Image matching method based on gradient magnitude random sampling

Abstract

The invention discloses an image matching method based on gradient magnitude random sampling, and the method comprises the following steps: s1, intercepting a region of interest for a target detection image, and obtaining a first template image; s2, preprocessing the first template image to obtain a binary string of template image sampling point pairs; s3, moving pixel points of the to-be-matched image by a step length, and generating a binary string of sampling point pairs of the to-be-matched image from the moved to-be-matched image according to the method in the step S2; s4, obtaining the position of the minimum distance in the target detection image according to the minimum distance between the binary string of the to-be-matched image sampling point pair and the binary string of the template image sampling point pair; s5, mapping the position of the minimum distance in the target detection image to the target detection image by adopting the sampling relation of the image pyramid to obtain an accurate target position, and ending the matching. According to the invention, the problem of inaccurate accurate positioning of the target area in vision-based product detection is solved.

Description

technical field [0001] The present invention relates, in particular, to an image matching method based on gradient amplitude random sampling. Background technique [0002] In product defect detection using visual images, the detection area needs to be positioned first. Since the production line is in motion, and the on-site lighting may also be affected by the environment, certain changes may occur. Therefore, there are certain differences in the images taken during each detection. This difference leads to the possibility that the positioning accuracy of the detection area may not meet the actual detection requirements. In addition, when the product is in the state of online motion, there may be a certain angle of rotation, which may also lead to insufficient positioning accuracy. As an important step in the image preprocessing stage of visual inspection, accurate positioning of the detection area has a crucial impact on the accuracy of visual inspection in the later stag...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides an image matching method based on gradient amplitude random sampling, which solves the problem of inaccurate positioning of the target area in vision-based product detection

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