Moving target detecting method based on background reconstruction

Abstract

The invention discloses a moving target detecting method based on background reconstruction, comprising the following steps: inputting an image sequence and computing the gray level difference of the adjacent frames of the pixels; classifying the stable gray level intervals; computing the mean gray level of each class of stable gray level intervals; merging the similar classes of stable gray level intervals; selecting the background gray levels of the pixels; and detecting the moving target. The method saves storage space, is small in computed amount, good in robustness and wide in application range, dispenses with establishing models of the backgrounds and targets in the scenes and can directly reconstruct the backgrounds from the scene images containing moving foreground and effectively avoid mixing. The method has extensive application prospect in such real-time system fields as machine vision, video monitoring, military science, urban traffic monitoring, daily resident safety monitoring, etc.

Description

technical field [0001] The invention relates to a detection and processing system for moving objects, in particular to a background-based processing method and system for moving objects. Background technique [0002] Segment the moving target in the video sequence, that is, extract the moving area from the continuous video sequence, and distinguish the moving foreground and background. The intelligent monitoring system extracts the moving target of the video sequence without human intervention, locates, recognizes and tracks the extracted moving target, and analyzes and judges the behavior of the target, which can be used for subsequent target identification and tracking. , Alarm and records provide the basis, and can also respond in time when abnormal situations occur. In addition, in addition to the application in the intelligent monitoring system, it has broad application prospects in the fields of machine vision and military science. [0003] There are three commonly u...

AI Technical Summary

Problems solved by technology

The model method is to establish a statistical model for the gray level of each pixel, such as a Gaussian distribution model, a mixed Gaussian distribution model, etc., and use an adaptive method to update the background by adjusting the model parameters. This method is only available when the scene does not contain moving objects. Only when the model can be initialized correctly, there are certain difficulties in practical application; the gray level classification method is based on certain assumptions, using a continuous video sequence that has been observed to select the pixel gray level to obtain the current background image, such as: based on The background reconstruction technology of pixel classification, this method has a small amount of calculation, but when the pixel gray level changes slowly, it will produce wrong reconstruction results

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