Foreground detection method and device as well as adaptive threshold adjusting method and device

Abstract

The invention discloses a foreground detection method and a device as well as an adaptive threshold adjusting method and a device. The foreground detection method comprises the following steps: comparing a current input image with a background image of each frame to obtain the difference value points respectively corresponding to pixel points of the current input image; carrying out statistics onthe percentage of the difference value point number, with value more than different thresholds and choosing a threshold suitable for the current input image according to the variation trend that the percentage of the difference value point increases along with the threshold value. Thus, when foreground detection is carried out, the threshold can be adjusted aiming at the monitoring scene with highor low noise, so that the adjusted threshold can be used for judging the foreground pixel points in the image, thereby improving the accuracy of foreground detection and further improving the accuracy of moving object detection and tracking.

Description

technical field [0001] The present invention relates to foreground detection technology, in particular to a foreground detection method and device for moving object detection and tracking, and an adaptive threshold adjustment method and device for foreground detection. Background technique [0002] In the existing video surveillance device, the video in the monitoring scene is usually captured by a still camera, and then the moving object detection and tracking are performed on the continuous multi-frame images of the video, so as to distinguish the moving objects in the continuous multi-frame images from the background image. for analysis. [0003] In the detection and tracking of moving objects, foreground detection is the first step, and its accuracy directly affects the performance of the entire device. The processing process of the existing foreground detection is as follows: first compare the current input image with the background image, and obtain the value differen...

AI Technical Summary

Problems solved by technology

[0006] It can be seen that for any monitoring scene with high or low noise, the existing motion detection can only use a fixed threshold to judge the foreground pixels in the image, which will make the accuracy of the foreground detection not high, which will make the The accuracy of moving object detection and tracking is not high

Images