Fast high-precision geometric template matching method enabling rotation and scaling functions

Abstract

The present invention provides a fast high-precision geometric template matching method enabling rotation and scaling functions. According to the method, based on image edge information, with the sub-pixel edge points of a template image adopted as feature points, the tangent directions of the gradient directions of a target image adopted as feature lines, and based on the local extremum points of a similarity value, the similarity and the candidate positions of the template image and the target image are calculated from fine to rough through adopting a Pyramid algorithm and according to a similarity function; and pixel-level positioning accuracy is obtained at the bottommost layer of a Pyramid, the least squares method is adopted to carry out fin adjustment, so that sub-pixel positioning accuracy, higher-precision angle and size scaling accuracy can be achieved. The method can realize fast, stable and high-precision positioning and identification of target images which are moved, rotated, scaled and is partially shielded, and where the brightness of illumination changes, illumination is uneven, and cluttered background exists. The method can be applied to situations which require machine vision to carry out target positioning and identification.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a fast and high-precision geometric template matching method. Background technique [0002] Existing template matching generally adopts an algorithm based on grayscale correlation, using image grayscale as matching information, and measuring the matching degree by calculating the grayscale correlation coefficient between the template image and the sub-region of the target image; some algorithms use edge features or generalized Huo The other is to calculate the invariant moment of the image and use the information of the moment for matching. [0003] Patent Document 1 (Chinese Patent Publication No. CN10556695A) discloses a grayscale template matching algorithm based on NCC (Normalized Cross Correlation); Patent Document 2 (Chinese Patent Publication No. CN100483283C) discloses a two-dimensional positioning device based on machine vision , the digital camera is installe...

AI Technical Summary

Problems solved by technology

Although the method proposed by Wang Ke has high accuracy, it takes too long to deal with the positioning of large rotation angle targets

Most of other public target positioning methods based on geometric features can only provide pixel-accurate position information, and some methods can provide rotation angle parameters. How to calculate sub-pixel-accurate position coordinates and scaling factors are not mentioned in the above materials. public

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