Template matching method, system and device based on normalized cross-correlation and medium

Abstract

The invention discloses a template matching method, system and device based on normalized cross-correlation and a medium. The method comprises the following steps: constructing a template image pyramid and a target image pyramid with the same layer number according to a template image and a target image; performing rotation processing on each layer of image of the template image pyramid according to a preset angle step length to obtain a plurality of rotation images, and further determining key pixel points; screening out a first matching area with the highest correlation coefficient with the rotation image from a top image of the target image pyramid according to the key pixel points, and determining a first upper left corner coordinate and a first rotation angle; and performing layer-by-layer search on each layer of image of the target image pyramid according to the first upper left corner coordinate and the first rotation angle until a second matching area with the highest correlation coefficient with the rotation image in the bottom layer image is determined. According to the method, the calculation amount of template matching is reduced, the template matching efficiency is improved, the template matching accuracy is also improved, and the method can be widely applied to the technical field of image processing.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a template matching method, system, device and medium based on normalized cross-correlation. Background technique [0002] Template matching is a classic method in the field of computer vision and image processing. By giving a template image and a target image, the similarity between the template image and the candidate window in the target image is calculated, and the candidate window most similar to the template image is the matching result. Therefore, the position of the template image can be accurately found in the target image. [0003] In an ideal state, the pixel value of each point in the region matching the template image in the target image should be equal to the pixel value of the corresponding point in the template image. Therefore, the traditional template matching adopts the method based on the gray value to judge, which sets the discriminant funct...

AI Technical Summary

Problems solved by technology

Although this method is simple and easy to implement, when the target image is affected by light, there will be wrong matching results

[0004] In related technologies, considering the influence of illumination on the target image, the discriminant function is corrected, but at the same time, the amount of calculation is increased, resulting in a decrease in the speed of template matching

Especially after adding rotation interference, although accurate results can be obtained by traversing all angles according to the existing template matching method, the matching speed is slow, the amount of calculation is large, and the efficiency is very low

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