Beaconing-free vision measuring-technique for moving target based on time-space correlative characteristics

Abstract

The invention relates to a beaconing-free vision measuring-technique for a moving target based on time-space correlative characteristics, which belongs to the technical field of vision measuring, aims at overcoming shortages and shortcomings in the prior art and providing a moving target identifying and detecting technique which the beaconing-free vision measuring-technique, namely, a signal marker is not needed on a target motion body in advance. When in technique realization, the time-space correlative characteristics of motion pixels are considered at the same time, a background image difference method and an inter-frame image difference method are combined together to identify the moving target, so that the disadvantages thereof are overcome effectively, the self-adaptive ability is strong, the speed is high, the antinoise effect is good proved by experiments, and the moving target can be better detected from video images.

Description

technical field [0001] The invention belongs to the technical field of visual measurement, and relates to a beacon-free moving target recognition technology utilizing time-space correlation features. Background technique [0002] There are three basic methods for the common visual measurement technology of moving targets: background image difference method, frame difference method and optical flow method. The position of the moving target detected by the background image difference method is accurate and fast. However, in practical applications, because the two images to be compared are taken at different times, they are easily affected by natural factors such as illumination changes, wind, and other human factors. . Moreover, in some cases, the gray value of some pixels in the area occupied by the research object on the image may be the same as the gray value of the background pixel on the corresponding area in the reference image. At present, research on background recon...

AI Technical Summary

Problems solved by technology

The position of the moving target detected by the background image difference method is accurate and fast. However, in practical applications, because the two images to be compared are taken at different times, they are easily affected by natural factors such as illumination changes, wind, and other human factors.

Moreover, in some cases, the gray value of some pixels in the area occupied by the research object on the image may be the same as the gray value of the background pixel on the corresponding area in the reference image

At present, research on background reconstruction has been carried out in order to reduce the impact of dynamic scenes on accurate segmentation, but these methods are not perfect; the inter-frame difference method only detects relatively moving objects, because the time interval between two images is short, The differential image is less affected by light changes, and the detection is effective and stable

But this kind of method has two defects: (1) The overlapping part of the object between two frames is not detected, that is, only a part of the object is detected, and a hole is formed in the middle of the object; (2) The position of the detected object is not accurate, and its circumscribed The rectangle is stretched in the direction of motion, and the detected target is larger than the real object; the advantage of the optical flow method is that it can detect independently moving objects without knowing any information about the scene in advance. The disadvantage is that the calculation formula is complex and the amount of calculation Large, it is difficult to meet real-time requirements without special hardware support

This method of using beacon identification not only has high requirements on the hardware environment, but also the beacons often have problems such as failure, cover, and shedding, which ultimately have a great impact on the identification of moving targets.

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