CN105913689B - Motor vehicle running safe early warning method - Google Patents
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- CN105913689B CN105913689B CN201610493819.5A CN201610493819A CN105913689B CN 105913689 B CN105913689 B CN 105913689B CN 201610493819 A CN201610493819 A CN 201610493819A CN 105913689 B CN105913689 B CN 105913689B
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/165—Anti-collision systems for passive traffic, e.g. including static obstacles, trees
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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
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
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- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
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Abstract
The present invention provides a kind of motor vehicle running safe early warning method, this method includes：In vehicle travel process, the image captured to vehicle-mounted vidicon carries out spacing detection；Alarm is sent out when the spacing of vehicle and front truck is less than safe distance.The present invention proposes a kind of motor vehicle running safe early warning method, and information of safety inspection for motor vehicles is realized in embedded chip, improves traffic safety early warning performance, calculating and early warning in real time can will be realized under calculation amount in task treating capacity.
Description
Technical field
The present invention relates to intelligent transportation, more particularly to a kind of motor vehicle running safe early warning method.
Background technology
In recent years, as global traffic demand increases, all kinds of urban highway traffic facility resources are limited, transportation supplies and need
It asks uneven, huge pressure is brought to urban transportation.In China, no card is violating the regulations to drive, road traveling on unqualified vehicle, drives
Member's fatigue drives, drives when intoxicated, overloading, exceed the speed limit etc. the reason of being initiation traffic accident.Existing road traffic accident analytical table
Bright, accident percentage related with driver's subjective factor accounts for nearly 95%.The reason of really causing serious accident is finally still returned
It ties in traffic participant itself, to which a set of comprehensive traffic safety auxiliary system is just particularly important.In recent years, computer
Technology rapidly develops, and objectively differentiates that specific environment is possibly realized using camera, digital image processing techniques day
Become perfect, it is more and more accurate quick to handle acquired visual information using digital computer.In traditional automobile chip manufacture,
It is controlled using microcontroller.Software in microcontroller still uses the assembler language of lowermost level.Using the single thread method of operation, money
Source utilization rate is low.The effect of the introducing of intelligent transportation system, running safe early warning is increasingly taken seriously, and function is increasingly
It is powerful, while what is brought is also task treating capacity, the increase of calculation amount.Therefore only the chip controls of microcontroller is leaned on cannot
Adapt to the safe manufacturing of automobile.
Invention content
To solve the problems of above-mentioned prior art, the present invention proposes a kind of motor vehicle running safe early warning side
Method, including：
In vehicle travel process, the image captured to vehicle-mounted vidicon carries out spacing detection；When vehicle and front truck
Spacing sends out alarm when being less than safe distance.
Preferably, the spacing detection further comprises：
Edge detection is carried out using approximate circle sliding window first, i.e., by approximate circle sliding window on gray level image to be detected
It slides, the gray value for each pixel for giving number inside sliding window is compared with the gray value of sliding window center pixel, such as
The gray value of certain point pixel is less than the threshold value t of setting with the difference of center gray scale in fruit sliding window, it is determined that the point and sliding window center
Putting has identical gray scale, and all summations for having the value of same grayscale with center constitute similar area in sliding window；
By coordinate (xc, yc) indicate sliding window centre coordinate, it is as follows using similar comparison function：
C (x, y)=exp [- [[I (x, y)-I (xc,yc)]/2]6]
I (x, y) is the gray scale of coordinate x, y；
Then the size of similar area is calculated as：
It is adaptively selected to t values under different contrast, i.e., in round sliding window, by pixel value in cumulative sliding window come really
Determine the threshold value t of pixel and sliding window center pixel difference in sliding window：
For given approximate circle sliding window, accumulated variables, img are indicated with sum(i, j)(k) indicate center pixel in source figure
The i-th row jth row as in, k indicate k-th of pixel in sliding window, then the threshold value t of k-th of pixel is：
T=sum/n (xc, yc)
Sum makes t values in response to local contrast by cumulative sliding window pixel；
K-th of pixel and the difference of center pixel are found out, is made comparisons with t, if less than or equal to if t, similar area adds 1, most
The size of similar area and threshold value g is judged afterwards, if being less than g, current pixel is marginal point, and current pixel value is set as 255, no
Then, current pixel is not marginal point, is set to 0.
Preferably, before the edge detection, returning method further includes：Edge detection, screening side only are done to candidate marginal
Method is as follows：
First centered on central pixel point, calculate the pixel difference at vertical segment both ends, and with pre-set difference threshold
Value Th is compared, and the gray-scale pixels point more than Th is as candidate marginal, conversely, the point less than Th is considered as then internal picture
Vegetarian refreshments prepares removal.
The present invention compared with prior art, has the following advantages：
The present invention proposes a kind of motor vehicle running safe early warning method, and automobile safety is realized in embedded chip
Detection, improves traffic safety early warning performance, calculating and early warning in real time can will be realized under calculation amount in task treating capacity.
Description of the drawings
Fig. 1 is the flow chart of motor vehicle running safe early warning method according to the ... of the embodiment of the present invention.
Specific implementation mode
Retouching in detail to one or more embodiment of the invention is hereafter provided together with the attached drawing of the diagram principle of the invention
It states.The present invention is described in conjunction with such embodiment, but the present invention is not limited to any embodiments.The scope of the present invention is only by right
Claim limits, and the present invention covers many replacements, modification and equivalent.Illustrate in the following description many details with
Just it provides a thorough understanding of the present invention.These details are provided for exemplary purposes, and without in these details
Some or all details can also realize the present invention according to claims.
An aspect of of the present present invention provides a kind of motor vehicle running safe early warning method.Fig. 1 is according to embodiments of the present invention
Motor vehicle running safe early warning method flow chart.
Present invention vehicle detection in vehicle travel process, real time distance.Embedded OS is cut out first,
Then load driver transplants compiled system.After loading third-party image software handles library, application software is carried out
It writes and carry, is then transplanted in embedded chip.Using the method for adaptive threshold to candidate marginal Detection and Extraction vehicle
Edge and then vehicle is extracted, to calculate spacing.
The present invention installs cross compilation environment in server end, sets first, in server end into line program
Binary image is write and generated, and the operation of application program is carried out at embedded board end.Therefore the auxiliary of the present invention is driven
The program for sailing early warning system adds corresponding hardware and driving on embedded board.
The auxiliary of the present invention drives early warning system and uses camera collection image, then on the basis of operating system, into
Row application is write, and is comprised the following modules：
Image collection module：Image is obtained from camera, then carries out color space conversion and the pretreatment of image, will be detected
To image be sent to other modules.
Lane detection module：It identifies the traffic lane line in image, itself is judged whether within the scope of safe track, if not
It is then to send out alarm.
Spacing detection module：By the video frame of acquisition, a series of processing are carried out to image, determine that front truck or barrier exist
Position in image, adjusts the distance and is judged, if it is less than safe distance, then sends out alarm.
Car alarming module：The function of the module is when there is unsafe condition to aforementioned function module, to send out alarm.
Image display：Distance prompt is provided from image, provides the user with visible results.
Wherein spacing detection module uses the same video streaming image source with lane detection module, therefore uses multithreading
Programming is realized.The present invention opens thread using timer class.A signal is generated when timer triggers, and is run in this way
Timer class, the communication between thread is realized using incompatible lock mechanism.If possessing mutual exclusion lock there are one thread, other
Thread at this time can not access it, can be only in dormant state, until the thread unlocks lock release.
For lane detection, detection method proposed by the present invention utilizes track color and both known features of direction,
Processing is weighted to color characteristic, bonding position significant characteristics divide lane position jointly, and it is special then to extract lane markings
Point is levied, candidate point is fitted, track region is obtained.
Due to Perspective Principles, obtained track always intersects at certain point in road imaging process, and is actually flat
Two tracks of line can be rendered as π/3 and 2 π/3 two intersecting lens in the picture, according to this feature to being constrained into line direction,
Make notable figure Direction of superposition feature, can more clearly from indicate the notable feature in track.
For direction α and scale β, definition filtering kernel function：
Wherein a=xcos α+ysin α, b=-xsin α+ycos α, c=2.2.For track, π/3 and 2 π/3 liang are chosen
Kernel function under the scale of two, a direction carries out convolution, if I (x, y) is the value that (x, y) is put in figure, I is α with direction and scale is
Kernel function convolution under β, is defined as：
It is divided into real part and imaginary part two parts in the convolution results that z=(x, y) is put, response is taken as putting down for real part and imaginary part
Fang He：
Iα,β(z)=Re (Gα,β(z)2)+Im(Gα,β(z)2)
Response under a direction α is defined as the fusion of the transformation results of direction different scale β, uniformly to obtain two
The information of a scale takes the average value of different scale result, the fusion results finally obtained, for the region of each different directions
Respond different, region response region that is relatively strong, and being runed counter to image texture direction identical with image texture direction
It responds relatively weak.
There is known obvious color characteristic according to track, to designated color picture in color notable figure generating process
Element carries out significance enhancing, then carries out region contrast comparison on the basis of the notable figure by color characteristic enhancing, obtains
Notable figure based on region contrast.I.e. on color space, to some pixel, it is calculated between other all pixels
Apart from summation, notable figure of the pixel under global resolution ratio has just been obtained.
The pixel I in image IkIt is as follows being calculated using color contrast as the saliency value of significance measure method:
S(Ik)=∑1≤j≤nfjD(Ik, Ij)
Wherein D (Ik, Ij) it is pixel IkAnd IjColor distance in Luv color spaces.N is all for include in image
The sum of all kinds of colors, fjIt is with pixel IkThe quantity of all pixels point of color.
If color notable figure is S, direction notable figure is set as R, need to be by color notable figure and direction further to highlight track
Notable figure blends.Regularization is done to color notable figure and direction notable figure respectively.
N (S)=(S-min (S))/(max (S)-min (S))
Max (S) in formula, min (S) respectively represent the maximum and minimum value in notable figure.
On this basis, the two is done into fusion treatment and obtains total notable figure SR.
SR=N (S) × N (R)
Binary conversion treatment is carried out to notable figure, obtains segmentation image.So being retrieved since picture centre line, choose notable
1/3 is ROI at figure close shot, extracts two track characteristic points, is set as (xi,yi) (i=0,1,2 ..., n).If function y=F
(x) corresponding parametric equation is y=kx+b, to arbitrary characteristics point (xi,yi) error of target line is corresponded to as ε=F (xi)-yi,
Then the corresponding error sum of squares of all characteristic points is as follows：
The function that above formula obtains minimum value is required straight line parameter.
Spacing is detected, the front vehicles in identification extraction image are first had to.The present invention uses a kind of approximate circle cunning
Window carries out edge detection.Approximate concentric stroking window is slided on gray level image to be detected, each of number is given inside sliding window
The gray value of pixel will be all compared with the gray value of sliding window center pixel.If in sliding window the gray value of certain point pixel with
The difference of center gray scale is less than the threshold value t of setting, it is determined that the point and sliding window central point have an identical gray scale, in sliding window it is all with
Center has the summation of the value of same grayscale to constitute similar area.
By coordinate (xc, yc) indicate sliding window centre coordinate.It is as follows using similar comparison function：
C (x, y)=exp [- [[I (x, y)-I (xc,yc)]/2]6]
I (x, y) is the gray scale of coordinate x, y；
Then the size of similar area is calculated as：
Under normal circumstances, threshold value t determines the feature quantity for the characteristic point that can be extracted.The present invention is under different contrast
It is adaptively selected to t values：In round sliding window, pixel and imago in sliding window in sliding window are determined by pixel value in cumulative sliding window
The threshold value t of plain difference.Computational methods are as follows：
For given approximate circle sliding window, sum indicates accumulated variables, img(i, j)(k) indicate center pixel in source images
In the i-th row jth row, k indicate sliding window in k-th of pixel.
Then the threshold value t of k-th of pixel is：
T=sum/n (xc, yc)
Sum makes t values calculate the response characteristic for having local contrast by the method for the sliding window pixel that adds up, in sliding window
Pixel, t values are increasing, and can remove the smaller complex background of most of contrast, retain target, detach well target with
Background, and edge is refined, therefore can accurate reservation vehicle edge.
K-th of pixel and the difference of center pixel are found out, is made comparisons with t, if less than or equal to if t, similar area adds 1, most
The size of similar area and threshold value g is judged afterwards, if being less than g, current pixel is marginal point, and current pixel value is set as 255, no
Then, current pixel is not marginal point, is set to 0.
Before above-mentioned edge detection, preliminary screening is first carried out, edge detection only is done to candidate marginal, screening technique is such as
Under：
First centered on central pixel point, calculate the pixel difference at vertical segment both ends, and with pre-set difference threshold
Value Th is compared, and edge appears in the big pixel of grey-scale contrast, therefore the gray-scale pixels point more than Th is as candidate side
Edge point, conversely, the point less than Th, which is considered as then interior pixels point, prepares removal.
The shape of vehicle in the picture in video image is presented certain rule, typically proportional rectangle,
Therefore the present invention is used as detection vehicle foundation using shape feature.Vehicle be have lines rule, top and bottom portion horizontal line, two
In the picture after treatment, the features such as certain straight line can be all presented in side vertical edges etc..
For complicated environment, the feature of selected shape feature of the present invention and boundary characteristic as extraction vehicle location.
The present invention is cut out image first, only carries out vehicle detection to close shot, then carries out enhancing processing to image, including swollen
It is swollen, corrode scheduling algorithm.In order to further determine vehicle location, using the shape feature of vehicle, exclude accidentally to survey caused by background.
Optionally, in spacing detection, vehicles segmentation is carried out by the classification of the size to each light stream vectors mould, is obtained
To front vehicle position.
ROI can be divided on the basis of having detected track, establishes pattern mask, if two tracks is straight in image
Line is y=k1x+b1And y=k2x+b2, the two of N × M is similarly for N × M dimension image I (x, y), setting pattern mask M (x, y)
It is worth image, is all 1's matrix.Its create-rule is as follows.
The y ＜ of M (x, y)=1 k1x+b1And y ＞ k2x+b2
M (x, y)=0 is other
The area coverage of vehicle in the picture is far longer than a block of pixels, so image is subjected to vector block division,
Setup algorithm obtains Ii=I (xi,yi) point 5 × 5 neighborhood light stream vectors be Vi=(ui,vi), then it can obtain image optical flow field Y
(x, y), each field direction cover 5 × 5 neighborhoods of corresponding position in original image.As M (xi,yiWhen)=1, Y (xi,
yi)=(ui,vi)
In order to carry out single threshold value segmentation, component u, v by light stream vectors in x, y both direction are merged, and are melted
Close scalar figure P (x, y)：
To P (xi,yi) region division is carried out, vehicle movement contrast district in image is obtained, the early warning calculating for after provides
Reliable guarantee.
In conclusion the present invention proposes a kind of motor vehicle running safe early warning method, realized in embedded chip
Information of safety inspection for motor vehicles improves traffic safety early warning performance, can will realize under calculation amount in task treating capacity and calculate in real time
And early warning.
Obviously, it should be appreciated by those skilled in the art, each module of the above invention or each steps can be with general
Computing system realize that they can be concentrated in single computing system, or be distributed in multiple computing systems and formed
Network on, optionally, they can be realized with the program code that computing system can perform, it is thus possible to they are stored
It is executed within the storage system by computing system.In this way, the present invention is not limited to any specific hardware and softwares to combine.
It should be understood that the above-mentioned specific implementation mode of the present invention is used only for exemplary illustration or explains the present invention's
Principle, but not to limit the present invention.Therefore, that is done without departing from the spirit and scope of the present invention is any
Modification, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.In addition, appended claims purport of the present invention
Covering the whole variations fallen into attached claim scope and boundary or this range and the equivalent form on boundary and is repairing
Change example.
Claims (2)
1. a kind of motor vehicle running safe early warning method, which is characterized in that including：
In vehicle travel process, the image captured to vehicle-mounted vidicon carries out spacing detection；When the spacing of vehicle and front truck
Alarm is sent out when less than safe distance；
The spacing detection further comprises：
Edge detection is carried out using approximate circle sliding window first, i.e., it is approximate circle sliding window is sliding on gray level image to be detected
Dynamic, the gray value that each pixel of number is given inside sliding window is compared with the gray value of sliding window center pixel, if
The gray value of certain point pixel is less than the threshold value t of setting with the difference of center gray scale in sliding window, it is determined that the point and sliding window central point
There is an identical gray scale, all summations for having the value of same grayscale with center constitute similar area in sliding window；
By coordinate (xc, yc) indicate sliding window centre coordinate, it is as follows using similar comparison function：
C (x, y)=exp [- [[I (x, y)-I (xc,yc)]/2]6]
I (x, y) is the gray scale of coordinate x, y；
Then the size of similar area is calculated as：
It is adaptively selected to t values under different contrast, i.e., in round sliding window, cunning is determined by pixel value in cumulative sliding window
The threshold value t of pixel and sliding window center pixel difference in window：
For given approximate circle sliding window, accumulated variables, img are indicated with sum(i, j)(k) indicate center pixel in source images
The i-th row jth row, k indicate sliding window in k-th of pixel, then the threshold value t of k-th of pixel be：
T=sum/n (xc, yc)
Sum makes t values in response to local contrast by cumulative sliding window pixel；
K-th of pixel and the difference of center pixel are found out, is made comparisons with t, if less than or equal to if t, similar area adds 1, finally sentences
The size of disconnected similar area and threshold value g, if being less than g, current pixel is marginal point, and current pixel value is set as 255, otherwise,
Current pixel is not marginal point, is set to 0.
2. according to the method described in claim 1, it is characterized in that, before the edge detection, returning method further includes：Only to waiting
Marginal point is selected to do edge detection, screening technique is as follows：
First centered on central pixel point, calculate the pixel difference at vertical segment both ends, and with pre-set difference threshold Th
It is compared, the gray-scale pixels point more than Th is as candidate marginal, conversely, the point less than Th is considered as then interior pixels point
Prepare removal.
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| CN102063704A (en) * | 2010-11-19 | 2011-05-18 | 中国航空无线电电子研究所 | Airborne vision enhancement method and device |
| JP5471310B2 (en) * | 2009-10-30 | 2014-04-16 | コニカミノルタ株式会社 | Operation analysis system |
| CN103870833A (en) * | 2014-03-31 | 2014-06-18 | 武汉工程大学 | Method for extracting and evaluating pavement crack based on concavity measurement |
| CN105336217A (en) * | 2015-12-09 | 2016-02-17 | 东华大学 | Driving safety prewarning system based on machine vision and Android platform |
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- 2016-06-28 CN CN201610493819.5A patent/CN105913689B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5471310B2 (en) * | 2009-10-30 | 2014-04-16 | コニカミノルタ株式会社 | Operation analysis system |
| CN102063704A (en) * | 2010-11-19 | 2011-05-18 | 中国航空无线电电子研究所 | Airborne vision enhancement method and device |
| CN103870833A (en) * | 2014-03-31 | 2014-06-18 | 武汉工程大学 | Method for extracting and evaluating pavement crack based on concavity measurement |
| CN105336217A (en) * | 2015-12-09 | 2016-02-17 | 东华大学 | Driving safety prewarning system based on machine vision and Android platform |
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Denomination of invention: Pre-warning method for motor vehicle driving safety Effective date of registration: 20200619 Granted publication date: 20180828 Pledgee: Bank of Chengdu science and technology branch of Limited by Share Ltd. Pledgor: CHENGDU ZHIDA TECHNOLOGY Co.,Ltd. Registration number: Y2020980003275 |
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