CN205211167U - Vehicle model recognition system based on infrared CCD and pressure sensor - Google Patents
Vehicle model recognition system based on infrared CCD and pressure sensor Download PDFInfo
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- CN205211167U CN205211167U CN201521068234.6U CN201521068234U CN205211167U CN 205211167 U CN205211167 U CN 205211167U CN 201521068234 U CN201521068234 U CN 201521068234U CN 205211167 U CN205211167 U CN 205211167U
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Abstract
The utility model discloses a vehicle model recognition system based on infrared CCD and pressure sensor, including setting up the camera on bridge tunnel entry, buried ground pressure sensor underground under the road surface in the camera ken center the place ahead on the bridge tunnel entry 5, processing unit is all connected to ground pressure sensor and camera, and processing unit includes the treater, treater connection camera and ground pressure sensor, the treater still is connected with image recognition system, wheel base computational system, database, sensor identification system and data input output interface. The utility model discloses combine camera and ground pressure sensor to being calculated by the treater and obtaining the vehicle number of axles, wheel base and front and top profile characteristic, compare with database rules data, the accuracy recognises the motorcycle type information of bridge tunnel entry traffick, the utility model discloses a two kinds of identification method corecognition have improved the discrimination to this device is laid simply, and easy to carry out guarantees continuously going on of all -weather vehicle model recognition work.
Description
[technical field]
The utility model relates to the round-the-clock monitoring recognition methods of a kind of vehicle, is specifically related to a kind of model recognition system based on infrared CCD and pressure transducer.
[background technology]
Along with the development of intelligent transportation, vehicle cab recognition is embarked on journey the focus studied in the industry, and this is also the precondition of many subsequent treatment, such as the safe early warning of bridge tunnel entrance, the automatic detection etc. of traffic toll gate.It has larger reference value compared with single information of vehicle flowrate.The vehicle identified generally comprises passenger vehicle, car, lorry, offroad vehicle and minibus etc.
The model recognizing method that current industry adopts usually mainly contains ocular estimate, inductive coil method, infrared detecting method, ultrasonic Detection Method and pattern-recognition method etc.Ocular estimate needs at substantial manpower, financial resources and time; Inductive coil method affects very large by the speed of a motor vehicle etc., reliability is lower; The hardware system more complicated of Infrared Detection Method and ultrasonic Detection Method, and the requirement of system to environment is higher, failure rate is also higher, and maintenance is inconvenient, so be difficult to promote in the application of reality; The vehicle information of pattern-recognition method identification is single, and can not reflect vehicle parameter, set expandability is poor comprehensively.
[utility model content]
The purpose of this utility model is to overcome above-mentioned deficiency, a kind of model recognition system based on infrared CCD and pressure transducer is provided, can combining image disposal system and ground-pressure pick-up system, detect and travel vehicle characteristics, for bridge tunnel provides current vehicle cab recognition reliably.In addition, the model recognition system extendability of application ARM is strong, is convenient to direct implantation and the application of other program.
In order to achieve the above object, the utility model comprises the ccd video camera be arranged on bridge tunnel entrance, ground-pressure pick-up is embedded with under the road surface in front, camera field center, ground-pressure pick-up and the equal connection handling unit of video camera, processing unit comprises processor, processor connects video camera and ground-pressure pick-up, and processor is also connected with image identification system, wheelbase computing system, database, sensor recognition system and data input/output interface.
Described video camera adopts infrared CCD video camera.
Described video camera is arranged on bridge tunnel entrance center upper portion.
Described processor adopts the S3CZ410 processor of ARM11 core.
Described image identification system adopts C328 high integration cmos image acquisition module, accepts and export order with serial line interface.
Described processor is connected with reservoir.
Compared with prior art, the utility model by two serial-grams of video camera and ground-pressure pick-up collection vehicle and pressure transducer pressurized number of times and and the pressurized moment, and then obtain vehicle frontal and top contour feature and the number of axle and wheelbase, compared with database regulation data, accurately identify the vehicle information of bridge tunnel entrance traffick, the utility model identifies by two kinds of recognition methodss are collaborative, improve recognition accuracy, and this device is laid simple, easy to implement, ensure round-the-clock vehicle cab recognition work continue carry out.
Further, the utility model adopts infrared CCD video camera, can round-the-clockly monitor road conditions.
Further, video camera of the present utility model is arranged on centre position directly over bridge tunnel entrance, ensures that pictures taken is comprehensively accurate.
Further, the utility model is connected with reservoir, can store vehicular traffic information.
[accompanying drawing explanation]
Fig. 1 is structural representation of the present utility model;
Fig. 2 is control block diagram of the present utility model.
[embodiment]
Below in conjunction with accompanying drawing, the utility model is described further.
See Fig. 1 and Fig. 2, the utility model comprises the video camera 1 be arranged on bridge tunnel entrance 5, video camera 1 is arranged on bridge tunnel entrance 5 center upper portion, the road surface in the front, camera field center on bridge tunnel entrance 5 is embedded with ground-pressure pick-up 43 times, ground-pressure pick-up 4 and video camera 1 all connection handling unit, processing unit comprises processor, processor connects video camera 1 and ground-pressure pick-up 4, processor is also connected with image identification system, wheelbase computing system, database, sensor recognition system and data input/output interface, processor adopts the S3CZ410 processor of ARM11 core, image identification system adopts C328 high integration cmos image acquisition module, accept with serial line interface and export order, processor is connected with reservoir.
Preferably, video camera 1 adopts infrared CCD video camera, ensures the vehicle cab recognition in night and greasy weather.
Recognition methods of the present utility model, comprises the following steps:
Step one, when vehicle 2 front-wheel rolls ground-pressure pick-up 4, triggering ground-pressure pick-up 4 and video camera 1 work simultaneously, can obtain the pressurized number of times of ground-pressure pick-up 4, pressurized moment and continuous print two vehicle pictures;
Step 2, by the information transmission of acquisition in step one to processing unit;
Step 3, processing unit obtains vehicle 2 front and top contour feature and the speed of a motor vehicle according to the picture that video camera 1 is taken, by the length of vehicle ' s contour feature calculation vehicle, width and height; Processing unit calculates obtain the number of axle, wheelbase according to the pressurized number of times of the speed of a motor vehicle and ground-pressure pick-up 4, pressurized moment;
Step 4, according to the number of axle of the vehicle 2 calculated, wheelbase and vehicle ' s contour size, contrasts with database data and judges vehicle;
Step 5, processing unit generates vehicle information, completes identification; Vehicle information storage is uploaded to relevant departments.
In step, when vehicle 2 i-th axles are by ground-pressure pick-up 4, the stressed Flexible element of pressure transducer 4 produces distortion, be pasted onto the quick strain bridge output voltage signal of power on Flexible element, wherein, foil gauge resistance value relative variation is heavily directly proportional to axle, by amplifier by voltage amplification, become corresponding digital quantity by digital-to-analog conversion again, then can calculate each axle weight of vehicle.
In step 3, two pictures of vehicle 2 taken by video camera 1, can obtain the speed of a motor vehicle by image procossing; The vehicle dimension that this external system calculates two pictures is respectively verified mutually; And the steps such as the model recognition system applying ARM can directly implant number-plate number recognizer, is positioned, splits by image, image binaryzation, Characteristic Extraction obtain the number-plate number.
The rtp stack that the transmission of data and image adopts the JRPTPLIB function library of open source code to provide realizes.The result that compression coding is good is encapsulated in RTP bag by transmitting terminal, adds receiving end destination address, then data and image subpackage is sent to receiving end address, by embedded web server, information of vehicles is passed to relevant departments.
Claims (6)
1. the model recognition system based on infrared CCD and pressure transducer, it is characterized in that, comprise the video camera (1) be arranged on bridge tunnel entrance (5), the road surface (3) in video camera (1) sighting center front is embedded with ground-pressure pick-up (4), ground-pressure pick-up (4) and video camera (1) all connection handling unit, processing unit comprises processor, processor connects video camera (1) and ground-pressure pick-up (4), processor is also connected with image identification system, wheelbase computing system, database, sensor recognition system and data input/output interface parts.
2. a kind of model recognition system based on infrared CCD and pressure transducer according to claim 1, it is characterized in that, described video camera (1) adopts infrared CCD video camera.
3. a kind of model recognition system based on infrared CCD and pressure transducer according to claim 1, it is characterized in that, described video camera (1) is arranged on bridge tunnel entrance (5) center upper portion.
4. a kind of model recognition system based on infrared CCD and pressure transducer according to claim 1, it is characterized in that, described processor adopts the S3CZ410 processor of ARM11 core.
5. a kind of model recognition system based on infrared CCD and pressure transducer according to claim 1, is characterized in that, described image identification system adopts C328 high integration cmos image acquisition module, accepts and export order with serial line interface.
6. a kind of model recognition system based on infrared CCD and pressure transducer according to claim 1, it is characterized in that, described processor is connected with reservoir.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201521068234.6U CN205211167U (en) | 2015-12-19 | 2015-12-19 | Vehicle model recognition system based on infrared CCD and pressure sensor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201521068234.6U CN205211167U (en) | 2015-12-19 | 2015-12-19 | Vehicle model recognition system based on infrared CCD and pressure sensor |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN205211167U true CN205211167U (en) | 2016-05-04 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN201521068234.6U Expired - Fee Related CN205211167U (en) | 2015-12-19 | 2015-12-19 | Vehicle model recognition system based on infrared CCD and pressure sensor |
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| CN (1) | CN205211167U (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109389828A (en) * | 2018-10-19 | 2019-02-26 | 深圳市朋辉科技术有限公司 | A kind of monitoring system of road vehicle driving information |
| CN110807936A (en) * | 2019-11-13 | 2020-02-18 | 佛山科学技术学院 | Statistical system for identifying vehicle model and measuring and calculating speed |
-
2015
- 2015-12-19 CN CN201521068234.6U patent/CN205211167U/en not_active Expired - Fee Related
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109389828A (en) * | 2018-10-19 | 2019-02-26 | 深圳市朋辉科技术有限公司 | A kind of monitoring system of road vehicle driving information |
| CN110807936A (en) * | 2019-11-13 | 2020-02-18 | 佛山科学技术学院 | Statistical system for identifying vehicle model and measuring and calculating speed |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 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: 20160504 Termination date: 20161219 |