Complex background modeling method based on variable Gaussian mixture number

A technology of Gaussian mixture and complex background, applied in the field of complex background modeling based on variable Gaussian mixture number, to achieve good anti-interference effect

Active Publication Date: 2014-04-02
中国航天科工集团第二研究院二〇七所
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Problems solved by technology

[0004] The technical problem to be solved by the present invention is how to design a variable Gaussian mixture number adaptive background modeling method, through the Gaussian mixture model and the varia

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  • Complex background modeling method based on variable Gaussian mixture number
  • Complex background modeling method based on variable Gaussian mixture number

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[0044] In order to make the purpose, content, and advantages of the present invention clearer, the specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0045] The invention is an image processing method for realizing moving target detection under complex background, which is mainly applied to mass video retrieval system. This method runs under the VC6.0 platform with the help of C++ language programming. In order to realize the moving target detection in complex scenes, such as figure 1 As shown, the method includes the following steps:

[0046] Step S1: Collecting the current video sequence images in a stationary state of the shooting device;

[0047] Step S2: Assuming that each pixel in the video scene is affected by independent Gaussian noise, a pixel model of the background is established;

[0048] Step S3: Calculate the model of the entire video scene according...

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Abstract

The invention relates to a complex background modeling method based on a variable Gaussian mixture number and belongs to the technical field of photoelectric product application. The complex background modeling method comprises the following steps: assuming that each pixel in a video scene is affected by independent Gaussian noise, establishing a background pixel model; according to the pixel model, calculating the whole video scene model; calculating the probability of a certain pixel point value by using a Gaussian mixture model; based on a current pixel point value, a pixel point mean value and a pixel point variance value, calculating the Mahalanobis distance from a current pixel point to a certain Gaussian distribution; updating background model parameters of Gaussian mixture distribution according to a comparison result between the Mahalanobis distance and a judged threshold so as to model a complex background. In the complex background modeling method, through the Gaussian mixture model and a variable Gaussian mixture number updating strategy, a moving target in a complex scene under dynamic disturbance can be effectively detected; tests on visible light sequence images in a street environment prove that the complex background modeling method has good interference resistance and realizes detection of a moving object in complex scenes such as tree branch waggling, shadow existence.

Description

technical field [0001] The invention relates to the technical field of optoelectronic product applications, in particular to a complex background modeling method based on variable Gaussian mixture numbers. Background technique [0002] Back moving object detection technology based on video or image sequence has always been a very important and active research topic in the fields of computer vision, image processing and pattern recognition. How to extract the object of interest from the video image sequence is the first and most important step in the intelligent video analysis system. The effectiveness of video moving target detection methods directly affects the processing effect of subsequent systems. In practical applications, due to the complexity of the environment where the moving target is located and some degradation in image transmission and conversion in the image system, complex backgrounds Moving object detection becomes more difficult. Therefore, finding a real...

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Application Information

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IPC IPC(8): G06T7/20
Inventor 杨文佳王楠柴智李亚鹏
Owner 中国航天科工集团第二研究院二〇七所
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