Automatic registration of FPC images based on SURF features and hash perception algorithm

Abstract

Automatic registration of FPC images based on SURF features and hash perception algorithm. The invention discloses a FPC image registration method based on SURF feature and hash perception algorithm,including: first selecting the template image and ROI area, selecting four rectangular regions within the ROI region, matching the rectangular region and the SURF feature points of the image to be registered is realized by using force matching or FLANN, checking the similarity of the rectangular region around the matched feature points by using perceptual hashing algorithm, and finding four pairsof matched feature points to generate perspective transformation matrix, and then registering the image to be registered by perspective transformation. The invention verifies the matched SURF characteristic points by using the perceptual hash algorithm, greatly improves the matching accuracy of the SURF characteristic points, simultaneously establishes a perspective transformation matrix by usingthe matched characteristic points, and completes the image registration by using the perspective transformation and obtains a better effect.

Description

technical field [0001] The invention relates to machine vision and image processing technology, in particular to an FPC image automatic registration method based on SURF feature and hash perception algorithm. Background technique [0002] Image registration refers to the process of best matching two or more images obtained from different sensors at different times. In the process of image registration, one image is usually designated as the reference image, and the other image is the image to be registered. The purpose of registration is to make the coordinates of the image to be registered consistent with the reference image through some geometric transformation. [0003] According to the difference of image information used in image registration, the existing image registration methods can be summarized into three categories: methods based on gray information, methods based on transform domain and methods based on features. The basic idea of ​​the registration method base...

AI Technical Summary

Problems solved by technology

[0004] To sum up, the existing methods are all oriented to a specific range of application fields, and also have their own characteristics and application scenarios. In the FPC image registration scenario, repeating similar texture structures will greatly reduce the accuracy of SURF feature point matching.

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