CN109063675A - Vehicle density calculation method, system, terminal and computer readable storage medium - Google Patents
Vehicle density calculation method, system, terminal and computer readable storage medium Download PDFInfo
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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
- G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
- G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30232—Surveillance
Abstract
The present invention is suitable for Traffic monitoring field, provides a kind of vehicle density calculation method, comprising: carries out binary conversion treatment to the detection image of detection zone acquisition, obtains bianry image；Using the operational objective in bianry image described in pixels statistics method statistic, the vehicle density of the detection zone is obtained；According to the vehicle density of the detection zone, the vehicle density state of the detection zone is determined using fuzzy vehicle density.The embodiment of the present invention measures vehicle density state using fuzzy vehicle density, solves the problems, such as not determining the vehicle density situation in detection section in the prior art.
Description
Technical field
The invention belongs to Traffic monitoring field more particularly to a kind of vehicle density calculation method, system, terminal and computers
Readable storage medium storing program for executing.
Background technique
In recent years, the development and its vigorous actual demand of Traffic Surveillance Video technology have attracted a large amount of research both at home and abroad
Person in video accident detection and related algorithm expand further investigation.
Nilakorn Seenouvong et al. proposes vehicle count algorithm based on computer vision, counting it is accurate
Degree is high, improves the order of accuarcy to vehicle flowrate monitoring；Nowosielski, A et al. are based on Camshift algorithm, propose one
Kind new track of vehicle algorithm for pattern recognition, can the behaviors such as parking violation to vehicle or illegal turning accurately analyze identification；
Daw-Tung Lin et al. then proposes Superpixel track algorithm and track of vehicle analytical technology, and is applied to crossroad
Traffic monitoring；Sang Hai-feng et al. propose it is a kind of by detection and tracking track of vehicle judge vehicle whether drive in the wrong direction with
The system of hypervelocity；Li et al. people uses the method for extracting characteristic point to test and analyze traffic abnormity, is promoted in accuracy；
Hanlin Tan then proposes a kind of Outlier Detection Algorithm based on sparse optical flow method, can detecte drive in the wrong direction and jaywalk equal traffic
Abnormal conditions；Li Ning et al. then proposes a kind of algorithm for integrating a variety of traffic informations and being analyzed abnormal conditions, improves
The applicability of network analysis；Ahmed Tageldin et al. propose one kind in specific time on road target spacing from come
Judge the method for traffic conditions, and with the collision problem of pedestrian and vehicle under this traffic behavior to solve height congestion；Yang Zhi
It is brave et al. to pass through fusion fuzzy logic and improved increment comparison algorithm, establish a kind of highway friendship based on fuzzy logic
Interpreter's part detection model, the model carry out event analysis by extracting car speed and information of vehicle flowrate, but due to traffic shape
Condition is sufficiently complex, and the premise of the model inspection has certain limitation.Siyuan Liu et al. people then proposes to extract city using GPS
The track data of taxi analyzes taxi movement speed to detect urban road congestion situation.
Although also substantially increasing testing cost, practicability is not however, the abnormality detection precision based on GPS positioning is high
Foot.Conventionally, as the track moment of moving target is in variable condition and without fixed run duration, can not determine
Detect the vehicle density situation in section.
Summary of the invention
Technical problem to be solved by the present invention lies in provide a kind of vehicle density calculation method, system, terminal and calculating
Machine readable storage medium storing program for executing, it is intended to solve the prior art since the track moment of moving target is in variable condition and without fixed fortune
The problem of moving the time, can not determining the vehicle density situation in detection section.
The invention is realized in this way a kind of vehicle density calculation method, comprising:
Binary conversion treatment is carried out to the detection image of detection zone acquisition, obtains bianry image；
Using the operational objective in bianry image described in pixels statistics method statistic, the wagon flow for obtaining the detection zone is close
Degree；
According to the vehicle density of the detection zone, determine that the wagon flow of the detection zone is close using fuzzy vehicle density
Degree state.
Further, the detection image to detection zone acquisition carries out binary conversion treatment, and obtaining bianry image includes:
Obtain the detection image of the detection zone；
Mixed Gaussian background modeling is carried out to the foreground image of the detection image, obtains modeled images；
Binary conversion treatment is carried out to the modeled images, obtains the bianry image.
Further, the detection image for obtaining the detection zone includes:
The trapezoid area for detection is determined according to lane shape, using the trapezoid area as the detection zone；
The detection video of the detection zone is acquired, each frame detection image in the detection video is obtained.
Further, the operational objective using in bianry image described in pixels statistics method statistic, obtains the inspection
Survey region vehicle density include:
Any pixel point P in the bianry imageiPixel value be Xi, Xi=0 or Xi=1, form the moving target
Pixel region XiTotal pixel value of=1, the detection zone S are Spix, vehicle density ρpix, then:
Wherein XiFor the pixel value in the detection zone S.
Further, the vehicle density according to the detection zone, the inspection is determined using fuzzy vehicle density
Survey region vehicle density state include:
According to the vehicle density of the detection zone, using Gaussian distribution model and 3 σ principles, using fuzzy vehicle density
Determine the vehicle density state；
S is used respectively, and U, V indicate dilute, normal, close three kinds of states of traffic density state, by vehicle density ρpixIt obscures and is
{ S, U, V }, the vehicle density ρpixSubordinating degree function include:
With ρ1、ρ2Indicate the critical value between S and U, ρ3、ρ4Indicate the critical value between U and V；
If fS(ρpix) bigger, then vehicle density ρpixThe degree for belonging to S is bigger, works as ρpix∈(0,ρ1) when, determine that wagon flow is close
Spend ρpixFor S；Work as ρpix∈(ρ1,ρ2) when, determine vehicle density ρpixBetween S and U；
If fU(ρpix) bigger, then vehicle density ρpixThe degree for belonging to U is bigger, works as ρpix∈(ρ1,ρ2) when, determine that wagon flow is close
Spend ρpixBetween S and U；Work as ρpix∈(ρ2,ρ3) when, determine vehicle density ρpixFor U；Work as ρpix∈(ρ3,ρ4) when, determine vehicle
Current density ρpixBetween U and V；
If fV(ρpix) bigger, then vehicle density ρpixThe degree for belonging to V is bigger, works as ρpix∈(ρ3,ρ4) when, determine that wagon flow is close
Spend ρpixBetween U and V；Work as ρpix∈(ρ4, 1) when, vehicle density ρpixFor V；Work as fV(ρpixWhen) > 0, vehicle density ρ is determinedpix
∈V。
The embodiment of the invention also provides a kind of vehicle density computing systems, comprising:
Processing unit, the detection image for acquiring to detection zone carry out binary conversion treatment, obtain bianry image；
Statistic unit, for obtaining the inspection using the operational objective in bianry image described in pixels statistics method statistic
Survey the vehicle density in region；
Determination unit determines the inspection using fuzzy vehicle density for the vehicle density according to the detection zone
Survey the vehicle density state in region.
Further, the statistic unit is specifically used for:
Any pixel point P in the bianry imageiPixel value be Xi, Xi=0 or Xi=1, form the moving target
Pixel region XiTotal pixel value of=1, the detection zone S are Spix, vehicle density ρpix, then:
Wherein XiFor the pixel value in the detection zone S.
Further, the determination unit is specifically used for:
According to the vehicle density of the detection zone, using Gaussian distribution model and 3 σ principles, using fuzzy vehicle density
Determine the vehicle density state；
S is used respectively, and U, V indicate dilute, normal, close three kinds of states of traffic density state, by vehicle density ρpixIt obscures and is
{ S, U, V }, the vehicle density ρpixSubordinating degree function include:
With ρ1、ρ2Indicate the critical value between S and U, ρ3、ρ4Indicate the critical value between U and V；
If fS(ρpix) bigger, then vehicle density ρpixThe degree for belonging to S is bigger, works as ρpix∈(0,ρ1) when, determine that wagon flow is close
Spend ρpixFor S；Work as ρpix∈(ρ1,ρ2) when, determine vehicle density ρpixBetween S and U；
If fU(ρpix) bigger, then vehicle density ρpixThe degree for belonging to U is bigger, works as ρpix∈(ρ1,ρ2) when, determine that wagon flow is close
Spend ρpixBetween S and U；Work as ρpix∈(ρ2,ρ3) when, determine vehicle density ρpixFor U；Work as ρpix∈(ρ3,ρ4) when, determine vehicle
Current density ρpixBetween U and V；
If fV(ρpix) bigger, then vehicle density ρpixThe degree for belonging to V is bigger, works as ρpix∈(ρ3,ρ4) when, determine that wagon flow is close
Spend ρpixBetween U and V；Work as ρpix∈(ρ4, 1) when, vehicle density ρpixFor V；Work as fV(ρpixWhen) > 0, vehicle density ρ is determinedpix
∈V。
The embodiment of the invention also provides a kind of terminal, including memory, processor and be stored on the memory and
The computer program run on the processor when the processor executes the computer program, is realized as described above
Vehicle density calculate in each step.
The embodiment of the invention also provides a kind of readable storage medium storing program for executing, are stored thereon with computer program, the computer
When program is executed by processor, each step in vehicle density calculation method as described above is realized.
Compared with prior art, the present invention beneficial effect is: the embodiment of the present invention passes through the inspection that acquires to detection zone
Altimetric image carries out binary conversion treatment, obtains bianry image, using the operational objective in the pixels statistics method statistic bianry image,
The vehicle density of the detection zone is obtained, according to the vehicle density of the detection zone, the inspection is determined using fuzzy vehicle density
Survey the vehicle density state in region.The embodiment of the present invention measures vehicle density state using using fuzzy vehicle density, solves
The problem of in the prior art can not determining the vehicle density situation in detection section.
Detailed description of the invention
Fig. 1 is the flow chart of vehicle density calculation method provided in an embodiment of the present invention；
Fig. 2 is the traffic scene image schematic diagram of detection zone provided in an embodiment of the present invention；
Fig. 3 is the subordinating degree function of fuzzy vehicle flowrate provided in an embodiment of the present invention；
Fig. 4 is the structural schematic diagram of vehicle density computing system provided in an embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
Fig. 1 shows a kind of vehicle density calculation method provided in an embodiment of the present invention, comprising:
S101 carries out binary conversion treatment to the detection image of detection zone acquisition, obtains bianry image；
S102 obtains the detection zone using the operational objective in bianry image described in pixels statistics method statistic
Vehicle density；
S103 determines the detection zone using fuzzy vehicle density according to the vehicle density of the detection zone
Vehicle density state.
The embodiment of the present invention is further illustrated below:
Traffic scene is often complicated various, often there is the region unrelated with traffic, such as roadside in a traffic scene
Trees, blue sky etc., in order to reduce influence of these regions to traffic information parameter, while improving real-time, the present invention is real
It applies example and a trapezoid area delimited for detecting operation according to lane shape in traffic scene, which is denoted as S, such as
Shadow region in Fig. 2 is detection zone S, and the upper left corner of traffic scene is set as coordinate origin O.
A) the vehicle density detection algorithm based on pixels statistics:
Traffic current density in order to obtain, embodiment provides a kind of vehicle density inspection based on pixels statistics when of the invention
Method of determining and calculating, the vehicle density detection algorithm carry out binary conversion treatment to using the foreground image after mixed Gaussian background modeling, obtain
To bianry image.Specifically, foreground image is the images such as vehicle, the personage in detection image, and background image is in detection image
Static background carries out binary conversion treatment to prospect after background modeling, obtains the gray level image for only focusing on vehicle, pedestrian, should
Gray level image is bianry image, any pixel point P in the bianry imageiPixel value be Xi, Xi=0 or Xi=1.Composition fortune
The pixel region X of moving-targeti=1.If total pixel value of detection zone S is spix, vehicle density ρpix, then pass through following formula
Obtain vehicle density ρpix。
Wherein XiFor the pixel value in S.
B) vehicle density is obscured
Based on above-mentioned, according to the vehicle density ρ of available k-th of the unit interval of formula (1)pix.Benefit of the embodiment of the present invention
With Gaussian distribution model and 3 σ principles, vehicle density state is measured using fuzzy vehicle density, uses S respectively, and U, V indicate traffic
Dilute, normal, close three kinds of states of density state, by vehicle density ρpixIt obscures as { S, U, V }.Its subordinating degree function such as (2)-
(4), the subordinating degree function figure for obscuring vehicle density is as shown in Figure 3.
If ρ1、ρ2For the critical value between S (dilute) and U (normal), ρ3、ρ4For the critical value between U (normal) and V (close).
By formula (2) and Fig. 3 it can be seen that fSIt is bigger, vehicle density ρ at this timepixThe degree for belonging to S is bigger.Work as ρpix∈(0,ρ1) when, vehicle
Current density ρpixFor S (dilute)；Work as ρpix∈(ρ1,ρ2) when, vehicle density ρpixBetween S (dilute) and U (normal).
By formula (3) and Fig. 3 it can be seen that fUIt is bigger, vehicle density ρ at this timepixThe degree for belonging to U is bigger.Work as ρpix∈(ρ1,
ρ2) when, vehicle density ρpixBetween S (dilute) and U (normal)；Work as ρpix∈(ρ2,ρ3) when, vehicle density ρpixFor U (normal)；
Work as ρpix∈(ρ3,ρ4) when, vehicle density ρpixBetween U (normal) and V (close).
By formula (4) and Fig. 3 it can be seen that fVIt is bigger, vehicle density ρ at this timepixThe degree for belonging to V is bigger.Work as ρpix∈(ρ3,
ρ4) when, vehicle density ρpixBetween U (normal) and V (close)；Work as ρpix∈(ρ4, 1) when, vehicle density ρpixFor V (close).When
fVWhen > 0, there is ρpix∈V。
Fig. 4 shows a kind of vehicle density computing system provided in an embodiment of the present invention, comprising:
Processing unit 401, the detection image for acquiring to detection zone carry out binary conversion treatment, obtain bianry image；
Statistic unit 402, for obtaining described using the operational objective in bianry image described in pixels statistics method statistic
The vehicle density of detection zone；
Determination unit 403 is determined described for the vehicle density according to the detection zone using fuzzy vehicle density
The vehicle density state of detection zone.
Further, processing unit 401 is specifically used for:
Obtain the detection image of the detection zone；
Mixed Gaussian background modeling is carried out to the foreground image of the detection image, obtains modeled images；
Binary conversion treatment is carried out to the modeled images, obtains the bianry image.
Further, processing unit 401 is also used to:
The trapezoid area for detection is determined according to lane shape, using the trapezoid area as the detection zone；
The detection video of the detection zone is acquired, each frame detection image in the detection video is obtained.
Further, statistic unit 402 is specifically used for:
Any pixel point P in the bianry imageiPixel value be Xi, Xi=0 or Xi=1, form the moving target
Pixel region XiTotal pixel value of=1, the detection zone S are Spix, vehicle density ρpix, then:
Wherein XiFor the pixel value in the detection zone S.
Further, it is determined that unit 403 is specifically used for:
According to the vehicle density of the detection zone, using Gaussian distribution model and 3 σ principles, using fuzzy vehicle density
Determine the vehicle density state；
S is used respectively, and U, V indicate dilute, normal, close three kinds of states of traffic density state, by vehicle density ρpixIt obscures and is
{ S, U, V }, the vehicle density ρpixSubordinating degree function include:
With ρ1、ρ2Indicate the critical value between S and U, ρ3、ρ4Indicate the critical value between U and V；
If fS(ρpix) bigger, then vehicle density ρpixThe degree for belonging to S is bigger, works as ρpix∈(0,ρ1) when, determine that wagon flow is close
Spend ρpixFor S；Work as ρpix∈(ρ1,ρ2) when, determine vehicle density ρpixBetween S and U；
If fU(ρpix) bigger, then vehicle density ρpixThe degree for belonging to U is bigger, works as ρpix∈(ρ1,ρ2) when, determine that wagon flow is close
Spend ρpixBetween S and U；Work as ρpix∈(ρ2,ρ3) when, determine vehicle density ρpixFor U；Work as ρpix∈(ρ3,ρ4) when, determine vehicle
Current density ρpixBetween U and V；
If fV(ρpix) bigger, then vehicle density ρpixThe degree for belonging to V is bigger, works as ρpix∈(ρ3,ρ4) when, determine that wagon flow is close
Spend ρpixBetween U and V；Work as ρpix∈(ρ4, 1) when, vehicle density ρpixFor V；Work as fV(ρpixWhen) > 0, vehicle density ρ is determinedpix
∈V。
In several embodiments provided herein, it should be understood that disclosed method and apparatus can pass through it
Its mode is realized.For example, the apparatus embodiments described above are merely exemplary, for example, the division of the module, only
Only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple module or components can be tied
Another device is closed or is desirably integrated into, or some features can be ignored or not executed.Another point, it is shown or discussed
Mutual coupling, direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING or logical of device or module
Letter connection can be electrical property, mechanical or other forms.
The module as illustrated by the separation member may or may not be physically separated, aobvious as module
The component shown may or may not be physical module, it can and it is in one place, or may be distributed over multiple
On network module.Some or all of the modules therein can be selected to realize the mesh of this embodiment scheme according to the actual needs
's.
It, can also be in addition, each functional module in each embodiment of the present invention can integrate in a processing module
It is that modules physically exist alone, can also be integrated in two or more modules in a module.Above-mentioned integrated mould
Block both can take the form of hardware realization, can also be realized in the form of software function module.
If the integrated module is realized in the form of software function module and sells or use as independent product
When, it can store in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially
The all or part of the part that contributes to existing technology or the technical solution can be in the form of software products in other words
It embodies, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can be personal computer, server or the network equipment etc.) executes the complete of each embodiment the method for the present invention
Portion or part steps.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. are various can store journey
The medium of sequence code.
It should be noted that for the various method embodiments described above, describing for simplicity, therefore, it is stated as a series of
Combination of actions, but those skilled in the art should understand that, the present invention is not limited by the sequence of acts described because
According to the present invention, certain steps can use other sequences or carry out simultaneously.Secondly, those skilled in the art should also know
It knows, the embodiments described in the specification are all preferred embodiments, and related actions and modules might not all be this hair
Necessary to bright.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, there is no the portion being described in detail in some embodiment
Point, it may refer to the associated description of other embodiments.
The above are the descriptions to a kind of vehicle density calculation method provided by the present invention and system, for the skill of this field
Art personnel, thought according to an embodiment of the present invention, there will be changes in the specific implementation manner and application range, to sum up,
The contents of this specification are not to be construed as limiting the invention.
Claims (10)
1. a kind of vehicle density calculation method characterized by comprising
Binary conversion treatment is carried out to the detection image of detection zone acquisition, obtains bianry image；
Using the operational objective in bianry image described in pixels statistics method statistic, the vehicle density of the detection zone is obtained；
According to the vehicle density of the detection zone, the vehicle density shape of the detection zone is determined using fuzzy vehicle density
State.
2. vehicle density calculation method as described in claim 1, which is characterized in that the detection figure to detection zone acquisition
As carrying out binary conversion treatment, obtaining bianry image includes:
Obtain the detection image of the detection zone；
Mixed Gaussian background modeling is carried out to the foreground image of the detection image, obtains modeled images；
Binary conversion treatment is carried out to the modeled images, obtains the bianry image.
3. vehicle density calculation method as claimed in claim 2, which is characterized in that the detection for obtaining the detection zone
Image includes:
The trapezoid area for detection is determined according to lane shape, using the trapezoid area as the detection zone；
The detection video of the detection zone is acquired, each frame detection image in the detection video is obtained.
4. vehicle density calculation method as described in claim 1, which is characterized in that described to utilize pixels statistics method statistic institute
The operational objective in bianry image is stated, the vehicle density for obtaining the detection zone includes:
Any pixel point P in the bianry imageiPixel value be Xi, Xi=0 or Xi=1, form the pixel of the moving target
Region XiTotal pixel value of=1, the detection zone S are Spix, vehicle density ρpix, then:
Wherein XiFor the pixel value in the detection zone S.
5. vehicle density calculation method as claimed in claim 4, which is characterized in that the wagon flow according to the detection zone
Density determines that the vehicle density state of the detection zone includes: using fuzzy vehicle density
It is determined using Gaussian distribution model and 3 σ principles using fuzzy vehicle density according to the vehicle density of the detection zone
The vehicle density state；
S is used respectively, and U, V indicate dilute, normal, close three kinds of states of traffic density state, by vehicle density ρpixObscure for S, U,
V }, the vehicle density ρpixSubordinating degree function include:
With ρ1、ρ2Indicate the critical value between S and U, ρ3、ρ4Indicate the critical value between U and V；
If fS(ρpix) bigger, then vehicle density ρpixThe degree for belonging to S is bigger, works as ρpix∈(0,ρ1) when, determine vehicle density ρpix
For S；Work as ρpix∈(ρ1,ρ2) when, determine vehicle density ρpixBetween S and U；
If fU(ρpix) bigger, then vehicle density ρpixThe degree for belonging to U is bigger, works as ρpix∈(ρ1,ρ2) when, determine vehicle density
ρpixBetween S and U；Work as ρpix∈(ρ2,ρ3) when, determine vehicle density ρpixFor U；Work as ρpix∈(ρ3,ρ4) when, determine wagon flow
Density ppixBetween U and V；
If fV(ρpix) bigger, then vehicle density ρpixThe degree for belonging to V is bigger, works as ρpix∈(ρ3,ρ4) when, determine vehicle density
ρpixBetween U and V；Work as ρpix∈(ρ4, 1) when, vehicle density ρpixFor V；Work as fV(ρpixWhen) > 0, vehicle density ρ is determinedpix∈
V。
6. a kind of vehicle density computing system characterized by comprising
Processing unit, the detection image for acquiring to detection zone carry out binary conversion treatment, obtain bianry image；
Statistic unit, for obtaining the detection zone using the operational objective in bianry image described in pixels statistics method statistic
The vehicle density in domain；
Determination unit determines the detection zone using fuzzy vehicle density for the vehicle density according to the detection zone
The vehicle density state in domain.
7. vehicle density computing system as claimed in claim 6, which is characterized in that the statistic unit is specifically used for:
Any pixel point P in the bianry imageiPixel value be Xi, Xi=0 or Xi=1, form the pixel of the moving target
Region XiTotal pixel value of=1, the detection zone S are Spix, vehicle density ρpix, then:
Wherein XiFor the pixel value in the detection zone S.
8. vehicle density computing system as claimed in claim 7, which is characterized in that the determination unit is specifically used for:
It is determined using Gaussian distribution model and 3 σ principles using fuzzy vehicle density according to the vehicle density of the detection zone
The vehicle density state；
S is used respectively, and U, V indicate dilute, normal, close three kinds of states of traffic density state, by vehicle density ρpixObscure for S, U,
V }, the vehicle density ρpixSubordinating degree function include:
With ρ1、ρ2Indicate the critical value between S and U, ρ3、ρ4Indicate the critical value between U and V；
If fS(ρpix) bigger, then vehicle density ρpixThe degree for belonging to S is bigger, works as ρpix∈(0,ρ1) when, determine vehicle density ρpix
For S；Work as ρpix∈(ρ1,ρ2) when, determine vehicle density ρpixBetween S and U；
If fU(ρpix) bigger, then vehicle density ρpixThe degree for belonging to U is bigger, works as ρpix∈(ρ1,ρ2) when, determine vehicle density
ρpixBetween S and U；Work as ρpix∈(ρ2,ρ3) when, determine vehicle density ρpixFor U；Work as ρpix∈(ρ3,ρ4) when, determine wagon flow
Density ppixBetween U and V；
If fV(ρpix) bigger, then vehicle density ρpixThe degree for belonging to V is bigger, works as ρpix∈(ρ3,ρ4) when, determine vehicle density
ρpixBetween U and V；Work as ρpix∈(ρ4, 1) when, vehicle density ρpixFor V；Work as fV(ρpixWhen) > 0, vehicle density ρ is determinedpix∈
V。
9. a kind of terminal, including memory, processor and the meter for being stored on the memory and running on the processor
Calculation machine program, which is characterized in that when the processor executes the computer program, realize such as claim 1 to 5 any one
Each step in the vehicle density calculating.
10. a kind of readable storage medium storing program for executing, is stored thereon with computer program, which is characterized in that the computer program is processed
When device executes, each step in the vehicle density calculation method as described in claim 1 to 5 any one is realized.
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