CN101692313A - Portable vehicle recognition device base on embedded platform - Google Patents
Portable vehicle recognition device base on embedded platform Download PDFInfo
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- CN101692313A CN101692313A CN200910054373A CN200910054373A CN101692313A CN 101692313 A CN101692313 A CN 101692313A CN 200910054373 A CN200910054373 A CN 200910054373A CN 200910054373 A CN200910054373 A CN 200910054373A CN 101692313 A CN101692313 A CN 101692313A
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Abstract
The invention discloses a portable vehicle recognition device base on an embedded platform, belonging to the technical field of traffic and vehicle management. A camera, a display or a touch screen, a wireless transmission (GPRS) module, a radio frequency identification card (RFID) reader, a global positioning (GPS) module are arranged on the embedded platform to form a portable device which integrates set data acquisition, data display, data processing, self location, data transmission and communication function as a whole, so that the recognition of licence plate images comprising five key links, such as image acquisition, image preprocessing, licence plate location, character segmentation and character recognition is realized, and the image acquisition and processing are directly completed in the portable device. The device has the advantages of convenient carrying, rapid location, high flexibility, high efficiency, high accuracy, high reliability, low cost and high quality, and is recommended to be used in the field of traffic and vehicle management.
Description
Technical field
The present invention relates to a kind of portable vehicle recognition device, belong to the technical field of traffic and vehicle management based on embedded platform.
Background technology
Current, the vehicle management system of discerning based on car plate is widely used in traffic department, parking lot.Its ultimate principle is: the image that contains car plate that camera photographs is imported PC or embedded digital signal Processing (EDSP) system by video frequency collection card, finish Flame Image Process and Recognition of License Plate Characters by PC or embedded digital signal processing system again, last carry out operations such as the record of corresponding information or inquiry according to the digitizing characters on license plate that identifies.
The shortcoming of this vehicle management system is that camera is installed in the fixed position, can only discern inspection to the vehicle that enters in its pickup area, cause this method not check vehicle whenever and wherever possible, be difficult to the vehicle of pinpointing the problems, can not handle in time during discovery.
Summary of the invention
The technical problem to be solved in the present invention is to release a kind of portable vehicle recognition device based on embedded platform, the maximum characteristics of this device are exactly portable, it has solved the deficiency that the existing system terminal is installed in the fixed position, and the vehicle management system of being made up of it can be realized the conduct monitoring at all levels to vehicle.
For solving above-mentioned technical matters, the present invention takes following technical scheme.Camera is installed on embedded platform, display/touch screen, wireless transmission (GPRS) module, radio-frequency identification card (RFID) reader and global location (GPS) module, constitute the collection data acquisition, data presentation, data processing, self poisoning, data transmission and communication function are in the described portable unit of one, realization comprises image acquisition, the image pre-service, the car plate location, five key links of Character segmentation and character recognition are in the identification of interior license plate image, the collection and the processing of image are directly finished in described portable unit, fundamentally solved the shortcoming of existed system.In addition, also can communicate by letter, improve recognition accuracy, make and serve the geographic position that control center can grasp operating personnel at any time, so that to its reinforcement with serving control center.
Now be described with reference to the accompanying drawings technical scheme of the present invention.A kind of portable vehicle recognition device based on embedded platform, need and serve control center, gps satellite, GPRS network and the coupling of Internet network, contain embedded platform and camera, display/touch screen, radio-frequency identification card (RFID) reader, wireless transmission (GPRS) module and global location (GPS) module, processor in the embedded platform is the S3C2440 chip of Samsung, described chip is equipped with utilizing camera interface CAMIF, the display/touch screen interface, the first serial line interface UART0, the second serial line interface UART1 and the 3rd serial line interface UART2, the store memory of embedded platform contains WINCE5.0 operating system, it is characterized in that, camera is connected with embedded platform by utilizing camera interface CAMIF, display/touch screen is connected with embedded platform by the display/touch screen interface, radio-frequency (RF) identification (RFID) module is connected with embedded platform by the first serial line interface UART0, wireless transmission (GPRS) module is connected with embedded platform by the second serial line interface UART1, global location (GPS) module is connected with embedded platform by the 3rd serial line interface UART2, and camera is complementary metal oxide semiconductor (CMOS) (CMOS) camera.
With camera collection to license plate image on embedded platform, finish image recognition, obtain the numerical information of car plate quickly and accurately, be the portable key of implement device.Another object of the present invention is to release the method for a kind of described portable unit with the camera collection license board information.For achieving the above object, the present invention adopts following technical scheme.This method is by five steps: the whole operations that collect the numerical information that obtains car plate from license plate image are finished in image acquisition, image pre-service, car plate location, Character segmentation and character recognition.The operating process of this method is seen Fig. 3.
Now be described with reference to the accompanying drawings technical scheme of the present invention.A kind of method with the camera collection license board information of described portable unit is characterized in that the concrete operations step:
First step image acquisition
The camera of described portable unit is aimed at the car plate of vehicle to be checked, take the number of this car plate, collect the coloured image of this car plate;
The image pre-service of second step
Comprise following three processes:
1. gray processing
Coloured image claims the RGB image again, represents the component of red, green, blue look respectively with R, G, B component, and gray processing refers to that image is the processing of black and white by color conversion, compose different weights for R, G, B, make R, G, B all equal the mean value of weighted sum of their value, finish the gray processing of image, that is:
R＝G＝B＝(w
r×R+w
g×G+w
b×B)/3，
W wherein
r, w
g, w
bBe respectively the weights of R, G, B, work as w
r=0.299, w
g=0.587, w
b, will obtain the most rational black white image at=0.114 o'clock;
(illustrate: camera collection to license plate image be colored, because coloured image has comprised a large amount of information, not only taken very big storage space, and also can take a large amount of resources when on embedded platform, handling, the travelling speed of reduction system, so at first the license plate image of the colour that collects should be converted to the license plate image of its corresponding black and white, gray processing refers to that image is the processing of black and white by color conversion.Experience shows, works as w
r=0.299, w
g=0.587, w
b, can obtain the most rational black white image at=0.114 o'clock.)
2. use horizontal Sobel operator extraction edge feature
With the edge feature in the license plate image of horizontal Sobel operator extraction black and white, the directivity of this operator guarantees that the edge feature that extracts is more clear;
(illustrate: the image border is the essential characteristic of image, and the edge is meant the pixel collection that the image pixel gray scale has step to change around those.The variation of each pixel gray scale in certain field of image under consideration utilizes contiguous single order in edge or second order directional derivative Changing Pattern just can obtain image edge information.For making edge feature more clear, with the edge feature in the license plate image of horizontal Sobel operator extraction black and white.)
3. image binaryzation
Image binaryzation refers to come target and background in the differentiate between images according to certain threshold value T, therefore the key of image binaryzation is selected threshold T, come image is carried out binaryzation with the Otsu algorithm, image is divided into target and background two parts, inter-class variance between the target and background is big more, the two-part difference that composing images is described is big more, when part target mistake is divided into background or part background mistake and is divided into target, the capital causes two parts difference to diminish, therefore, make to mean the misclassification probability minimum cutting apart of inter-class variance maximum, the segmentation threshold of image object and background is designated as T, the ratio that the pixel number that belongs to target accounts for entire image is designated as ω
0, its average gray is designated as μ
0, the ratio that the pixel number that belongs to background accounts for entire image is designated as ω
1, its average gray is designated as μ
1, the overall average gray scale of image is designated as μ, and inter-class variance is designated as β, then
μ=ω
0* μ
0Ten ω
1* μ
1(1)
β＝ω
0×(μ
0-μ)
2+ω
1×(μ
1-μ)
2(2)
With formula (1) substitution formula (2), obtain equivalence formula: β=ω
0ω
1(μ
0-μ
1)
2, adopt the method that travels through to make inter-class variance reach maximum T and be the threshold value of being asked;
(illustrate: because image is through horizontal Sobel operator transformation, feasible image grey level histogram presents good bimodal, so the binaryzation of Otsu algorithm is respond well.)
The 3rd step car plate location
1. horizontal transition detection
For the size of the extraction that makes license board information and license plate image irrelevant, the information that must carry out horizontal transition detection and the horizontal saltus step of preservation to image;
(illustrate: very big characteristics of license plate image be exactly character in the car plate than comparatively dense, very high through the gradation of image jump frequency after the Edge Gradient Feature.This is characterized by the zone that just has the intensive concussion of a fritter gray scale on the gradation of image, and all there is gray scale uniformly the inside of character itself and licence plate background color.Utilize above-mentioned feature can realize the extraction of license board information and the irrelevant target of size of license plate image.For this reason, must carry out horizontal transition detection, and preserve the information of horizontal saltus step image.)
2. the texture analysis car plate is located
For the existing standard car plate of China, license plate area has seven standard characters, detecting back character edge 0-1 saltus step feature through upper edge will be comparatively outstanding, the standard of edge transition times≤80 of being expert at according to 18≤car plate, all possible car plate place row filter in the license plate image is come out, be partitioned into the border, the left and right sides of license plate image again with clustering algorithm, obtain the accurate location of car plate;
(illustrate: for the existing standard car plate of China, the span of the edge transition times that car plate is expert at can be set as follows: the setting of (1) lower limit: consider opposite extreme situations, if five numerals of the number-plate number all are " 11111 ", then its edge transition times is 10, when Chinese character and alphabetical a certain provisional capital are one stroke, the edge transition times is minimum and be 4 (as the top line of " capital " " I "), thereby the minimum value of edge transition times should be 14, consider the existence that disturb the car plate both sides, can be made as 18; (2) setting of the upper limit: consider extreme situation, during five numerals of license plate number certain delegation of twice process (as the last the latter half in " 88888 "), its edge transition times is 20 to the maximum, when letter is " M " or " W ", four process delegation of letter, its edge transition times is maximum and be 8, and when Chinese character be " Tibetan " word, the edge transition times was 12 to the maximum when sweep trace passed through this word.Maximal value should be considered in the actual license plate image to have some disturbing factors for 60 (as " hiding WWWWWW ") in theory, this maximal value can be made as 80.Be expert at all possible car plate that above-mentioned standard sieve is selected in the license plate image, be partitioned into border, the left and right sides with clustering algorithm again, just can accurate localization go out car plate.)
The 4th step Character segmentation
Realize the Character segmentation of license plate image by following specific algorithm:
(1) license plate image is carried out vertical projection, orient the border, the left and right sides of each character, and be kept in the array of the number-plate number, (2) again license plate image is carried out horizontal projection, orient the up-and-down boundary of each character, and be kept in the array of the number-plate number and (3) according to the border of each character, character information is kept in the array of the number-plate number, and in image, shows the location situation;
(illustrate: the Character segmentation that realizes license plate image with sciagraphy.According to the uniform characteristics of character marshalling in the license plate image, (1) license plate image is carried out the projection of vertical direction, many and concentrate because of the character zone black pixel point, certain gapping interval is arranged between each characters on license plate, and the perspective view that obtains like this should have several projection peak cluster of concentrating relatively.As long as cut apart according to the characteristics of peak cluster, orient the border, the left and right sides of each character, obtain the character in the license plate image.(2) license plate image is carried out horizontal projection, orient the up-and-down boundary of each character.(3) according to the border of each character, character information is kept in the array of the number-plate number, and in image, shows the location situation.)
The 5th step character recognition
Come the character that is partitioned into is discerned with neural network algorithm.
(illustrate: treat identification character earlier and carry out feature extraction, come the neural network training sorter with the feature that obtains then, remove identification character with neural network classifier again, this method has the ability of very strong self study and self organization ability, very strong processing nonlinear problem, very strong antijamming capability and robustness preferably.)
Compare with existing system, device of the present invention has the following advantages:
1, is convenient for carrying
Functions such as processor, camera, display/touch screen, radio transmission apparatus, GPS, radio frequency identification equipment are integrated in one than in the bigger device of palm, not only multiple functional, and convenient, flexible, be easy to carry, guaranteed that the problem of finding can in time obtain handling.
2, locate fast
Can in time the information of operating personnel and vehicle location be sent to by global location and wireless data transmission and serve control center, conveniently serve control center and this area is sent affairs such as personnel.
3, flexible and efficient
Can directly obtain information of vehicles to the vehicle that is equipped with RFID tag by radio frequency identification module, and can obtain information of vehicles by the photographic analysis image to the vehicle that RFID tag is not installed, and these two kinds of recognition methodss all can be finished in 3s.
4, accurately and reliably
The information of vehicles that the vehicle that is equipped with RFID tag is obtained by radio frequency identification module quick and precisely, and to the vehicle of RFID tag is not installed, in conjunction with image pre-processing methods such as greyscale transformation, rim detection, in location algorithm, got rid of disturbing factors such as illumination and complex background preferably, the car plate locating accuracy has been controlled at about 98%.Meanwhile, can also correct, adopt the mode identification method of neural network that the accuracy rate of car plate identification is guaranteed the inclination car plate.
5, good and cheap
Car plate location and Recognition of License Plate Characters algorithm creatively on embedded platform, have been realized, and RFID read with write device embed wherein, and it is button of realization is finished a basic function on touch-screen, makes equipment volume and cost descend significantly, and very easy-to-use.
Description of drawings
Fig. 1 is portable unit of the present invention and the structural representation of serving control center's coupling.
Fig. 2 is the structural representation of portable unit of the present invention.
Fig. 3 is the operational flowchart of portable unit of the present invention with the method for camera collection license board information.
Embodiment
Portable unit of the present invention is disclosed in above-mentioned summary of the invention and with the method for camera collection license board information, this content is exactly the specific embodiment of the present invention, for avoiding repetition, repeats no more here.Now be described with reference to the accompanying drawings the principle of work and the application of portable unit of the present invention.
This device with serve control center and constitute a portable intelligent vehicle management system.Its structural representation is seen Fig. 1.
Being applied in traffic department's vehicle management with this device is that example illustrates it.If the traffic police finds a suspect vehicle, need go forward it is checked affirmation.At this moment, the operation of this device can be summarized as follows:
A) operating personnel utilize radio-frequency (RF) identification (RFID) or photographic analysis license plate image by this device, obtain the numerical information of the car plate of vehicle.
B) operating personnel send to GPRS network with the numerical information of car plate and current time, geographical location information by wireless transmission (GPRS) module, then through the Internet Network Transmission to serving control center.
C) serve this vehicle is inquired about by control center in database details, such as car owner's name, vehicular seat, car owner's record violating the regulations etc.If finding this car is problem vehicle (stolen, in violation of rules and regulations, false-trademark or fake-licensed car), serve control center and just send warning information, the notifying operation personnel handle, otherwise show normal.At last details are sent to this device.
This device receives from the feedback information of serving control center, and operating personnel make respective handling according to information, such as detaining problem vehicle or the like.
In addition, this device can also be used in parking lot management charge and sub-district security, and the operation of this device can be summarized as follows:
Parking lot management charge: when automobile enters Entrance, if post radio-frequency (RF) identification (RFID) card on the vehicle window of this vehicle, the keeper reads the license plate number of this vehicle and the entry time of this vehicle of record with the RFID card reader of this device, and the information of this license plate number and this entry time by wireless transmission (GPRS) module, send to through GPRS network, Internet network and to serve control center, serve control center and preserve this information.When this vehicle is desired to leave the parking lot, the keeper utilizes the RFID card reader to read the license plate number of this vehicle, and this license plate number sent to through GPRS network, Internet network by wireless transmission (GPRS) module serve control center, service control center determines toll amount according to the entry time of the vehicle of this license plate number, and this pay imformation by Internet network, GPRS network, feed back to this device through wireless transmission (GPRS) module, the keeper is according to the pay imformation that receives, finish charge, open the sluices, let pass to vehicle.
Sub-district security: when automobile enters the sub-district, take a vehicle image the porch keeper with the camera of this device, handle through embedded platform, identify the number-plate number of this vehicle, and write down the entry time of this vehicle, the information of this license plate number and this entry time is passed through wireless transmission (GPRS) module, send to through GPRS network, Internet network and serve control center, serve control center and preserve this information.When this vehicle is desired to leave the sub-district, the keeper takes a vehicle image again with the camera of this device, handle through embedded platform, identify the number-plate number of this vehicle, and with this license plate number by wireless transmission (GPRS) module through GPRS network, the Internet network sends to serves control center, service control center determines toll amount according to the entry time of the vehicle of this license plate number, and this pay imformation by the Internet network, GPRS network, feed back to this device through wireless transmission (GPRS) module, the keeper is according to the pay imformation that receives, finish charge, open the sluices, let pass to vehicle.
Claims (2)
1. portable vehicle recognition device based on embedded platform, need and serve control center, gps satellite, GPRS network and the coupling of Internet network, contain embedded platform and camera, display/touch screen, the radio-frequency (RF) identification card reader, wireless transport module and global location module, processor in the embedded platform is the S3C2440 chip of Samsung, described chip is equipped with utilizing camera interface (CAMIF), the display/touch screen interface, first serial line interface (UART0), second serial line interface (UART1) and the 3rd serial line interface (UART2), the store memory of embedded platform contains WINCE5.0 operating system, it is characterized in that, camera is connected with embedded platform by utilizing camera interface (CAMIF), display/touch screen is connected with embedded platform by the display/touch screen interface, the radio-frequency (RF) identification card reader is connected with embedded platform by first serial line interface (UART0), wireless transport module is connected with embedded platform by second serial line interface (UART1), the global location module is connected with embedded platform by the 3rd serial line interface (UART2), and camera is complementary metal oxide semiconductor (CMOS)/touch-screen camera.
2. the method with the camera collection license board information of the described portable unit of claim 1 is characterized in that the concrete operations step:
First step image acquisition
The camera of described portable unit is aimed at the car plate of vehicle to be checked, take the number of this car plate, collect the coloured image of this car plate;
The image pre-service of second step
Comprise following three processes:
1. gray processing
Coloured image claims the RGB image again, represents the component of red, green, blue look respectively with R, G, B component, and gray processing refers to that image is the processing of black and white by color conversion, compose different weights for R, G, B, make R, G, B all equal the mean value of weighted sum of their value, finish the gray processing of image, that is:
R＝G＝B＝(w
r×R+w
g×G+w
b×B)/3
W wherein
r, w
g, w
bBe respectively the weights of R, G, B, work as w
r=0.299, w
g=0.587, w
b, will obtain the most rational black white image at=0.114 o'clock;
2. use horizontal Sobel operator extraction edge feature
With the edge feature in the license plate image of horizontal Sobel operator extraction black and white, the directivity of this operator guarantees that the edge feature that extracts is more clear;
3. image binaryzation
Image binaryzation refers to come target and background in the differentiate between images according to certain threshold value T, therefore the key of image binaryzation is selected threshold T, come image is carried out binaryzation with the Otsu algorithm, image is divided into target and background two parts, inter-class variance between the target and background is big more, the two-part difference that composing images is described is big more, when part target mistake is divided into background or part background mistake and is divided into target, the capital causes two parts difference to diminish, therefore, make to mean the misclassification probability minimum cutting apart of inter-class variance maximum, the segmentation threshold of image object and background is designated as T, the ratio that the pixel number that belongs to target accounts for entire image is designated as ω
0, its average gray is designated as μ
0, the ratio that the pixel number that belongs to background accounts for entire image is designated as ω
1, its average gray is designated as μ
1, the overall average gray scale of image is designated as μ, and inter-class variance is designated as β, then
μ＝ω
0×μ
0+ω
1×μ
1 (1)
β＝ω
0×(μ
0-μ)
2+ω
1×(μ
1-μ)
2 (2)
With formula (1) substitution formula (2), obtain equivalence formula: β=ω
0ω
1(μ
0-μ
1)
2, adopt the method that travels through to make inter-class variance reach maximum T and be the threshold value of being asked;
The 3rd step car plate location
1. horizontal transition detection
For the size of the extraction that makes license board information and license plate image irrelevant, the information that must carry out horizontal transition detection and the horizontal saltus step of preservation to image;
2. the texture analysis car plate is located
For the existing standard car plate of China, license plate area has seven standard characters, detecting back character edge 0-1 saltus step feature through upper edge will be comparatively outstanding, the standard of edge transition times≤80 of being expert at according to 18≤car plate, all possible car plate place row filter in the license plate image is come out, be partitioned into the border, the left and right sides of license plate image again with clustering algorithm, obtain the accurate location of car plate;
The 4th step Character segmentation
Realize the Character segmentation of license plate image by following specific algorithm:
(1) license plate image is carried out vertical projection, orient the border, the left and right sides of each character, and be kept in the array of the number-plate number, (2) again license plate image is carried out horizontal projection, orient the up-and-down boundary of each character, and be kept in the array of the number-plate number and (3) according to the border of each character, character information is kept in the array of the number-plate number, and in image, shows the location situation;
The 5th step character recognition
Come the character that is partitioned into is discerned with neural network algorithm.
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