborhood relevant information.As matrix
shown in position, middle 1 is Seed Points Pixel Information, and eight neighborhood represents with 0.To eight neighborhood pixel information according to from left to right, order is from top to bottom labeled as P successively
1, P
2, P
3, P
4, P
5, P
6, P
7, P
8, Seed Points is denoted as P
0.According to weight parameter, Gauss model is set up to Seed Points,
Wherein,
for setting up the lightness after Gauss model,
,
,
,
,
,
,
,
,
be respectively the lightness of Seed Points and its eight neighborhood.
In like manner, same method establishment Seed Points colourity and the Gauss model of saturation degree,
Wherein,
for setting up the colourity after Gauss model,
,
,
,
,
,
,
,
,
be respectively the colourity of Seed Points and its eight neighborhood.
Wherein,
for setting up the saturation degree after Gauss model,
,
,
,
,
,
,
,
,
be respectively the saturation degree of Seed Points and its eight neighborhood.
Model variance learning process is:
Wherein,
represent a new two field picture variance learning outcome,
represent the variance of current background,
represent model variance Studying factors,
,
,
represent the lightness of the Gauss model at background image Seed Points place, colourity, saturation infromation respectively.
,
,
represent the lightness of the Gauss model at current frame image and Seed Points place, background image corresponding position, colourity, saturation infromation respectively.
Model Weight record be the modeling of background Seed Points success number.When background Seed Points modeling sum reaches 1/3 of whole Seed Points quantity, background modeling success.
Described foreground detection is and detects emerging people or thing in background.The foreground detection method that the present invention adopts is the method for prospect compared with the Gauss model of background.In like manner set up the Gauss model parameter lightness of current frame image pixel Seed Points, colourity, saturation degree, weight, covariance information.Respectively corresponding with the Gauss model of background for prospect lightness, colourity, saturation degree, that variance parameter carries out respectively is poor.If difference is less than certain threshold value, so Seed Points is doubtful foreground point.Otherwise be background dot.After all Seed Points in foreground point have been contrasted, UNICOM's expansion process is carried out to Seed Points, like this, each Seed Points of same foreground object is by UNICOM, calculate the size in each UNICOM region, girth, area, center of gravity, depth-width ratio information, exclude the impact of too small false prospect noise spot, then respectively different sequence numbers is labeled as to the mask of different prospect.By the effective foreground data in the first two field picture after Background learning stored in prospect history information library, so that the prospect coupling in subsequent detection process upgrades and sheds the operations such as thing judgement.
Described protection zone be set as on tunnel or highway, vehicle travel region.By drawing two lines to indicate protection zone information along tunnel or highway edge in the picture.And setting is simultaneously shed thing warning sensitivity, is shed the long-pending monitoring restriction of object plane, depth-width ratio restriction, prevents the impact of too small stone, fruit stone etc.
The foreground information that described prospect coupling renewal process mainly refers to newly detecting removes renewal prospect history information library.By detecting the emerging foreground information of current frame image, according to prospect size, girth, area, center of gravity, depth-width ratio information, prospect historical data is compared, if change is less than threshold value, then think and belong to same foreground information, and upgrade prospect historical data, if do not find the historical information of coupling, be then emerging prospect, relevant new prospect is saved in historical data.
Described formal matter part of shedding judges mainly to judge whether whether whether prospect meet the demands in protected location and warning sensitivity for shedding thing and shedding thing.Deterministic process is traversal prospect history information library, judge the area of prospect, depth-width ratio information whether meet threshold value setting, if meet, then for shedding thing.Judge whether, in the protection zone of setting, if in protection zone, to judge whether warning sensitivity meets the demands according to prospect center of gravity information further; if meet warning sensitivity; then for shedding thing, send warning message simultaneously, and foreground information is marked out be presented on screen.
Be illustrated in figure 3 this and shed thing Intelligent Measurement alarm condition figure.As shown in Figure 3, oblique line information in the left and right sides is highway or direction, tunnel marginal information.The far and near scope in monitor area position up and down for limiting, forms closed region A.Closed region A is protection zone, only has when thing information is shed in closed region, just can report to the police.As shed thing 11 in the A of protection zone, can report to the police in testing process; Shed thing 10 in the B of non-protected area, can not report to the police in testing process.
Any those skilled in the art may utilize the technology contents of above-mentioned announcement to be changed or be modified as the Equivalent embodiments of equivalent variations.But everyly do not depart from technical solution of the present invention content, any simple modification, equivalent variations and the remodeling done above embodiment according to technical spirit of the present invention, still belong to the protection domain of technical solution of the present invention.
Claims (7)
1. shed thing intelligent detection device and method, it is characterized in that: described in shed thing intelligent detection device and comprise Intelligent Measurement module, display module and alarm module.
2. apparatus and method according to claim 1; it is characterized in that: the Intelligent Measurement module of shedding described in thing intelligent detection device and method mainly comprises color camera, protective device, infrared illumination lamp and DSP process chip; wherein; what color camera collected is color video frequency image; color camera to be connected with DSP process chip by netting twine and to transmit data; color camera by image transmitting to DSP process chip; DSP process chip mainly algorithm unit, provides and sheds thing Intelligent Measurement scheme.
3. apparatus and method according to claim 1, it is characterized in that: shed color camera described in thing intelligent detection device and method and DSP process chip is encapsulated in shell, the cylindrical, hollow encapsulating shell that shell is made up of Stainless steel 316 L, enclosure front end is provided with clear glass, clear glass is for the protection of color camera and DSP process chip, color camera is arranged on the side near front end clear glass, DSP process chip is arranged on the side away from front end clear glass, and color camera can carry out collection surrounding situation map picture through front glass simultaneously; Outer casing back has two wiring holes, a hole is used for connecting power line, power to color camera and DSP process chip, another one hole is used for connecting fiber cable, and the alerting signal for the video signal of color camera collection and the process of DSP process chip being obtained is transferred to hundred meters or the outer Control Room of km.
4. apparatus and method according to claim 1, is characterized in that: described in shed thing intelligent detection device and method step is:
The color image information that color camera gathers, be transferred to display module and DSP process chip simultaneously, display module shows tunnel, highway live state information in real time, and DSP process chip receives the further Intelligent Recognition process of color video frequency image information that color camera transmission comes;
The color video frequency image information received is carried out background modeling by DSP process chip, foreground detection, the setting of protection zone, prospect coupling upgrade, shed thing and judge treatment scheme, obtains shedding thing information;
Result is transferred to alarm module by DSP process chip, will shed thing information transmission to display module simultaneously, and demonstrate and shed thing information, and prompting monitor staff be for further processing.
5. apparatus and method according to claim 1, it is characterized in that: described in shed the color video frequency image that background modeling described in thing intelligent detection device and method mainly inputs according to color camera and carry out pattern-recognition, Intelligent Establishment adaptive learning background model, utilizes the lightness of video image, chrominance information sets up background model; Pixel in traversing graph picture successively, finds its eight neighborhood pixel to each pixel, and set up Gauss model according to Seed Points and eight neighborhood information, Gauss model parameter has lightness, colourity, saturation degree, weight, covariance information; Gauss model is set up to each Seed Points:
Lightness, the colourity of model are obtained, as matrix by Seed Points and its eight neighborhood relevant information
shown in position, middle 1 is Seed Points Pixel Information, and eight neighborhood represents with 0, and to eight neighborhood pixel information according to from left to right, order is from top to bottom labeled as P successively
1, P
2, P
3, P
4, P
5, P
6, P
7, P
8, Seed Points is denoted as P
0, according to weight parameter, Gauss model is set up to Seed Points,
Wherein,
for setting up the lightness after Gauss model,
,
,
,
,
,
,
,
,
be respectively the lightness of Seed Points and its eight neighborhood;
In like manner, same method establishment Seed Points colourity and the Gauss model of saturation degree,
Wherein,
for setting up the colourity after Gauss model,
,
,
,
,
,
,
,
,
be respectively the colourity of Seed Points and its eight neighborhood;
Wherein,
for setting up the saturation degree after Gauss model,
,
,
,
,
,
,
,
,
be respectively the saturation degree of Seed Points and its eight neighborhood;
Model variance learning process is:
Wherein,
represent a new two field picture variance learning outcome,
represent the variance of current background,
represent model variance Studying factors,
,
represent the lightness of the Gauss model at background image Seed Points place, colourity, saturation infromation respectively;
,
,
represent the lightness of the Gauss model at current frame image and Seed Points place, background image corresponding position, colourity, saturation infromation respectively.
6. apparatus and method according to claim 1, is characterized in that: described in the foreground detection of shedding described in thing intelligent detection device and method be and detect emerging people or thing in background; The method of employing prospect compared with the Gauss model of background, in like manner set up the Gauss model parameter lightness of current frame image pixel Seed Points, colourity, saturation degree, weight, covariance information, respectively corresponding with the Gauss model of background for prospect lightness, colourity, saturation degree, that variance parameter carries out respectively is poor, if difference is less than certain threshold value, so Seed Points is doubtful foreground point, otherwise is background dot; After all Seed Points in foreground point have been contrasted, UNICOM's expansion process is carried out to Seed Points, like this, each Seed Points of same foreground object is by UNICOM, calculate the size in each UNICOM region, girth, area, center of gravity, depth-width ratio information, exclude the impact of too small false prospect noise spot, then respectively different sequence numbers is labeled as to the mask of different prospect.
7. apparatus and method according to claim 1; it is characterized in that: described in shed protection zone described in thing intelligent detection device and method be set as on tunnel or highway; the region that vehicle travels; by drawing two lines to indicate protection zone information along tunnel or highway edge in the picture; and setting is simultaneously shed thing warning sensitivity, is shed the long-pending monitoring restriction of object plane, depth-width ratio restriction, prevents the impact of too small stone, fruit stone etc.
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| CN201410688800.7A CN104392630A (en) | 2014-11-26 | 2014-11-26 | Throw-out intelligent detection device and method |
| CN201510595135.1A CN105245831B (en) | 2014-11-26 | 2015-09-18 | Shed object intelligent detection device |
| CN201510598595.XA CN105187800B (en) | 2014-11-26 | 2015-09-18 | Detector with high definition modular structure |
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| CN201510595135.1A Active CN105245831B (en) | 2014-11-26 | 2015-09-18 | Shed object intelligent detection device |
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Also Published As
| Publication number | Publication date |
|---|---|
| CN105187800A (en) | 2015-12-23 |
| CN105245831B (en) | 2019-10-08 |
| CN105187800B (en) | 2019-01-08 |
| CN105245831A (en) | 2016-01-13 |
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