Image stereo matching method, binocular vision equipment

Abstract

The invention discloses an image stereo matching method and a binocular vision device. The method comprises steps: stereo matching cost calculation is carried out on a reference pixel point in a firstphotographed image and multiple to-be-matched pixel points in a second photographed image to determine a matching cost value of the reference pixel point and each to-be-matched pixel point, wherein the first image and the second image are images photographed by different cameras of the binocular vision device towards the same scene; a matching point for the reference pixel point is screened fromthe multiple to-be-matched pixel points; and whether the screened matching point is stable is judged according to a matching cost curve, an instable matching point is replaced, and a disparity map isobtained. The technical scheme can effectively improve foreground expansion effects of the disparity map, the operation efficiency is improved, instable matching points are removed through adopting amedian filter method, the disparity map precision can be enhanced, and edge details of the disparity map can also be kept.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image stereo matching method and a binocular vision device. Background technique [0002] Stereo matching (Stereo Matching) is a technique for recovering depth information from planar images, and it is also the basis of computer vision theory and applications. The binocular stereo matching system simulates the principle of human visual perception, uses two digital cameras installed on the same horizontal line, and finds matching corresponding points from images from different viewpoints. It is widely used in industrial production automation, assembly line control, unmanned vehicles (ranging, navigation), security monitoring, remote sensing image analysis, robot intelligent control, etc. [0003] Although many domestic and foreign scholars have conducted in-depth research on this field, there are many mature stereo matching methods, but on the one hand, these methods ...

AI Technical Summary

Problems solved by technology

[0003] Although many domestic and foreign scholars have conducted in-depth research on this field, there are many mature stereo matching methods, but on the one hand, these methods are sensitive to noise, and the obtained disparity map will have foreground expansion effect, and the processing of small objects There are also obvious deficiencies in

On the other hand, these methods mostly use the traditional sliding window method, which greatly increases the running time

In addition, many methods do not optimize the disparity map. Even if they do, they only use the relatively inefficient double check for processing, and cannot achieve both accuracy and speed.

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