CN105118305B - Motor pool outlet vehicle management platform - Google Patents
Motor pool outlet vehicle management platform Download PDFInfo
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- CN105118305B CN105118305B CN201510532857.2A CN201510532857A CN105118305B CN 105118305 B CN105118305 B CN 105118305B CN 201510532857 A CN201510532857 A CN 201510532857A CN 105118305 B CN105118305 B CN 105118305B
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
- G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
- G07B15/06—Arrangements for road pricing or congestion charging of vehicles or vehicle users, e.g. automatic toll systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/08—Detecting or categorising vehicles
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Abstract
The present invention relates to a kind of motor pool outlet vehicle management platform, the outlet of described motor pool accepts the vehicle in multiple export house tracks and sails into, described management platform includes parking lot congestion level detection equipment, master image acquiring and processing device, embedded processing equipment and multiple subimage acquiring and processing device, the information of vehicles that embedded processing equipment sends based on the multiple subimage acquiring and processing devices received determines vehicle appearance predetermined sequence, master image acquiring and processing device information of vehicles based on vehicle appearance predetermined sequence and exit position determines the charging policy of the vehicle of exit position, master image acquiring and processing device and subimage acquiring and processing device all include that haze processes subset, for removing the corresponding haze composition gathered in image.By the present invention, even if in various haze weather, it is also possible to improve the traffic efficiency of the motor pool with multiple export house track, save time and effort for car owner.
Description
The present invention is Application No. 201510178865.1, filing date April 16 in 2015 day,
The divisional application of the patent of bright entitled " motor pool outlet vehicle management platform ".
Technical field
The present invention relates to detection of electrons field, particularly relate to a kind of motor pool outlet vehicle management and put down
Platform.
Background technology
Parking lot, refers to the place for parking cars.Divide by land use situation, parking lot
Underground parking and motor pool two class can be divided into.The main task in parking lot is that car is parked in keeping
, collect parking fee.Parking lot is the place for storing cycle.Parking lot has only draws parking lattice and nothing
People's management and the simple parking lot of charge, also have and be furnished with lairage mouth, park manager and timing gathering
The pay parking of member.Modernization parking lot Chang You automatization time counting toll collection system, closed-circuit television and
Video recorder system.Parking lot master and the legal responsibility of manager, be generally only offer place to person for driving a car
Scholar's parked vehicle, support vehicles are not undermined mistake car responsibility, and about exemption clause of typically fitting is in parking
Field refers to for car owner outside gate.
For motor pool, in the case of stopping too much, a problem is had to need to solve:
Due to personnel and the restriction in place, motor pool outlet is fewer, and a general outlet is corresponding multiple
Enter track, when the multiple vehicles on multiple entrance tracks all collect in an outlet, for vehicle
The order not having corresponding ordering mechanism that vehicle is entered outlet is managed, and causes each vehicle to be driven
The person of sailing falls over each other and robs inlet/outlet position, inevitably brings some accidents, and this is to export
Traffic efficiency will sink into vicious cycle.
In prior art, the technical scheme to motor pool outlet vehicle sequence is little, even if having
Electronics sequencing schemes based on image procossing, also due to have ignored what vehicle was sorted by various haze weather
Impact, haze composition may cause image to detect unsuccessfully, thus has a strong impact on normal electronic vehicle row
Sequence operates.
Accordingly, it would be desirable to the technical scheme of a kind of motor pool outlet vehicle management, it is possible to for leave
The car owner of motor pool provides the outlet Queue sequence being referred to, it is to avoid sending out of dispute and accident
Raw, meanwhile, it is capable to overcome the haze weather impact on sorting operation, improve the reliability of scheme.
Summary of the invention
In order to solve the problems referred to above, the invention provides a kind of motor pool outlet vehicle management and put down
Platform, for motor pool, completes vehicle letter based on high-precision image acquisition and image recognition technology
The identification of breath, establishes a normalized vehicle pass-through order keeping mechanism, it is ensured that every chassis
Fair, reasonably pass through order, improve the traffic efficiency of motor pool, it is to avoid block up and thing
Therefore generation, more it is essential that determine the haze influence factor to image according to atmospheric attenuation model,
And go hazeization to process the detection image gathered under many haze weather, improve this platform can
By property.
According to an aspect of the present invention, it is provided that a kind of motor pool outlet vehicle management platform, institute
The vehicle stating the multiple export house tracks of motor pool outlet acceptance sails into, and described management platform includes:
Parking lot congestion level detection equipment, master image acquiring and processing device, embedded processing equipment and multiple
Subimage acquiring and processing device, congestion level detection equipment in parking lot is for detecting in motor pool
Vehicle fleet size, each subimage acquiring and processing device is for gathering the vehicle on an export house track
Information, master image acquiring and processing device is for gathering the information of vehicles of exit position, and embedded processing sets
The standby information of vehicles sent based on the multiple subimage acquiring and processing devices received determines that vehicle appears on the scene
Predetermined sequence, master image acquiring and processing device is based on vehicle appearance predetermined sequence and the vehicle of exit position
Information determines the charging policy of the vehicle of exit position, master image acquiring and processing device and subimage collection
Processing equipment all includes that haze processes subset, becomes for removing the corresponding haze gathered in image
Point, wherein, the vehicle fleet size that embedded processing equipment is additionally based upon in motor pool determines whether to manage
Platform wakes up up from resting state.
More specifically, in described motor pool outlet vehicle management platform, also include: static state is deposited
Storage equipment, is used for prestoring vehicle upper limit gray threshold and vehicle lower limit gray threshold, described vehicle
Upper limit gray threshold and described vehicle lower limit gray threshold are used for the vehicle in image and background separation,
Described static storage device has also prestored charge synopsis, and described charge synopsis meets with numbering
Grade is index, stores each numbering and meets the downward percentage of the Parking Fee corresponding to grade
Ratio, wherein, in described charge synopsis, numbering meets the highest grade, corresponding Parking Fee
Lower percentage ratio the biggest；Described parking lot congestion level detection equipment, sets including panoramic high-definition shooting
Standby, parking lot Image semantic classification subset and parking lot vehicle identification subset, described panoramic high-definition is taken the photograph
As subset uses the resolution acquisition parking lot image of 3840 × 2160, described parking lot image is located in advance
Reason subset is connected with described panoramic high-definition shooting subset, and it is right to carry out described parking lot image successively
Process than degree enhancing, 3 × 3 pixel window medium filterings and gray processing, to obtain gray processing parking lot figure
Picture, described parking lot vehicle identification subset sets with static storage device and parking lot Image semantic classification
Back-up does not connect, by gray value in the image of described gray processing parking lot at vehicle upper limit gray threshold and car
Pixel identification between lower limit gray threshold also forms multiple parking lots vehicle pattern, and outputting parking
The quantity of field vehicle pattern；Described subimage acquiring and processing device is positioned at the upper of corresponding export house track
Side, including: carriageway image gathers subset, shoots corresponding export house track to gather carriageway image；
First goes haze to process subset, is positioned at carriageway image collection subset and carriageway image pretreatment sets
Between Bei, for removing the haze composition in described carriageway image, to obtain sharpening carriageway image；
Carriageway image pretreatment subset, go with described first haze process subset be connected, to described clearly
Change carriageway image and carry out contrast enhancing, self adaptation recursive filtering and gray processing process successively, to obtain
Gray processing carriageway image；Track Car license recognition subset and described static storage device and described track figure
As pretreatment subset connects respectively, by gray value in described gray processing carriageway image on described vehicle
Limit the pixel identification between gray threshold and described vehicle lower limit gray threshold and form track vehicle figure
Case, based on the track number-plate number in track vehicle pattern described in OCR recognizer identification；Described
Embedded processing equipment is positioned at the machine room of motor pool, including the first timing subset and the first numbering
Subset, described first timing subset is used for providing the instant moment, described first numbering subset with
Described first timing subset and the plurality of subimage acquiring and processing device connect respectively, every every day
Zero time, remove the vehicle appearance predetermined sequence of a day, start all tracks received from 1
The number-plate number is ranked up, to form the vehicle appearance predetermined sequence after sorting；Described master image collection
Processing equipment is positioned at the top of EXIT, including: outlet image acquisition subset, to parking lot
Exit position carries out shooting to gather outlet diagram picture；Second goes haze to process subset, is positioned at outlet diagram
As gather subset and outlet Image semantic classification subset between, for remove described outlet diagram as in
Haze composition, to obtain sharpening outlet diagram picture；Outlet Image semantic classification subset, with described second
Go haze process subset connect, described sharpening outlet diagram picture is carried out successively contrast enhancing, from
Adapt to recursive filtering and gray processing processes, to obtain gray processing outlet diagram picture；Outlet Car license recognition sets
For being connected respectively, by described ash with described static storage device and described outlet Image semantic classification subset
Degree dissolves in mouthful image gray value at described vehicle upper limit gray threshold and described vehicle lower limit gray scale threshold
Pixel identification between value also forms outlet vehicle pattern, goes out based on described in OCR recognizer identification
The exit number-plate number in mouth vehicle pattern；Second timing subset, is used for providing the instant moment；
Second numbering subset, with described second timing subset and described outlet Car license recognition subset difference
Connect, every every day zero time, be numbered from the 1 exit number-plate number started receiving；
Parking Fee calculates subset, with described second numbering subset, described static storage device and described
Embedded processing equipment connects respectively, based on the exit number-plate number inquiry exit number-plate number at car
Serial number in appearance predetermined sequence, by the numbering of described serial number Yu the described exit number-plate number
Mate, to determine numbering goodness of fit, determine that described numbering meets grade according to numbering goodness of fit,
The downward of the Parking Fee corresponding to grade is met in the lookup of described charge synopsis and the numbering determined
Percentage ratio, lowers, based on find, the outlet vehicle that percentage ratio is corresponding to the described exit number-plate number
Receivable Parking Fee lower, to obtain receivable Parking Fee, wherein, described serial number and institute
State the numbering more coupling of the exit number-plate number, it is determined that numbering goodness of fit the highest, the numbering that determines
Meet the highest grade；Described first goes haze to process subset includes: the first haze concentration detecting unit,
It is positioned in air, for the haze concentration of the corresponding position, export house track of detection in real time, and according to
Haze concentration determines that intensity removed by haze, and described haze removes intensity value between 0 to 1；First
Overall air light value acquiring unit, gathers subset with described carriageway image and is connected to obtain described track
Image, calculates the gray value of each pixel in described carriageway image, by the ash of pixel maximum for gray value
Angle value is as overall air light value；First atmospheric scattering light value acquiring unit, adopts with described carriageway image
Collection subset and described first haze concentration detecting unit connect respectively, each to described carriageway image
Individual pixel, extracts its R, G, B tri-in Color Channel pixel value minima as target pixel value,
Use and keep the Gaussian filter EPGF (edge-preserving gaussian filter) at edge right
Described target pixel value is filtered processing to obtain filtered target pixel value, is deducted by target pixel value
Filtered target pixel value, to obtain object pixel difference, uses EPGF to filter object pixel difference
Ripple processes to obtain filtered target pixel value difference, filtered target pixel value is deducted filtered target pixel poor
It is worth to obtain haze removal reference value, haze is removed intensity and is multiplied by haze removal reference value to obtain mist
Haze removes threshold value, takes haze and removes the minima in threshold value and target pixel value as comparison reference,
Take the atmospheric scattering light value as each pixel of the maximum in comparison reference and 0；First medium
Transfer rate acquiring unit, with the described first overall air light value acquiring unit and described first atmospheric scattering
Light value acquiring unit connects respectively, by the atmospheric scattering light value of each pixel divided by overall air light value
To obtain except value, deduct described except value is to obtain the medium transmission rate of each pixel by 1；First is clear
Clearization image acquisition unit, gathers subset, the described first overall air light value with described carriageway image
Acquiring unit and described first medium transfer rate acquiring unit connect respectively, deduct each pixel by 1
Medium transmission rate to obtain the first difference, described first difference is multiplied by overall air light value to obtain
Product value, deducts described product value to obtain by the pixel value of each pixel in described carriageway image
Two differences, by described second difference divided by the medium transmission rate of each pixel to obtain each pixel
Sharpening pixel value, in described carriageway image, the pixel value of each pixel includes described carriageway image
In the R of each pixel, G, B tri-Color Channel pixel value, correspondingly, it is thus achieved that each picture
The sharpening pixel value of element includes the R of each pixel, G, B tri-Color Channel sharpening pixel value,
The sharpening pixel value of all pixels forms described sharpening carriageway image；Described second goes haze to process
Subset includes: the second haze concentration detecting unit, is positioned in air, detects parking lot in real time
The haze concentration of exit position, and determine that intensity removed by haze according to haze concentration, described haze is removed
Intensity value is between 0 to 1；Second overall air light value acquiring unit, adopts with described outlet diagram picture
Collection subset connects to obtain described outlet diagram picture, calculates the gray scale of each pixel in described outlet diagram picture
Value, using the gray value of pixel maximum for gray value as overall air light value；Second air scattered light value
Acquiring unit, with described outlet image acquisition subset and described second haze concentration detecting unit difference
Connect, each pixel to described outlet diagram picture, extract its R, G, B tri-Color Channel pixel
In value, minima is as target pixel value, uses the Gaussian filter EPGF keeping edge
Described target pixel value is filtered processing to obtain filter by (edge-preserving gaussian filter)
Ripple target pixel value, deducts filtered target pixel value to obtain object pixel difference by target pixel value,
EPGF is used to be filtered object pixel difference processing to obtain filtered target pixel value difference, will filter
Ripple target pixel value deducts filtered target pixel value difference and removes reference value to obtain haze, is removed by haze
Intensity is multiplied by haze removal reference value removes threshold value to obtain haze, takes haze and removes threshold value and target picture
Minima in element value, as comparison reference, takes the maximum in comparison reference and 0 as each
The atmospheric scattering light value of individual pixel；Second medium transfer rate acquiring unit, with the described second overall air
Light value acquiring unit and described second air scattered light value acquiring unit connect, respectively by each pixel
Atmospheric scattering light value divided by overall air light value to obtain except value, deduct described except value is with acquisition by 1
The medium transmission rate of each pixel；Second sharpening image acquisition unit, adopts with described outlet diagram picture
Collection subset, the described second overall air light value acquiring unit and described second medium transfer rate obtain single
Unit connects respectively, deducts the medium transmission rate of each pixel by 1 to obtain the first difference, by described
First difference is multiplied by overall air light value to obtain product value, by each pixel in described outlet diagram picture
Pixel value deduct described product value to obtain the second difference, by described second difference divided by each picture
The medium transmission rate of element is to obtain the sharpening pixel value of each pixel, each in described outlet diagram picture
The pixel value of individual pixel includes the R of each pixel in described outlet diagram picture, G, B tri-Color Channel
Pixel value, correspondingly, it is thus achieved that the sharpening pixel value of each pixel include the R of each pixel,
G, B tri-Color Channel sharpening pixel value, the sharpening pixel value composition of all pixels is described clearly
Dissolve a mouthful image；Wherein, the plurality of subimage acquiring and processing device exports to described motor pool
Distance equal.
More specifically, in described motor pool outlet vehicle management platform, described embedded processing
Equipment is more than or equal to predetermined number threshold value in the quantity of described parking lot congestion level detection equipment output
Time, described management platform is waken up up from resting state.
More specifically, in described motor pool outlet vehicle management platform, described embedded processing
Equipment, will when the quantity of described parking lot congestion level detection equipment output is less than predetermined number threshold value
Described management platform enters resting state.
More specifically, in described motor pool outlet vehicle management platform, described predetermined number threshold
Value is pre-stored in described static storage device.
More specifically, in described motor pool outlet vehicle management platform, described embedded processing
Equipment is ARM11 processing equipment.
Accompanying drawing explanation
Below with reference to accompanying drawing, embodiment of the present invention are described, wherein:
Fig. 1 is the knot exporting vehicle management platform according to the motor pool shown in embodiment of the present invention
Structure block diagram.
Detailed description of the invention
Motor pool to the present invention exports the embodiment party of vehicle management platform below with reference to accompanying drawings
Case is described in detail.
Along with acceleration and the raising of people's living standard of urbanization process, automobile has entered into thousand
Ten thousand families, the work of people, doing shopping and travelling all be unable to do without automobile.In each working space, shopping field
Institute and tourist attractions, can see that a large amount of vehicle is assembled, for parking of these vehicles of specification, it is to avoid
Dispute occur, also for the extra earning of relevant departments, above-mentioned place all can plan that bulk region is as parking
, parked vehicle was charged according to the storage period.
Motor pool is owing to the construction period is fast, security performance is high and is prone to the advantages such as examination & approval, and is subject to
Favor to car parking department.But, motor pool there is also some problems, most importantly,
In the case of vehicle flowrate is big, owing to a lot of motor pools only have a small amount of outlet, each outlet
Front all there may be three even more than three sail track into, at this moment, multiple cars sailing track into
Clamp-oning an outlet, because the order sailing outlet into cannot be planned, each vehicle is thought soon simultaneously
Speed is left, and this necessarily causes disorder, even results in collision accident and occurs.
Prior art lacks the order of export Concept of Maintenance of above-mentioned motor pool, needs to build one
Can be used in the motor pool outlet vehicle management platform of motor pool, it is possible to rationally arrange and have
The vehicle pass-through order in multiple outlet fronts sailing track into, meanwhile, in view of the environment of motor pool
Considering, this management platform needs to overcome the interference of various haze weather.
To this, the present invention has built a kind of motor pool outlet vehicle management platform, uses image to adopt
Collect and know the information of vehicles in each entrance track in advance otherwise, by rational ordering mechanism with sharp
The mechanism of encouraging forces driver to wait according to Queue sequence, improves the current effect of motor pool
Rate, and, this management platform can also remove the impact on gathering image of the haze composition,
Fig. 1 is the knot exporting vehicle management platform according to the motor pool shown in embodiment of the present invention
Structure block diagram, the outlet of described motor pool accepts the vehicle in multiple export house tracks and sails into, described pipe
Platform includes parking lot congestion level detection equipment 1, master image acquiring and processing device 2, embedded
3 and n sub-image acquisition and processing equipment 4 of processing equipment, n is the natural number more than 1.
Wherein, parking lot congestion level detection equipment 1 is used for detecting the vehicle fleet size in motor pool,
Each subimage acquiring and processing device 4 is for gathering the information of vehicles on an export house track, main
Image acquisition and processing equipment 2 is for gathering the information of vehicles of exit position, embedded processing equipment 3 base
The information of vehicles sent in the n received sub-image acquisition and processing equipment 4 determines that vehicle appearance is preset
Sequence, master image acquiring and processing device 2 vehicle based on vehicle appearance predetermined sequence and exit position is believed
Breath determines the charging policy of the vehicle of exit position, master image acquiring and processing device 2 and subimage collection
Processing equipment 4 all includes that haze processes subset, becomes for removing the corresponding haze gathered in image
Point, wherein, the vehicle fleet size that embedded processing equipment 3 is additionally based upon in motor pool determine whether by
Management platform wakes up up from resting state.
Then, the concrete structure continuing the outlet vehicle management platform of the motor pool to the present invention is carried out
Further instruction.
Described management platform also includes: static storage device, is used for prestoring vehicle upper limit gray scale threshold
Value and vehicle lower limit gray threshold, described vehicle upper limit gray threshold and described vehicle lower limit gray threshold
For by the vehicle in image and background separation, it is right that described static storage device has also prestored charge
According to table, described charge synopsis with numbering meet grade for index, store each numbering and meet
The downward percentage ratio of the Parking Fee corresponding to Ji, wherein, in described charge synopsis, numbering symbol
Closing the highest grade, the downward percentage ratio of corresponding Parking Fee is the biggest.
Described parking lot congestion level detection equipment 1, images subset, parking lot including panoramic high-definition
Image semantic classification subset and parking lot vehicle identification subset, described panoramic high-definition shooting subset is adopted
With the resolution acquisition parking lot image of 3840 × 2160, described parking lot Image semantic classification subset with
Described panoramic high-definition shooting subset connect, described parking lot image is carried out successively contrast enhancing,
3 × 3 pixel window medium filterings and gray processing process, to obtain gray processing parking lot image, described in stop
Parking lot vehicle identification subset connects respectively with static storage device and parking lot Image semantic classification subset
Connect, by gray value in the image of described gray processing parking lot at vehicle upper limit gray threshold and vehicle lower limit ash
Spend the pixel identification between threshold value and form multiple parking lots vehicle pattern, and outputting parking field vehicle figure
The quantity of case.
Described subimage acquiring and processing device 4 is positioned at the top in corresponding export house track, including: track
Image acquisition subset, shoots corresponding export house track to gather carriageway image；First goes at haze
Reason subset, gathers between subset and carriageway image pretreatment subset at carriageway image, is used for
Remove the haze composition in described carriageway image, to obtain sharpening carriageway image；Carriageway image is located in advance
Reason subset, goes with described first haze to process subset and is connected, depend on described sharpening carriageway image
Secondary contrast enhancing, self adaptation recursive filtering and the gray processing of carrying out processes, to obtain gray processing track figure
Picture；Track Car license recognition subset sets with described static storage device and described carriageway image pretreatment
Back-up does not connect, by gray value in described gray processing carriageway image at described vehicle upper limit gray threshold and
Pixel identification between described vehicle lower limit gray threshold also forms track vehicle pattern, based on OCR
The track number-plate number in vehicle pattern in track described in recognizer identification.
Described embedded processing equipment 3 is positioned at the machine room of motor pool, including the first timing subset
With the first numbering subset, described first timing subset is used for providing the instant moment, and described first compiles
Work song equipment connects respectively with described first timing subset and the plurality of subimage acquiring and processing device
Connect, every every day zero time, remove the vehicle appearance predetermined sequence of a day, start reception from 1
To all tracks number-plate number be ranked up, with formed sequence after vehicle appearance predetermined sequence.
Described master image acquiring and processing device 2 is positioned at the top of EXIT, including: outlet diagram picture
Gather subset, shoot to gather outlet diagram picture to EXIT position；Second goes at haze
Reason subset, between outlet image acquisition subset and outlet Image semantic classification subset, is used for
Remove the haze composition in described outlet diagram picture, to obtain sharpening outlet diagram picture；Outlet diagram picture is located in advance
Reason subset, goes with described second haze to process subset and is connected, depend on described sharpening outlet diagram picture
Secondary contrast enhancing, self adaptation recursive filtering and the gray processing of carrying out processes, to obtain gray processing outlet diagram
Picture；Outlet Car license recognition subset sets with described static storage device and described outlet Image semantic classification
Back-up does not connect, by gray value in described gray processing outlet diagram picture at described vehicle upper limit gray threshold and
Pixel identification between described vehicle lower limit gray threshold also forms outlet vehicle pattern, based on OCR
The exit number-plate number in vehicle pattern is exported described in recognizer identification；Second timing subset,
For providing the instant moment；Second numbering subset, with described second timing subset and described outlet
Car license recognition subset connects respectively, every every day zero time, start the exit received from 1
The number-plate number is numbered；Parking Fee calculates subset, with described second numbering subset, described
Static storage device and described embedded processing equipment 3 connect respectively, look into based on the exit number-plate number
Ask exit number-plate number serial number in vehicle appearance predetermined sequence, by described serial number with described
The numbering of the exit number-plate number is mated, to determine numbering goodness of fit, true according to numbering goodness of fit
Fixed described numbering meets grade, meets grade institute in the lookup of described charge synopsis and the numbering determined right
The downward percentage ratio of the Parking Fee answered, based on the downward percentage ratio found to described exit car plate
The receivable Parking Fee of the outlet vehicle that number is corresponding is lowered, to obtain receivable Parking Fee, its
In, the numbering of described serial number and the described exit number-plate number is more mated, it is determined that numbering meet
Spending the highest, the numbering determined meets the highest grade.
Wherein, described first haze process subset is gone to include: the first haze concentration detecting unit, position
In air, for the haze concentration of the corresponding position, export house track of detection in real time, and according to mist
Haze concentration determines that intensity removed by haze, and described haze removes intensity value between 0 to 1；First is whole
Body atmosphere light value acquiring unit, gathers subset and is connected to obtain described track figure with described carriageway image
Picture, calculates the gray value of each pixel in described carriageway image, by the gray scale of pixel maximum for gray value
Value is as overall air light value；First atmospheric scattering light value acquiring unit, gathers with described carriageway image
Subset and described first haze concentration detecting unit connect respectively, to each of described carriageway image
Pixel, extracts its R, G, B tri-in Color Channel pixel value minima as target pixel value, make
With keeping the Gaussian filter EPGF (edge-preserving gaussian filter) at edge to institute
State target pixel value to be filtered processing to obtain filtered target pixel value, target pixel value is deducted filter
Ripple target pixel value, to obtain object pixel difference, uses EPGF to be filtered object pixel difference
Process to obtain filtered target pixel value difference, filtered target pixel value is deducted filtered target pixel value difference
To obtain haze removal reference value, haze is removed intensity and is multiplied by haze removal reference value to obtain haze
Remove threshold value, take haze and remove the minima in threshold value and target pixel value as comparison reference, take
Maximum in comparison reference and 0 is as the atmospheric scattering light value of each pixel；First medium passes
Defeated rate acquiring unit, with the described first overall air light value acquiring unit and described first atmospheric scattering light
Value acquiring unit connects respectively, by the atmospheric scattering light value of each pixel divided by overall air light value with
Obtain except value, deduct 1 described except value is to obtain the medium transmission rate of each pixel；First is clear
Change image acquisition unit, obtain with described carriageway image collection subset, the described first overall air light value
Take unit and described first medium transfer rate acquiring unit connects respectively, deduct each pixel by 1
Described first difference, to obtain the first difference, is multiplied by overall air light value and takes advantage of to obtain by medium transmission rate
Product value, deducts described product value to obtain second by the pixel value of each pixel in described carriageway image
Difference, by described second difference divided by the medium transmission rate of each pixel to obtain each pixel
Sharpening pixel value, during in described carriageway image, the pixel value of each pixel includes described carriageway image
The R of each pixel, G, B tri-Color Channel pixel value, correspondingly, it is thus achieved that each pixel
Sharpening pixel value include the R of each pixel, G, B tri-Color Channel sharpening pixel value,
The sharpening pixel value of all pixels forms described sharpening carriageway image.
Wherein, described second haze process subset is gone to include: the second haze concentration detecting unit, position
In air, for the haze concentration of detection EXIT position in real time and true according to haze concentration
Determining haze and remove intensity, described haze removes intensity value between 0 to 1；Second overall atmosphere light
Value acquiring unit, is connected with described outlet image acquisition subset to obtain described outlet diagram picture, calculates
The gray value of each pixel in described outlet diagram picture, using the gray value of pixel maximum for gray value as whole
Body atmosphere light value；Second air scattered light value acquiring unit, with described outlet image acquisition subset and
Described second haze concentration detecting unit connects respectively, and each pixel to described outlet diagram picture carries
Take its R, G, B tri-in Color Channel pixel value minima as target pixel value, use and keep limit
The Gaussian filter EPGF (edge-preserving gaussian filter) of edge is to described target picture
Element value is filtered processing to obtain filtered target pixel value, and target pixel value deducts filtered target picture
Element value, to obtain object pixel difference, uses EPGF to be filtered object pixel difference processing to obtain
Obtain filtered target pixel value difference, filtered target pixel value is deducted filtered target pixel value difference to obtain mist
Haze removes reference value, haze is removed intensity and is multiplied by haze removal reference value to obtain haze removal threshold
Value, takes haze and removes the minima in threshold value and target pixel value as comparison reference, take and compare ginseng
Examine the atmospheric scattering light value as each pixel of the maximum in value and 0；Second medium transfer rate obtains
Take unit, obtain with the described second overall air light value acquiring unit and described second air scattered light value
Unit connects respectively, is removed to obtain divided by overall air light value by the atmospheric scattering light value of each pixel
Value, deducts described except value is to obtain the medium transmission rate of each pixel by 1；Second sharpening image
Acquiring unit, with described outlet image acquisition subset, the described second overall air light value acquiring unit
Connecting respectively with described second medium transfer rate acquiring unit, the medium deducting each pixel by 1 passes
Described first difference, to obtain the first difference, is multiplied by overall air light value to obtain product value by defeated rate,
The pixel value of each pixel in described outlet diagram picture is deducted described product value to obtain the second difference,
By described second difference divided by the medium transmission rate of each pixel to obtain the clear of each pixel
Changing pixel value, in described outlet diagram picture, the pixel value of each pixel is each in including described outlet diagram picture
The R of individual pixel, G, B tri-Color Channel pixel value, correspondingly, it is thus achieved that each pixel clear
Clearization pixel value includes the R of each pixel, G, B tri-Color Channel sharpening pixel value, all
The sharpening pixel value of pixel forms described sharpening outlet diagram picture.
Wherein, the plurality of subimage acquiring and processing device 4 is to the distance of described motor pool outlet
Equal.
Alternatively, in described motor pool outlet vehicle management platform, described embedded processing sets
Standby 3 detect the quantity of equipment 1 output more than or equal to predetermined number threshold value at described parking lot congestion level
Time, described management platform is waken up up from resting state, described embedded processing sets 3 in described parking
When the quantity of field congestion level detection equipment 1 output is less than predetermined number threshold value, by described management platform
Entering resting state, described predetermined number threshold value is pre-stored in described static storage device, and described
Embedded processing equipment 3 is ARM11 processing equipment.
It addition, haze image can remove haze by what a series of images processing equipment realized image,
To obtain the image of sharpening, improve the visibility of image.These image processing equipments perform not respectively
Same image processing function, the principle formed based on haze, reach to remove the effect of haze.Haze figure
The sharpening of picture processes all has great using value, military domain bag for dual-use field
Including military and national defense, remote sensing navigation etc., civil area includes road monitoring, target following and automatic Pilot
Deng.
The process that haze image is formed can be described by atmospheric attenuation process, in haze image and reality
The medium of the available overall air light value of the relation between image i.e. sharpening image and each pixel passes
Defeated rate is stated, i.e. in the case of known haze image, according to overall air light value and each picture
The medium transmission rate of element, can solve sharpening image.
There are some and have in the solving of medium transmission rate for overall air light value and each pixel
Effect and through the means of checking, such as, for the medium transmission rate of each pixel, need to obtain whole
Body atmosphere light value and the atmospheric scattering light value of each pixel, and the atmospheric scattering light value of each pixel
Can be at the Gaussian smoothing that each pixel pixel value in haze image is carried out twice holding edge
Filtering and obtain, therebetween, the intensity that haze is removed is adjustable；And the acquisition pattern of entirety air light value has
Two kinds, a kind of mode is, (i.e. can make in haze image by obtaining the black channel of haze image
The black channel value of some pixels is the lowest, black channel is R, and G, B tri-is in Color Channel
A kind of), in haze image, the multiple pixels bigger than normal by finding black channel pixel value are found
The pixel of gray value maximum obtains, and gray value that will search out, gray value is maximum pixel is made
For overall air light value, participate in the sharpening of each pixel in haze image and process；It addition, it is overall
Air light value also can obtain in the following manner: calculates the gray value of each pixel in haze image, will
The gray value of the pixel that gray value is maximum is as overall air light value.
Relation between concrete haze image and real image i.e. sharpening image, and parameters
Between relation can be found in above content.
By the discussion to haze image formation basic theory, build between haze image and sharpening image
Relation, represent this relation by multiple parameters, subsequently by the multiple parameter values obtained and haze figure
The image that picture the most reducible acquisition definition is higher, owing to some statistical means have been used in the acquisition of parameter
And empirical means, the image that the most described definition is higher can not be fully equivalent to real image, but
Have and considerable degree of gone haze effect, provide effectively for the every field operation under haze weather
Ensure.
Use the motor pool outlet vehicle management platform of the present invention, lack room for prior art
Outer EXIT ordering mechanism and in the technical problem of haze weather Detection results deviation, introduces height
Precision Image treatment technology realizes the letter to the vehicle on each entrance track of outlet and outlet
The identification of breath, introduces effective ordering mechanism and incentive mechanism, encourages driver according to getting ahead first
Order sails the outlet of motor pool into, more it is essential that use and high-precision go haze processing equipment
Solve and detect the fuzzy problem that image may bring because of haze weather, thus the most effectively
Improve the vehicle pass-through speed of motor pool exit position.
Although it is understood that the present invention discloses as above with preferred embodiment, but above-mentioned enforcement
Example is not limited to the present invention.For any those of ordinary skill in the art, without departing from
Under technical solution of the present invention ambit, all may utilize the technology contents of the disclosure above to the technology of the present invention
Scheme makes many possible variations and modification, or is revised as the Equivalent embodiments of equivalent variations.Therefore,
Every content without departing from technical solution of the present invention, the technical spirit of the foundation present invention is to above example
Any simple modification, equivalent variations and the modification done, all still falls within technical solution of the present invention protection
In the range of.
Claims (1)
1. a motor pool outlet vehicle management platform, the outlet of described motor pool accepts many
The vehicle in individual export house track sails into, described management platform include parking lot congestion level detection equipment,
Master image acquiring and processing device, embedded processing equipment and multiple subimage acquiring and processing device, stop
Field congestion level detection equipment is for detecting the vehicle fleet size in motor pool, and each subimage is adopted
Collection processing equipment is for gathering the information of vehicles on an export house track, master image acquiring and processing device
For gathering the information of vehicles of exit position, embedded processing equipment is based on the multiple subimages received
The information of vehicles that acquiring and processing device sends determines vehicle appearance predetermined sequence, and master image acquisition process sets
Standby information of vehicles based on vehicle appearance predetermined sequence and exit position determines the vehicle of exit position
Charging policy, master image acquiring and processing device and subimage acquiring and processing device all include that haze processes
Subset, for removing the corresponding haze composition gathered in image, wherein, embedded processing equipment is also
Determine whether from resting state, wake up management platform up based on the vehicle fleet size in motor pool；
Described management platform also includes:
Static storage device, is used for prestoring vehicle upper limit gray threshold and vehicle lower limit gray scale threshold
Value, described vehicle upper limit gray threshold and described vehicle lower limit gray threshold are for by the vehicle in image
And background separation, described static storage device has also prestored charge synopsis, and described charge compares
Table with numbering meet grade for index, store each numbering and meet the Parking Fee corresponding to grade
Downward percentage ratio, wherein, in described charge synopsis, meet the highest grade for numbering, corresponding
The downward percentage ratio of Parking Fee is the biggest；
Described parking lot congestion level detection equipment, images subset, parking lot figure including panoramic high-definition
As pretreatment subset and parking lot vehicle identification subset, described panoramic high-definition shooting subset uses
The resolution acquisition parking lot image of 3840 × 2160, described parking lot Image semantic classification subset and institute
State panoramic high-definition shooting subset connect, described parking lot image is carried out successively contrast enhancing, 3 × 3
Pixel window medium filtering and gray processing process, to obtain gray processing parking lot image, described parking lot
Vehicle identification subset is connected respectively with static storage device and parking lot Image semantic classification subset, will
In the image of described gray processing parking lot, gray value is at vehicle upper limit gray threshold and vehicle lower limit gray scale threshold
Pixel identification between value also forms multiple parking lots vehicle pattern, and outputting parking field vehicle pattern
Quantity；
Described subimage acquiring and processing device is positioned at the top in corresponding export house track, including:
Carriageway image gathers subset, shoots corresponding export house track to gather carriageway image；
First goes haze to process subset, is positioned at carriageway image collection subset and carriageway image is pre-
Process between subset, for removing the haze composition in described carriageway image, to obtain sharpening car
Road image；
Carriageway image pretreatment subset, goes with described first haze to process subset and is connected, right
Described sharpening carriageway image is carried out at contrast enhancing, self adaptation recursive filtering and gray processing successively
Reason, to obtain gray processing carriageway image；
Track Car license recognition subset is located in advance with described static storage device and described carriageway image
Reason subset connects, respectively by gray value in described gray processing carriageway image in described vehicle upper limit gray scale
Pixel identification between threshold value and described vehicle lower limit gray threshold also forms track vehicle pattern, based on
The track number-plate number in track vehicle pattern described in OCR recognizer identification；
Described embedded processing equipment is positioned at the machine room of motor pool, including the first timing subset and
First numbering subset, described first timing subset is used for providing instant moment, described first numbering
Subset is connected respectively with described first timing subset and the plurality of subimage acquiring and processing device,
Every every day zero time, remove the vehicle appearance predetermined sequence of a day, start receiving from 1
All tracks number-plate number is ranked up, to form the vehicle appearance predetermined sequence after sorting；
Described master image acquiring and processing device is positioned at the top of EXIT, including:
Outlet image acquisition subset, shoots to gather outlet diagram to EXIT position
Picture；
Second goes haze to process subset, is positioned at outlet image acquisition subset and outlet diagram picture is pre-
Process between subset, for removing the haze composition in described outlet diagram picture, clearly dissolve to obtain
Mouth image；
Outlet Image semantic classification subset, goes with described second haze to process subset and is connected, right
Described sharpening outlet diagram picture is carried out at contrast enhancing, self adaptation recursive filtering and gray processing successively
Reason, to obtain gray processing outlet diagram picture；
Outlet Car license recognition subset is located in advance with described static storage device and described outlet diagram picture
Reason subset connects, respectively by gray value in described gray processing outlet diagram picture in described vehicle upper limit gray scale
Pixel identification between threshold value and described vehicle lower limit gray threshold also forms outlet vehicle pattern, based on
The exit number-plate number in vehicle pattern is exported described in OCR recognizer identification；
Second timing subset, is used for providing the instant moment；
Second numbering subset, with described second timing subset and described outlet Car license recognition
Equipment connects respectively, every every day zero time, enter from the 1 exit number-plate number started receiving
Line number；
Parking Fee calculates subset, sets with described second numbering subset, described static storage
Standby and described embedded processing equipment connects respectively, based on exit number-plate number inquiry exit car plate
Number serial number in vehicle appearance predetermined sequence, by described serial number and described exit license plate number
The numbering of code is mated, and to determine numbering goodness of fit, determines described numbering symbol according to numbering goodness of fit
Close grade, search at described charge synopsis and meet the Parking Fee corresponding to grade with the numbering determined
Downward percentage ratio, based on find lower percentage ratio to corresponding the going out of the number-plate number of described exit
The receivable Parking Fee of mouth vehicle is lowered, to obtain receivable Parking Fee, wherein, and described sequence
Number more mate with the numbering of the described exit number-plate number, it is determined that numbering goodness of fit the highest, determine
Numbering meet the highest grade；
Wherein, described first haze process subset is gone to include:
First haze concentration detecting unit, is positioned in air, for the corresponding export house of detection in real time
The haze concentration of position, track, and determine that haze removes intensity, described haze according to haze concentration
Remove intensity value between 0 to 1；
First overall air light value acquiring unit, gather with described carriageway image subset be connected with
Obtain described carriageway image, calculate the gray value of each pixel in described carriageway image, by gray value
The gray value of big pixel is as overall air light value；
First atmospheric scattering light value acquiring unit, gathers subset and described with described carriageway image
First haze concentration detecting unit connects respectively, each pixel to described carriageway image, extracts it
R, G, B tri-in Color Channel pixel value minima as target pixel value, use the height keeping edge
Described target pixel value is filtered processing to obtain filtered target pixel by this smoothing filter EPGF
Value, deducts filtered target pixel value to obtain object pixel difference by target pixel value, use EPGF
It is filtered object pixel difference processing to obtain filtered target pixel value difference, by filtered target pixel
Value deducts filtered target pixel value difference and removes reference value to obtain haze, haze is removed intensity and is multiplied by mist
Haze is removed reference value and is removed threshold value to obtain haze, takes haze and removes in threshold value and target pixel value
Little value as comparison reference, takes big as each pixel of the maximum in comparison reference and 0
Gas scattering light value；
First medium transfer rate acquiring unit, with described first overall air light value acquiring unit and
Described first atmospheric scattering light value acquiring unit connects, respectively by the atmospheric scattering light value of each pixel
Divided by overall air light value to obtain except value, deduct described except value is to obtain Jie of each pixel by 1
Matter transfer rate；
First sharpening image acquisition unit, with described carriageway image gather subset, described the
One overall air light value acquiring unit and described first medium transfer rate acquiring unit connect, respectively by 1
Deduct the medium transmission rate of each pixel to obtain the first difference, described first difference is multiplied by entirety
The pixel value of each pixel in described carriageway image, to obtain product value, is deducted described by air light value
Product value to obtain the second difference, by described second difference divided by each pixel medium transmission rate with
Obtain the sharpening pixel value of each pixel, the pixel value bag of each pixel in described carriageway image
Include the R of each pixel in described carriageway image, G, B tri-Color Channel pixel value, correspondingly,
The sharpening pixel value of each pixel obtained includes the R of each pixel, and G, B tri-colors are logical
Road sharpening pixel value, the sharpening pixel value of all pixels forms described sharpening carriageway image；
Wherein, described second haze process subset is gone to include:
Second haze concentration detecting unit, is positioned in air, detects EXIT in real time
The haze concentration of position, and determine that intensity removed by haze according to haze concentration, intensity removed by described haze
Value is between 0 to 1；
Second overall air light value acquiring unit, be connected with described outlet image acquisition subset with
Obtain described outlet diagram picture, calculate the gray value of each pixel in described outlet diagram picture, by gray value
The gray value of big pixel is as overall air light value；
Second air scattered light value acquiring unit, with described outlet image acquisition subset and described
Second haze concentration detecting unit connects respectively, each pixel to described outlet diagram picture, extracts it
R, G, B tri-in Color Channel pixel value minima as target pixel value, use the height keeping edge
Described target pixel value is filtered processing to obtain filtered target pixel by this smoothing filter EPGF
Value, deducts filtered target pixel value to obtain object pixel difference by target pixel value, use EPGF
It is filtered object pixel difference processing to obtain filtered target pixel value difference, by filtered target pixel
Value deducts filtered target pixel value difference and removes reference value to obtain haze, haze is removed intensity and is multiplied by mist
Haze is removed reference value and is removed threshold value to obtain haze, takes haze and removes in threshold value and target pixel value
Little value as comparison reference, takes big as each pixel of the maximum in comparison reference and 0
Gas scattering light value；
Second medium transfer rate acquiring unit, with described second overall air light value acquiring unit and
Described second air scattered light value acquiring unit connects, respectively by the atmospheric scattering light value of each pixel
Divided by overall air light value to obtain except value, deduct described except value is to obtain Jie of each pixel by 1
Matter transfer rate；
Second sharpening image acquisition unit, with described outlet image acquisition subset, described
Two overall air light value acquiring units and described second medium transfer rate acquiring unit connect, respectively by 1
Deduct the medium transmission rate of each pixel to obtain the first difference, described first difference is multiplied by entirety
The pixel value of each pixel in described outlet diagram picture, to obtain product value, is deducted described by air light value
Product value to obtain the second difference, by described second difference divided by each pixel medium transmission rate with
Obtain the sharpening pixel value of each pixel, the pixel value bag of each pixel in described outlet diagram picture
Include the R of each pixel in described outlet diagram picture, G, B tri-Color Channel pixel value, correspondingly,
The sharpening pixel value of each pixel obtained includes the R of each pixel, and G, B tri-colors are logical
Road sharpening pixel value, the sharpening pixel value of all pixels forms described sharpening outlet diagram picture；
Wherein, the distance phase that the plurality of subimage acquiring and processing device exports to described motor pool
Deng；
Described embedded processing equipment is big in the quantity of described parking lot congestion level detection equipment output
When equal to predetermined number threshold value, described management platform is waken up up from resting state；
Described embedded processing equipment is little in the quantity of described parking lot congestion level detection equipment output
When predetermined number threshold value, described management platform is entered resting state；
Described predetermined number threshold value is pre-stored in described static storage device；
Described embedded processing equipment is ARM11 processing equipment.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201510532857.2A CN105118305B (en) | 2015-04-16 | 2015-04-16 | Motor pool outlet vehicle management platform |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510532857.2A CN105118305B (en) | 2015-04-16 | 2015-04-16 | Motor pool outlet vehicle management platform |
| CN201510178865.1A CN104794906B (en) | 2015-04-16 | 2015-04-16 | Motor pool outlet vehicle management platform |
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| CN201510178865.1A Division CN104794906B (en) | 2015-04-16 | 2015-04-16 | Motor pool outlet vehicle management platform |
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| CN201510532857.2A Expired - Fee Related CN105118305B (en) | 2015-04-16 | 2015-04-16 | Motor pool outlet vehicle management platform |
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| CN105974847B (en) * | 2016-06-27 | 2018-10-09 | 上海启裔昌物联网科技有限公司 | Temperature Monitoring in Cold Chain system based on remote management |
| TWI618035B (en) * | 2016-07-20 | 2018-03-11 | 大日開發有限公司 | Registering method, system and navigation method, system for vehicle parking location |
| CN106971166A (en) * | 2017-03-29 | 2017-07-21 | 纵目科技（上海）股份有限公司 | The image pre-processing method and system of parking stall detection |
| CN106991814B (en) * | 2017-05-12 | 2020-01-07 | 江苏智通交通科技有限公司 | Comprehensive parking lot exit queuing management control method and system |
| CN106991836A (en) * | 2017-06-06 | 2017-07-28 | 深圳市乃斯网络科技有限公司 | Recommend method and system in EXIT position |
| CN109035446B (en) * | 2018-07-04 | 2020-09-15 | 安徽省徽腾智能交通科技有限公司泗县分公司 | Automatic charging system for parking lot |
| CN109300302B (en) * | 2018-11-26 | 2024-02-27 | 江汉大学 | Queuing method and device applied to vehicle entrance and electronic equipment |
| CN110992707A (en) * | 2019-12-25 | 2020-04-10 | 深圳人人停技术有限公司 | Vehicle parking management method, system and computer readable storage medium |
| CN113299115B (en) * | 2021-07-27 | 2021-10-01 | 成都宜泊信息科技有限公司 | Multi-channel parking lot management method and system, storage medium and electronic equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| AU2013293034B2 (en) * | 2012-07-19 | 2017-06-29 | Esmart 21 Pty Ltd | An automated vehicle parking management system |
| CN203204837U (en) * | 2013-01-07 | 2013-09-18 | 深圳市金溢科技有限公司 | Lane controller and intelligent parking lot management system |
| CN103914898B (en) * | 2013-01-08 | 2016-11-02 | 新谊整合科技股份有限公司 | Vehicles while passing enters control system and method for control |
| CN103927902B (en) * | 2014-04-30 | 2016-03-09 | 西安科技大学 | A kind of medium and small parking lot intelligent vehicle guidance system and bootstrap technique |
| CN104282176B (en) * | 2014-10-29 | 2017-10-27 | 合肥指南针电子科技有限责任公司 | A kind of intelligent residential district vehicle and pedestrains safety management method and system |
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| CN104794906B (en) | 2016-05-18 |
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