Method for detecting moving target of video image

Abstract

The invention provides a method for detecting a moving target of a video image. The method comprises the following steps of: A. for previous N frames of images, constructing an initial background image by a codebook model; B. counting the mean value and the variance of the initial background image for an initialized hybrid gaussian background model; C. carrying out interval estimation on a background pixel and setting a confidence interval of the background pixel; and D. updating parameters of the hybrid gaussian background model so as to generate the background image when the pixel meets the confidence interval to obtain the moving target by subtraction of the current frame of image and the background image. According to the method, pixel values are matched so as to get rid of mutational pixel values in initialization of parameters of the model, a foreground image and the background image can be accurately distinguished due to the arrangement of the confidence interval, and relatively mutiple accurate moving target images can be obtained.

Description

technical field [0001] The invention relates to the field of digital image processing, in particular to a method for detecting a moving object of a video image. Background technique [0002] Moving target detection based on video images is a research hotspot in the field of computer vision, and it is the basis of moving target tracking. It is widely used in intelligent transportation systems, intelligent video surveillance, military guidance systems and other fields. [0003] The use of surveillance video for target detection generally uses fixed surveillance cameras to shoot real-time shots of moving scenes, then processes the captured video images, and performs target detection through moving target detection algorithms to lay the foundation for subsequent target tracking. [0004] Moving object detection refers to judging the moving object in the video image sequence, and locating and segmenting the moving object, so as to extract the object from the video image. As the ...

AI Technical Summary

Problems solved by technology

If the mean and variance of the pixel values ​​of the image frame over a period of time are calculated as the parameters of the initial model, then in the initial stage, moving objects or detection targets appearing in the scene will obviously take their pixel values ​​into account. Although in subsequent parameter updates, the mean and variance will tend to a value close to the "true" as the number of calculation frames increases, however, this calculation method will inevitably cause the background model to be inaccurate

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