Method for judging stolen articles in video monitoring range

Abstract

The invention discloses a method for judging stolen articles in a video monitoring range. The invention has the advantages that when determining whether pixel values of all pixel points in an image ina target area to be monitored of the original monitoring image is updated, similarities of the image in the target area to be monitored of the current image and the image in the target area to be monitored of the original monitoring image are introduced; whether the pixel values of all pixel points in the image in the target area to be monitored of the original monitoring image need to be updatedis determined by judging whether the similarity is greater than the similarity threshold value, thus being capable of effectively suppressing the instability of parts of images in the target area tobe monitored caused by rapid change of light; when the moving target leaves the target area to be monitored, whether the articles are stolen is determined by judging the dissimilarities of the image in the target area to be monitored of the current image and the image in the target area to be monitored of the original monitoring image, thus being capable of effectively avoiding misinformation, even though the light changes sharply.

Description

technical field [0001] The invention relates to a method for judging the theft of a monitored article, in particular to a method for judging the theft of an article within the scope of video surveillance. Background technique [0002] With the continuous in-depth development of the field of security monitoring, video surveillance has also developed from general simple monitoring to intelligent video surveillance, and more and more intelligent video surveillance products have been developed. In the analysis of video surveillance behavior, there are mainly alarms triggered when crossing the warning line, alarms are triggered when moving objects enter or leave the warning area, alarms are triggered when moving objects stay in the same place for a long time, and alarms are triggered when objects are lost from moving objects. According to the designated monitored items, an alarm will be triggered when a moving target takes away the monitored items. [0003] There are many situat...

AI Technical Summary

Problems solved by technology

In the process of detecting and identifying the theft of monitored items, the most primitive method is manual identification, which requires the guards to stare at the video transmitted to the client from the video capture device installed around the monitored items 24 hours a day. It can guarantee zero false positives and zero negative negatives, but this method has many disadvantages: (1), since the guards need to pay attention to the video at all times to prevent the theft of the monitored items, the cost of manual management is increased; (2), due to A special person needs to watch the video 24 hours a day, but because people stare at an object for a long time, they will have visual fatigue. At this time, they are prone to dozing off or deserting, which may cause someone to take advantage of the caretaker. theft

[0004] In order to solve the problems existing in the above-mentioned manual detection and identification methods, it is currently more commonly used to transmit the video acquired by the video capture device to a terminal device such as a computer in real time, and analyze whether there is a moving target near the monitored item. If there is a moving target appears, when the moving target leaves the monitored item, it is a method to determine whether the monitored item still exists. This method is more suitable for occasions where there are many monitored items, but the current method has a high false alarm rate and False negative rate

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