Moving object detection method based on multi-threshold self-optimization background modeling

A moving target and background modeling technology, which is applied in the field of moving target detection based on multi-threshold self-optimized background modeling, can solve the problems of reduced detection accuracy, easy generation of noise, and difficult elimination of artifacts, etc., to improve model reserves, Avoid repeated selection and better adapt to complex environments

Active Publication Date: 2019-08-09
WUHAN FENJIN INTELLIGENT MACHINE CO LTD
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Problems solved by technology

However, since this method uses the first frame image in the video sequence to establish a background model, it is easy to regard the moving object in the first frame as a background point, resulting in artifacts in the detection images of subsequent frames and the artif

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  • Moving object detection method based on multi-threshold self-optimization background modeling
  • Moving object detection method based on multi-threshold self-optimization background modeling
  • Moving object detection method based on multi-threshold self-optimization background modeling

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[0059] The technical scheme of the present invention will be further described below in conjunction with the drawings and embodiments.

[0060] Step 1. Build a background model. In order to improve the quality of the model and avoid the repeated selection of pixels, the present invention adopts the modeling of 20 neighborhood pixels of the first f frame image, and the specific implementation is as follows:

[0061] Step 101: Convert the input image from RGB space to grayscale image, the conversion formula is as follows:

[0062] v(x)=0.2989*R+0.5870*G+0.1140*B (1)

[0063] Where v(x) represents the gray-scale pixel value converted from the original RGB color space at position x.

[0064] Step 102: Initialize the background model by using the first f frames converted into grayscale images. It is more appropriate to take f as 5 after multiple experiments. The expression of the background model M(x) is as follows:

[0065] M(x)={v 1 ,v 2 ,...,v N } (2)

[0066] Where x is the position of t...

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Abstract

The invention provides a moving object detection method based on multi-threshold self-optimization background modeling. According to the method, artifacts in a detection result can be quickly eliminated, and the anti-interference capability to a complex environment is relatively high. In order to achieve the purpose, the adopted technical scheme is as follows: creating a background model by using20 neighborhoods of pixel points; judging whether the pixel value of the new frame belongs to the background or not through the simultaneous action of the self-adaptive distance threshold value of thegray scale space and the color distortion threshold value of the RGB space; removing noise points and filling holes in the foreground area through noise point removal, hole filling and median filtering processing; counting the occurrence frequency of foreground points, updating the background model according to the occurrence frequency, wherein a moving target and a background can be displayed onan image through binary segmentation. The method can be widely applied to the fields of traffic video monitoring, indoor security and protection, computer vision and the like, and has a wide application prospect and a high economic value.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to a moving target detection method, in particular to a moving target detection method based on multi-threshold self-optimizing background modeling. Background technique [0002] Moving object detection technology is a key technology in the field of computer vision. Its main purpose is to separate the moving objects in the video information from the background, so as to extract clear and complete moving objects. Currently common moving target detection methods include frame difference method, background difference method, mixed Gaussian modeling method, codebook method and visual background extraction method, etc. Among them, the visual background extraction algorithm is a moving object detection algorithm based on random background pixel modeling proposed by Barnich et al. in 2009. It occupies less memory and runs fast, and is suitable for video monitoring and automatic processing fi...

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Application Information

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IPC IPC(8): G06T7/246G06T7/215G06T7/11G06T7/136G06T7/194G06T5/00
CPCG06T5/002G06T2207/10016G06T2207/10024G06T2207/20032G06T7/11G06T7/136G06T7/194G06T7/215G06T7/246
Inventor 张子蓬周博文王淑青马烨蔡颖婧王珅庆逸辉王晨曦兰天泽刘逸凡邹琪骁
Owner WUHAN FENJIN INTELLIGENT MACHINE CO LTD
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