Video image foreground detection method for traffic intersection scene and based on network physical system

A technology for physical systems and traffic intersections, applied in traffic flow detection, instruments, character and pattern recognition, etc., can solve problems such as inability to correctly guide the background learning process, and achieve the effect of avoiding image processing steps

Inactive Publication Date: 2014-12-10
BEIHANG UNIV
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Problems solved by technology

Even if the improved algorithm mentioned above has the ability to adjust the learning rate online, if only the brightness information of the image is used, it will not be able to correctly guide the background learning process in this scene.

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  • Video image foreground detection method for traffic intersection scene and based on network physical system
  • Video image foreground detection method for traffic intersection scene and based on network physical system
  • Video image foreground detection method for traffic intersection scene and based on network physical system

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Embodiment Construction

[0031] The present invention will be described in detail below in conjunction with the drawings.

[0032] Such as figure 1 As shown, the specific operation process of the present invention is as follows:

[0033] (1) The computing unit obtains the video sequence from the still camera, and initializes the background model parameters, including the mixed Gaussian background model parameters: the number of Gaussian models K=5, the learning rate α=0.005, the standard deviation σ=30, and the mean value μ passes through the average frame Method to get.

[0034] (2) Lane line detection, because the traffic light signals will have different effects on different lanes, the computing unit divides the video image area through the lane line detection algorithm to obtain the area set φ={γ 1 , Γ 2 ,..., γ M }(Γ i Indicates the i-th region of interest, M is the total number of regions of interest, 1≤i≤M), as the basis for subsequent adjustment of the pixel learning rate according to the image space...

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Abstract

The invention discloses a video image foreground detection method for a traffic intersection scene and based on a network physical system, wherein the main application scene is an intersection in the urban traffic. The method mainly comprises the following steps of: performing lane line detection in the extracted background frame and dividing an area of interest according to a video image obtained by a static video camera in the system; adjusting the background learning process and the learning rate of the pixel points of different image areas by use of the external information sensed by the system; and adaptively adjusting the parameters in the algorithm in real time to finally obtain a more accurate foreground point detection result. The method disclosed by the invention realizes adaptive adjustment of the background learning rate according to the physical environment under the condition of complicated varying foreground speed in the scene of the urban traffic intersection.

Description

Technical field [0001] The invention relates to the fields of intelligent transportation, video image processing and machine vision, in particular to a video image foreground detection method used in traffic intersection scenes and based on a network physical system. Background technique [0002] Foreground Detection has always been an important research content in the field of video surveillance and image processing. It is the basis of subsequent processing and directly affects higher-level applications, such as interest target tracking, behavior analysis, and anomaly detection. There are two types of foreground detection algorithms: frame difference method and background difference method. The frame difference method is fast and can accurately obtain the edges of moving targets, but the obtained foreground targets have many holes. For fast moving targets, the detection will produce tailing phenomenon, and it cannot detect stationary targets. [0003] Background Subtraction is to...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/01G06K9/66
Inventor 丁嵘刘旭崔伟龙贺百灵
Owner BEIHANG UNIV
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