CN109584604A - A kind of the wisdom lamp stand and method of service area detection parking stall density - Google Patents
A kind of the wisdom lamp stand and method of service area detection parking stall density Download PDFInfo
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- CN109584604A CN109584604A CN201811371135.3A CN201811371135A CN109584604A CN 109584604 A CN109584604 A CN 109584604A CN 201811371135 A CN201811371135 A CN 201811371135A CN 109584604 A CN109584604 A CN 109584604A
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- parking stall
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
- G08G1/141—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces
- G08G1/142—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces external to the vehicles
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
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- General Physics & Mathematics (AREA)
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Abstract
The invention discloses the wisdom lamp stands and method of a kind of service area detection parking stall density, wisdom lamp stand includes lamp stand and the monitoring device that is arranged on lamp stand, monitoring device includes high-definition camera, video data acquiring device, intelligent controlling device and display, and intelligent controlling device includes picture feature recognition unit and interactive unit.The present invention is by combining street lamp and the monitoring of service area parking stall, in the case where not increasing service area equipment, original service area street lamp is transformed, realize the monitoring of service area monitoring parking stall density, improve Expressway Service volume of traffic pressure, recreating facility is provided for more driver and passenger, is had a good application prospect.
Description
Technical field
The present invention relates to parking stall density detection techniques, and in particular to a kind of wisdom lamp of service area detection parking stall density
Bar and method.
Background technique
Due to the continuous surge and the first preplanning of Parking Area Service Area of Expressway of vehicle fleet size, freeway service
Parking stall day is becoming tight in area, and easily get congestion phenomenon.
Existing solution is that license plate scanning means is arranged in service area entrance mostly, according to standing car in service area
Quantity judge parking stall service condition.Then, since part driver arbitrarily parks cars, there is a situation where the free time in parking stall
Under, regional area gets congestion, and the prior art cannot achieve supervision and coordination.
Summary of the invention
The purpose of the present invention is to provide the wisdom lamp stands and method of a kind of service area detection parking stall density.
Realize the technical solution of the object of the invention are as follows: a kind of wisdom lamp stand of service area detection parking stall density, including lamp
Bar and the monitoring device being set on lamp stand, the monitoring device include high-definition camera, video data acquiring device, intelligence control
Device and display processed, intelligent controlling device include picture feature recognition unit and interactive unit；
Parking stall scene information is uploaded to intelligence by video data acquiring device for shooting parking stall scene by high-definition camera
It can control device；Parking stall scene information is set as picture sample by intelligent controlling device, and picture feature recognition unit identifies picture sample
This characteristic parameter simultaneously establishes parameter model set, is screened the vehicle in the scene information of parking stall by parameter model set
Obtain vehicle-state；Vehicle-state and service area parking stall map are compared, marks unappropriated parking stall for the free time, marks occupied
Parking stall is occupancy；Idle and occupancy is marked using two kinds of colors and generates heating power distribution map and is existed by interactive unit
It is shown in display.
A kind of method of service area detection parking stall density, comprising the following steps:
S1, parking stall scene is shot by the high-definition camera fixed angle of each wisdom lamp stand；
S2, parking stall scene information is uploaded to by intelligent controller by video data acquiring device；
S3, parking stall scene information is set as by picture sample by intelligent controller, picture feature recognition unit identifies picture
The characteristic parameter of sample simultaneously establishes parameter model set；
S4, intelligent controller is initialized by parameter model set；
S5, it screens the vehicle in the scene information of parking stall to obtain vehicle-state by parameter model set；
S6, comparison vehicle-state and service area parking stall map, mark unappropriated parking stall for the free time；It marks occupied
Parking stall be occupy；
S7, generation heating power distribution map is marked using two kinds of colors to idle and occupancy and is being shown by interactive unit
It is shown in device.
Compared with prior art, the invention has the benefit that (1) present invention is by monitoring street lamp and service area parking stall
It combines, in the case where not increasing service area equipment, original service area street lamp is transformed, not only reduced costs but also reduced
Equipment occupies service zone position；(2) method for detecting parking stall density by service area establishes parameter model set sieve
Vehicle-state is selected, heating power distribution map is generated and is shown in the display by interactive unit, it is right to show that service area detects density
Driver and passenger provide convenient and produce positive effect, to solve to block up caused by Expressway Service vehicle is arbitrarily parked
Plug；(3) present invention can reconcile and improve Expressway Service volume of traffic pressure, provide recreating facility for more driver and passenger
With offer convenience, have a good application prospect.
Detailed description of the invention
Fig. 1 is the method flow diagram of present invention detection parking stall density.
Specific embodiment
A kind of wisdom lamp stand of service area detection parking stall density, including lamp stand and the monitoring device being set on lamp stand,
The monitoring device includes high-definition camera, video data acquiring device, intelligent controlling device and display, intelligent controlling device
Including picture feature recognition unit and interactive unit；
Parking stall scene information is uploaded to intelligence by video data acquiring device for shooting parking stall scene by high-definition camera
It can control device；Parking stall scene information is set as picture sample by intelligent controlling device, and picture feature recognition unit identifies picture sample
This characteristic parameter simultaneously establishes parameter model set, is screened the vehicle in the scene information of parking stall by parameter model set
Obtain vehicle-state；Vehicle-state and service area parking stall map are compared, marks unappropriated parking stall for the free time, marks occupied
Parking stall is occupancy；Idle and occupancy is marked using two kinds of colors and generates heating power distribution map and is existed by interactive unit
It is shown in display.
The picture pixels of high-definition camera acquisition are not less than 2,000,000 pixels.
As shown in Figure 1, a kind of method of service area detection parking stall density, comprising the following steps:
S1, parking stall scene is shot by the high-definition camera fixed angle of each wisdom lamp stand；
S2, parking stall scene information is uploaded to by intelligent controller, the parking stall scene letter by video data acquiring device
Breath include parking stall white line frame, the image recording stopped；
S3, parking stall scene information is set as by picture sample by intelligent controller；Picture feature recognition unit identifies picture
The characteristic parameter of sample simultaneously establishes parameter model set；The characteristic parameter of the picture sample include color characteristic, textural characteristics,
Shape feature, the textural characteristics are the mark that can be identified for that vehicle on vehicle；Color characteristic, textural characteristics, shape feature
Weight is respectively 90%, 5%, 5%.The step of establishing parameter model set is as follows:
S31, target scene photograph is obtained by the video camera of wisdom lamp stand, while by the RGB data of photo, gradation data
Classification storage；
S32, the image information of acquisition is filtered, the processing of image enhancement, image rotation, specifically:
(1) pixel filter is carried out using median filtering method, it is non-linear due to median filtering method, it needs to determine one first
Odd pixel window L, wherein L=2N+1, N are positive integer；
It is located at some moment, the sample of signal in window is x (i-N) ..., and x (i) ..., x (i+N), wherein x (i) is
Positioned at the sample of signal value of window center；After being arranged by sequence from small to large this L sample of signal value, intermediate value is defined as
The output valve of median filtering；In image algorithm processing, using two-dimentional median calculation, if f1(x, y), g1(x, y) is respectively original
Image after image and processing, W is the pixel region of two dimension pattern plate, usually 3*3 or 5*5, then two dimension median filter exports are as follows:
g1(x, y)=med { f1(x-k,y-l),(k,l∈W)}
(2) enhancing processing is carried out to image, is handled using spatial domain mode, defined:
f2(x, y) is input picture, g2(x, y) is enhanced image, and T is defined on the neighborhood of (x, y), and to f and progress
Enhancing operation, it may be assumed that g2(x, y)=T { f2{x,y}}
Histogram treatment, the balanced discrete transform formula of histogram are carried out to image are as follows:
Wherein, N is the sum of all pixels of piece image, NkFor gray level rkThe frequency of appearance, k are the sequence of gray level, T
(rk) it is transforming function transformation function, meet:
(a)T(rk) in 0≤r of sectionkIt is monodrome and monotone decreasing in≤1；
(b) as 0≤rkWhen≤1,0≤T (rk)≤1；
Therefore, the greyscale transformation value of each pixel after equilibrium can be acquired according to the statistics with histogram amount of original image；
Greyscale transformation: the gray value f of each pixel3(x,y){a≤f3(x, y)≤b } according to
g3(x,y){A≤g3(x, y)≤B } tonal gradation transformation:
Wherein [A, B] is entire tonal range, and [a, b] is the tonal range of the picture distribution of processing；
S33, the feature of needs is extracted, the information of vehicle is mainly extracted in the method, using Gabor wavelet
Exchanged form carries out multi-channel information resolution process:
Wherein σx,σyStandard deviation respectively relative to x-axis and y-axis；
U, V are the components of filter radial center two axis of frequency:
Gabor function from substantially for be the wave function limited by Gauss function window；It is different by defining
Gabor functional core, so that it may obtain one group of Gabor filter；It include one group with the process that Gabor filter carries out feature extraction
The different frequency of each spatial feature and the filter group in direction can be covered；
Then the feature of Gabor processing is further processed, is reapplied in processes such as identification, detections.
S34, the feature that vehicle is carried out using genetic algorithm identify that algorithm uses the classification performance of SVM as fitness
Solution is assessed, valuation functions are as follows:
Fitness=MarValue × 10d+NoErrRate
Wherein NoErrRate is the opposite error rate of individual, and d is constant choosing, and taking principle is the quantity according to training sample
Depending on；MarValue is the Margin of SVM classifier, and ErrRate is the false segmentation rate of SVM classifier training sample.
S4, intelligent controller is initialized by parameter model set；
S5, it screens the vehicle in the scene information of parking stall to obtain vehicle-state by parameter model set；The vehicle
State includes driving into, stop and being driven out to, and the vehicle-state judgement includes the following steps:
S51, sample time is set by intelligent controller；
S52, identify that the picture sample in sample time obtains the vehicle in sample time by picture feature recognition unit
Picture；
S53, vehicle position information is obtained according to vehicle pictures and service area parking stall map by intelligent controller；Software is flat
The parking stall grid of platform typing current service area parking area judges whether there is vehicle according to the range of stop line and occupies, with vehicle
Picture match is to identify the parking stall position that vehicle is stopped.
S54, vehicle position information is calculated by track of vehicle by intelligent controller, to judge vehicle-state；Wherein
The method for calculating track of vehicle are as follows: moving area detection is carried out based on background subtraction；Based on deep learning to moving area into
Pedestrian's vehicle target detection；Target is tracked；Based on target detection and tracking result, vehicle count and congestion judgement are carried out,
Congestion judgement is that the movement speed that is averaged according to target in setting time is judged.
S6, vehicle-state and service area parking stall map are compared by intelligent controller, marks unappropriated parking stall for sky
It is not busy；Occupied parking stall is to occupy to label；
S7, generation heating power distribution map is marked using two kinds of colors to idle and occupancy by display and passes through interaction
Unit is shown in the display；Congestion regions are shown on wisdom lamp stand screen by thermodynamic chart.
Further, the vehicle in the scene information of parking stall is screened by parameter model set in S5 to obtain vehicle shape
State；Specifically: by cross-validation method, vehicle to be determined and background training sample set are randomly divided into N equal portions；
1) then wherein N-1 parts are classified to remaining portion as new training sample set training classifier.It can
First background or one side of vehicle to be immobilized.
2) N number of test result is obtained after all testing every portion with N-1 parts of others.By the best N-1 parts of work of classification results
For this training sample set, portion is excluded.
If 3) the remaining N-1 parts assessment threshold value for being less than setting, repeatedly step 1), 2), vehicle and background are made together
The operation of sample.
The content of present invention is described in detail below with reference to embodiment.
Embodiment
The wisdom lamp stand of the present embodiment is mounted in service area, quantity be it is multiple, each wisdom lamp stand include be set to lamp stand
On monitoring device, monitoring device includes high-definition camera, video data acquiring device, intelligent controlling device and display, intelligence
Can control device includes picture feature recognition unit and interactive unit.High-definition camera passes through video for shooting parking stall scene
Parking stall scene information is uploaded to intelligent controlling device by data acquisition device；Parking stall scene information is set as figure by intelligent controlling device
Piece sample, the characteristic parameter of picture feature recognition unit identification picture sample simultaneously establish parameter model set, pass through parameter model
Set screens the vehicle in the scene information of parking stall to obtain vehicle-state；Vehicle-state and service area parking stall map are compared,
Mark unappropriated parking stall for the free time, occupied parking stall is to occupy to label；To it is idle and occupy using two kinds of colors into
Line flag generates heating power distribution map and is shown in the display by interactive unit.The picture pixels of high-definition camera acquisition are not low
In 2,000,000 pixels.
As shown in Figure 1, a kind of method of service area detection parking stall density, which comprises the following steps:
S1, parking stall scene is shot by the high-definition camera fixed angle of each wisdom lamp stand；
S2, parking stall scene information is uploaded to by intelligent controller by video data acquiring device；
S3, parking stall scene information is set as by picture sample by intelligent controller；
S4, the characteristic parameter of picture sample is identified by picture feature recognition unit and establishes parameter model set；It is described
The characteristic parameter of picture sample includes color characteristic, textural characteristics and shape feature；Color characteristic, textural characteristics, shape feature
Weight be respectively 90%, 5%, 5%.
S5, intelligent controller is initialized by parameter model set；
S6, it screens the vehicle in the scene information of parking stall to obtain vehicle-state by parameter model set；Vehicle shape
State includes driving into, stop and being driven out to；Vehicle-state judgement includes the following steps:
Sample time is set by intelligent controller；
Identify that the picture sample in sample time obtains the vehicle pictures in sample time by picture feature recognition unit；
Vehicle position information is obtained according to vehicle pictures and service area parking stall map by intelligent controller；
Vehicle position information is calculated into track of vehicle by intelligent controller, to judge vehicle-state.
S7, vehicle-state and service area parking stall map are compared by intelligent controller, marks unappropriated parking stall for sky
It is not busy；Occupied parking stall is to occupy to label；
S8, generation heating power distribution map is marked using two kinds of colors to idle and occupancy by display and passes through interaction
Unit is shown in the display.
Claims (9)
1. a kind of wisdom lamp stand of service area detection parking stall density, which is characterized in that including lamp stand and be set on lamp stand
Monitoring device, the monitoring device include high-definition camera, video data acquiring device, intelligent controlling device and display, intelligence
Can control device includes picture feature recognition unit and interactive unit；
Parking stall scene information is uploaded to intelligent control by video data acquiring device for shooting parking stall scene by high-definition camera
Device processed；Parking stall scene information is set as picture sample by intelligent controlling device, and picture feature recognition unit identifies picture sample
Characteristic parameter simultaneously establishes parameter model set, screens to obtain by the vehicle in the scene information of parking stall by parameter model set
Vehicle-state；Vehicle-state and service area parking stall map are compared, marks unappropriated parking stall for the free time, marks occupied
Parking stall is to occupy；Idle and occupancy is marked using two kinds of colors and generates heating power distribution map and is being shown by interactive unit
It is shown in device.
2. the wisdom lamp stand of service area detection parking stall density according to claim 1, which is characterized in that high-definition camera
The picture pixels of acquisition are not less than 2,000,000 pixels.
3. a kind of method of the service area detection parking stall density based on wisdom lamp stand described in claim 1, which is characterized in that packet
Include following steps:
S1, parking stall scene is shot by the high-definition camera fixed angle of each wisdom lamp stand；
S2, parking stall scene information is uploaded to by intelligent controller by video data acquiring device；
S3, parking stall scene information is set as by picture sample by intelligent controller, picture feature recognition unit identifies picture sample
Characteristic parameter and establish parameter model set；
S4, intelligent controller is initialized by parameter model set；
S5, it screens the vehicle in the scene information of parking stall to obtain vehicle-state by parameter model set；
S6, comparison vehicle-state and service area parking stall map, mark unappropriated parking stall for the free time；Mark occupied vehicle
Position is occupancy；
S7, generation heating power distribution map is marked using two kinds of colors to idle and occupancy and passes through interactive unit in the display
It shows.
4. the method for service area detection parking stall density according to claim 3, which is characterized in that the picture sample
Characteristic parameter includes color characteristic, textural characteristics and shape feature.
5. the method for service area detection parking stall density according to claim 4, which is characterized in that color characteristic, texture
Feature, the weight of shape feature are respectively 90%, 5%, 5%.
6. the method for detecting parking stall density according to service area described in claim 3,4 or 5, which is characterized in that established in S3
The step of parameter model set, is as follows:
S31, target scene photograph is obtained by the video camera of wisdom lamp stand, while the RGB data of photo, gradation data being classified
Storage；
S32, the image information of acquisition is filtered, the processing of image enhancement, image rotation；
S33, vehicle characteristics are extracted, multi-channel information resolution process is carried out using Gabor wavelet exchanged form；
S34, the feature that vehicle is carried out using genetic algorithm are identified, the classification performance of SVM is used to comment as fitness solution
Estimate.
7. the method for service area detection parking stall density according to claim 3, which is characterized in that high-definition camera acquisition
Picture pixels be not less than 2,000,000 pixels.
8. the method for service area detection parking stall density according to claim 3, which is characterized in that vehicle shape described in S5
State includes driving into, stop and being driven out to.
9. the method for service area detection parking stall density according to claim 8, which is characterized in that vehicle-state judgement side
Method are as follows:
S51, sample time is set by intelligent controller；
S52, identify that the picture sample in sample time obtains the vehicle pictures in sample time by picture feature recognition unit；
S53, vehicle position information is obtained according to vehicle pictures and service area parking stall map by intelligent controller；Typing currently takes
Be engaged in area's parking area parking stall grid, according to the range of stop line judge whether there is vehicle occupy, match with vehicle pictures thus
Identify the parking stall position that vehicle is stopped；
S54, vehicle position information is calculated by track of vehicle by intelligent controller, to judge vehicle-state.
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Application publication date: 20190405 |
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