CN105208398B - A kind of method for obtaining the real-time Background of road - Google Patents

A kind of method for obtaining the real-time Background of road Download PDF

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Publication number
CN105208398B
CN105208398B CN201510608645.8A CN201510608645A CN105208398B CN 105208398 B CN105208398 B CN 105208398B CN 201510608645 A CN201510608645 A CN 201510608645A CN 105208398 B CN105208398 B CN 105208398B
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frame
cluster
road
grid
maximum
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CN105208398A (en
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杨燕
潘鸿
李天瑞
王浩
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Southwest Jiaotong University
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Southwest Jiaotong University
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00Television systems
    • H04N7/18Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Image Analysis (AREA)

Abstract

The invention discloses a kind of methods for obtaining the real-time Background of road, use Grid Clustering quick obtaining road Background, road is divided into many grids first, secondly these grids are carried out with the statistics of H components, then cluster that different video frame is polymerized to is determined according to H component curve figures, finally therefrom extraction feature frame, finally therefrom extraction feature frame.This method has the advantages that complexity is low, efficient, exploitativeness is strong.

Description

A kind of method for obtaining the real-time Background of road
Technical field
The invention belongs to digital picture processing and cluster field, especially suitable for road video extraction Background.Road is carried on the back The modeling of scape figure is a kind of effective ways of video compress transmission process, and in particular to a kind of new Grid Clustering extracts Background The characteristic frame of piece.
Background technology
Recently, background modeling plays an increasingly important role in high efficiency monitor video coding.Meanwhile many practicalities regard Frequency coding application also proposed background modeling some specific requirements, such as low carrying cost, low computation complexity.
Existing background modeling method can substantially be classified as 2 classes:Parametric method, as gauss hybrid models -1, Gauss mix Molding type -2, gauss hybrid models -3 and nonparametric technique include Bayesian model, Density Estimator, time medium filtering, Value drift etc..
The drawbacks such as these methods have mathematical formulae more, and coding is complicated, operational efficiency is low, there is an urgent need for using it is new, simple easily Row and efficiently method are for background modeling.
It is existing with obtaining the relevant side of road background diagram technology by being found to the retrieval of existing patent and the relevant technologies Method and system include:
⑴Low-complexity and high-efficiency background modeling for Surveillance video coding, 2012IEEE International Conference on Visual Communication and Image Processing,San Jose,USA,pp.1-6,11/2012
Propose (SWRA) method based on a branch and weight.First by each pixel in SWRA in training frames Position be divided into some time, then calculate its corresponding average value and weight.Later, weighted mean procedure is used to reduce Influence foreground pixel, and obtain modeling result.
⑵A Fuzzy Background Modeling Approach for Motion Detection in Dynamic Backgrounds, Multimedia and Signal Processing Volume 346of the series Communications in Computer and Information Science pp 177-185
A kind of method is proposed, in -2 model of Gaussian Mixture, is come using fuzzy logic system recurrence sef-adapting filter The update weight of calculating, and finally obtain road Background.As a result it proves using the fuzzy method compared with conventional method, With larger advantage.
⑶Difference of Gaussian Edge-Texture Based Background Modeling for Dynamic Traffic Conditions, Advances in Visual Computing Volume 5358of the series Lecture Notes in Computer Science pp 406-417
It proposes based on Gauss Edge texture, obtains road background and the method for probe vehicle.This method passes through pixel Point and its edge, non-edge pixels point establish contact, have very strong learning performance, can be good at visiting road prospect It surveys and sorts out.
It can be seen that above method, which is all based on Gauss model, carries out mileage chart processing, have formula complicated, coding is realized Difficulty is big, does not have the shortcomings that real-time, is not suitable for road monitoring field higher to requirement of real-time now.
In existing patent still not explicitly for cluster obtain road Background method, so it is proposed that based on net The method that lattice cluster obtains road Background has preferable research significance and application value.
Invention content
In view of the deficiency of existing program set forth above, the present invention is intended to provide efficiently, simple method, and be allowed to overcome The disadvantage mentioned above of the prior art.
To achieve these goals, the considerations of of the invention is:
The road of normally travel all has vehicle above each frame picture.But the concept of grid is used, each frame Video is divided into tiny grid.Video pictures in each grid are made color histogram by us with the H components in HSV, By the maximum value of all H components of the grid in a period of time, curve graph is made.When carless in grid, H components Maximum value curve is basicly stable.When have automobile by when, particularly vehicle color is with the presence of having arrived Background color When larger difference, the maximum value of H components will appear great variety.Vehicle color and road are just the same or same Color automobile series by probability be substantially not present.
Its specific processing includes following means:
A kind of method for obtaining the real-time Background of road, it is first using the method for Grid Clustering quick obtaining road Background Road is first divided into many grids, secondly these grids are carried out with the statistics of H components, is then determined according to H component curve figures The cluster that different video frame is polymerized to, finally therefrom extraction feature frame, includes following processing means:
(1) it is frame by the road video extraction of 30 seconds, video 30 frame per second, 900 frame altogether;
(2) grid interception is done to every frame to divide, and 100 lattice is divided into per frame picture, respectively with the two-dimensional matrix of A-J and 1-10 It represents;
(3) to H components in each grid computing HSV of each frame, to the H component statistical maximum values of each grid;By 900 The maximum value of H components in each grid of each frame of frame is depicted as curve graph;The fluctuation of curve illustrates main in this period There is offset in color, has vehicle to pass through the region;
(4) with the method extraction characteristic frame of cluster:
A. it is calculated since grid A1, is cluster by point cluster of all deviation threshold ranges within 10, the maximum Cluster is exactly the big cluster of road surface Background;
B. the point cluster of all identical values is cluster in the maximum cluster obtained during a is walked, finds out the cluster of number maximum, takes Its longest continuity point, and extract characteristic frame;Characteristic frame pkExtraction model be:
Wherein, pkFor the characteristic frame extracted, pnFor each frame in maximum cluster, n is the number of frame in maximum cluster, and i is most The number that first frame starts in big cluster, j are the number of last frame in maximum cluster.
(5) characteristic frame got is replaced into the original frame of the grid, and returns to the extraction that (4) step starts next grid Characteristic frame until J10 processing completions, obtains the real-time Background of whole picture road;
(6) it returns to (1) step and starts next round calculating.
In actual implementation, the division methods of the grid of each frame, can also be according to practical need except being divided into as 100 especially Determine the grid number divided.
The present invention is directed to the modeling problem of road Background, specifically proposes a kind of feasibility height, and simple, real-time is very Strong Grid Clustering obtains road background drawing method.
Description of the drawings is as follows:
Fig. 1 is one first frame segmentation figure of video.
Fig. 2 is the H component curve figures in b1 regions.
Fig. 3 is the H component curve figures in b5 regions.
Fig. 4 is the 1st frame picture.
Fig. 5 is the 900th frame picture.
Fig. 6 is road background composite diagram.
Fig. 7 is the flow chart of the method for the present invention.
Specific embodiment
The invention will be further described below in conjunction with the accompanying drawings.
Because of the interference of extraneous sunlight, cloud layer, leaf, we are can not to obtain accurate curvilinear motion figure.Therefore we The point changed in threshold range is found out in the graph, and is gathered for cluster.It is considered that here it is road Backgrounds Cluster.Again in the cluster, continually look for having what stable state changed, have the frame of maximum eigenvalue, and draw it out, as the grid Background.Mesh generation is as shown in Figure 1, it is specifically included:
(1) it is frame by the road video extraction of 30 seconds.If video 30 frame per second, 900 frame altogether;
(2) do grid interception to every frame to divide, per frame picture, we are divided into 100 lattice, respectively with the two dimension of A-J and 1-10 Matrix represents, such as figure one;
(3) to H components in each grid computing HSV of each frame, to the H component statistical maximum values of each grid.By 900 The maximum value of H components in each grid of each frame of frame is depicted as curve graph.The fluctuation of curve illustrates main in this period There is offset in color, has vehicle to pass through the region.
(4) with the method extraction characteristic frame of cluster:
Characteristic frame pkExtraction formula:
p:Selected characteristic frame;
i:In (4)-b steps, selected initial position;
j:In (4)-b steps, selected end position.
A. it is calculated since grid A1, it, in this way can be with by point cluster of all deviation threshold ranges within 10 for cluster It filters out because of the offset of H values caused by leaf swing, sunlight scattering, cloud layer variation;Because when the area road free time It occupies the majority, it is believed that this maximum cluster is exactly the big cluster of road surface Background;
B. the maximum cluster obtained during a is walked, continues to handle it.It is cluster the point cluster of identical values all in cluster, Find out the cluster of number maximum.Can find out in this way can most represent the frame of road background under current environment;
C. in the cluster obtained again in b steps, longest continuity point is taken, and extract characteristic frame.By the step for, can be with Further confirm that the moment, which stablizes the most in ectocine, road is in idle state.We recognize The real-time Background in the region of present road can be represented for this feature frame, therefore this feature frame can be used to replace originally Frame.If Fig. 2, Fig. 3 are change curve of the H components maximum value of drafting in 30 seconds.
(5) characteristic frame got is replaced to original characteristic frame, and returns to the extraction spy that (4) step starts next grid Frame is levied, until J10 processing is completed;
(6) it returns to (1) step and starts next round calculating, as described in Figure 7 step.
From the picture of first frame and the 900th frame it can be found that picture has larger shade variation, such as Fig. 4, Fig. 5, figure Described in 6.Movement due to cloud layer, the variation of light are can be seen that from Fig. 6 composite diagrams, different grid charts is that have shade Difference.It can be concluded that from experiment, the real-time of road Background is replaced, to reducing Internet video flow, It is of practical significance.
From above experiment is discussed, it can know that this method has following clear advantage:
1st, this method has that extent feasible is very high, the simple advantage of coding;
2nd, the Background that this method obtains has stronger real-time;
3rd, the characteristic frame of this method extraction can react many variations such as cloud layer movement, light variation, and to road in time The shaking of leaf has very strong anti-interference on both sides of the road.

Claims (1)

  1. A kind of 1. method for obtaining the real-time Background of road, which is characterized in that use Grid Clustering quick obtaining road Background Method, road is divided into many grids first, secondly to these grids carry out H components statistics, then according to H components song Line chart determines the cluster that different video frame is polymerized to, finally therefrom extraction feature frame, includes following processing step:
    (1) it is frame by the road video extraction of 30 seconds, video 30 frame per second, 900 frame altogether;
    (2) grid interception is done to every frame to divide, and is divided into 100 lattice per frame picture, is represented respectively with the two-dimensional matrix of A-J and 1-10;
    (3) to H components in each grid computing HSV of each frame, to the H component statistical maximum values of each grid;By 900 frames The maximum value of H components in each each grid of frame is depicted as curve graph;The fluctuation of curve illustrates that master color occurs in this 30 seconds Offset, has the vehicle to pass through measured zone;
    (4) with the method extraction characteristic frame of cluster:
    A. it is calculated since grid A1, is cluster by point cluster of all deviation threshold ranges within 10, the cluster of the maximum is just It is the big cluster of road surface Background;
    B. the point cluster of all identical values is cluster in the maximum cluster obtained during a is walked, finds out the cluster of number maximum, takes it most Long continuity point, and extract characteristic frame;Characteristic frame pkExtraction model be:
    Wherein, pkFor the characteristic frame extracted, pnFor each frame in maximum cluster, n is the number of frame in maximum cluster, and i is maximum cluster The number that middle first frame starts, j are the number of last frame in maximum cluster;
    (5) characteristic frame got is replaced into the original frame of the grid, and returns to the extraction feature that (4) step starts next grid Frame until J10 processing completions, obtains the real-time Background of whole picture road;
    (6) it returns to (1) step and starts next round calculating.
CN201510608645.8A 2015-09-22 2015-09-22 A kind of method for obtaining the real-time Background of road Expired - Fee Related CN105208398B (en)

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