Complete graph extraction method

Abstract

The invention provides a complete graph extraction method. The complete graph extraction method comprises the steps of obtaining a shot video frame sequence; Extracting a foreground image of the current video according to the video frame sequence based on a pre-trained neural network model; Judging whether an abnormal cavity exists in the foreground image or not according to the target backgroundimage and a judgment threshold value, and if yes, filling the abnormal cavity according to a preset abnormal cavity filling method, Wherein the selection of the target background image is related to an illumination time period, an illumination intensity section and resolution, and the judgment threshold value is related to the motion state and time of an object corresponding to a foreground imagein the video frame sequence. According to the method, the accurate shape of the non-background image in the video image can be quickly and accurately obtained, so that subsequent further processing isfacilitated, the intelligence is high, the accuracy of the obtained graph is high, and the method has a wide application prospect.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for extracting complete graphics. Background technique [0002] The intelligent monitoring system adopts image processing, pattern recognition and computer vision technology. By adding an intelligent video analysis module to the monitoring system, the powerful data processing capability of the computer is used to filter out useless or disturbing information in the video screen, automatically identify different objects, analyze and extract The key and useful information in the video source can quickly and accurately locate the accident scene, judge the abnormal situation in the monitoring screen, and issue an alarm or trigger other actions in the fastest and best way, so as to effectively carry out pre-warning, processing during the event, and timely after the event Fully automatic, all-weather, real-time monitoring intelligent system for evidence collection. [0003] In ...

AI Technical Summary

Problems solved by technology

[0003] In the existing technology, intelligent monitoring has been widely used, but the relevant technologies for extracting images from flowing video frames and automatically processing the extracted images are not yet mature, so it is difficult to achieve complete automation, and it still needs to rely on Identification with the naked eye

In view of the immature technology of automatic image processing, the false alarm rate of automatic alarm based on image processing technology is high, and it is difficult to obtain the accurate outline and precise position of the suspected target

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