Multi-layer template adaptive matching target tracking method for infrared image

Abstract

The invention provides a multi-layer template adaptive matching target tracking method for an infrared image, and belongs to the field of image processing. The method comprises the steps: obtaining an infrared image, and carrying out the image enhancement preprocessing of the infrared image, and obtaining a first layer of an image feature pyramid; manually marking a target position on the infrared image, namely giving a target frame of a first frame; extracting images of different layers in a target frame on the infrared image by using a feature pyramid algorithm: carrying out target search on each layer by using an SSDA template matching algorithm, frame-selecting the maximum possible position of the target, and recording confidence and target moving position information at the same time; judging the confidence coefficient through an error function, and if scale change occurs, determining a new template; if morphological transformation occurs, updating the template in time; and if shielding occurs, enlarging the search area. According to the method provided by the invention, the effective features of the target can still be stored when the target is subjected to scale change, form change and shielding, and good tracking is kept.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a multi-level template adaptive matching target tracking method for infrared images. Background technique [0002] With the development of intelligence, images have become an important means of obtaining information. In image acquisition, image processing is a very important link. Image processing technology has been widely used in various fields such as industrial safety and medical management. In image processing, the detection and tracking of moving objects is the focus of image processing technology, and image processing and tracking algorithms are generally used to achieve detection and tracking processing. [0003] The current traditional image processing tracking method uses template matching algorithm. Conventional template matching algorithms tend to lose targets when faced with scale changes, shape changes, and occlusions of targets. The existing template matching tra...

AI Technical Summary

Problems solved by technology

Conventional template matching algorithms tend to lose targets when faced with target scale changes, shape changes, and occlusions

The disadvantages of the existing template matching tracking algorithm are as follows: the target cannot be continuously tracked when its shape changes; the target cannot be continuously tracked when its scale changes; and the target cannot be continuously tracked when it is blocked.

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