Image visual feature point extraction method and related device

Abstract

The invention provides an image visual feature point extraction method and a related device, and the method comprises the steps: carrying out the image division of a visual positioning image, and obtaining a plurality of blocks, wherein an overlapping region exists in the plurality of blocks; performing visual feature extraction on each block to obtain a feature point set corresponding to each block; and combining the feature points with the same coordinate parameters in the overlapping region, and determining a total feature point set corresponding to the visual positioning image according tothe plurality of feature point sets corresponding to the plurality of blocks. The feature points with the same coordinate parameters can be repeatedly extracted from the overlapping region and one feature point in the feature points with the same coordinate parameters is always not close to the block boundary; therefore, by combining the feature points with the same coordinate parameters, the features in the preset range near the feature points can be correctly extracted, and then the visual feature points near the division line can be correctly extracted, so that the accuracy of visual feature point extraction can be improved.

Description

technical field [0001] The present application relates to the technical field of image processing, in particular, to a method for extracting visual feature points of an image and related devices. Background technique [0002] In the visual positioning task, the visual feature points of the image are usually extracted by the visual feature extraction module to complete the visual positioning task. Among them, the effectiveness of visual feature point extraction plays a key role in the accuracy of localization. [0003] At present, before visual feature points are extracted from an image, the image is usually preprocessed (such as dividing the image into a grid), and then the preprocessed image is extracted using a technique (such as SIFT (Scale-invariantfeature transform, Scale-invariant feature transformation), ORB (Oriented FAST and Rotated BRIEF, fast feature point extraction and description algorithm), etc.) to extract visual feature points. Because the existing image p...

AI Technical Summary

Problems solved by technology

Because the existing image preprocessing method is very simple, the visual feature points near the dividing line of the image often have mismatching or failed matching, which leads to a sharp drop in the accuracy of visual positioning or even failure.

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