Stereo matching method based on graph cut

A technology of stereo matching and graph cut algorithm, which is applied in image analysis, image data processing, instruments, etc. It can solve the problems of poor real-time performance and long matching time, so as to reduce the amount of calculation, improve real-time performance, and improve matching accuracy Effect

Inactive Publication Date: 2016-03-16
NANJING UNIV OF SCI & TECH
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Problems solved by technology

In the global matching algorithm, the graph cut algorithm (see the literature Y.Boykov, O.Veksler, R.Zabih.FastApproximateEnergyMinimizationviaGraphCuts.IEEE, TransonPatternAnalysisandMachineIntelligence, 2001, 23(11):1222~1239), confidence extension propagation (BeliefProgramm , BP) (see literature SunJian, ZhengNanning, ShumYH.StereoMatchingUsingBeliefPropagation.IEEE, TransactiononPatternAnalysisandMachineIntelligence, 2003,25(7):787~800) and dynamic programming (DynamicProgramming, DP) (BAKERHH.Depthfromedgeandintensitybasedstereo-398 The entire image is effectively constrained, and the matching result is more accurate than the local matching algorithm, but the real-time performance is not good, and the matching time is too long

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  • Stereo matching method based on graph cut

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Embodiment Construction

[0017] combine figure 1 , the present invention is a stereo matching method based on graph cut, the steps are as follows:

[0018] Step 1. Obtaining more support points is the first step of the present invention. If the support points are too few or unevenly distributed, it will seriously hinder the accurate acquisition of dense parallax later. The present invention uses the MSERDoG operator to extract support points from the left and right images, and the operator can extract more support points even in areas where the texture is not rich.

[0019] The MSERDoG operator is to extract the maximum stable extremal regions MSER (maximallystableextremalregions) in the Gaussian difference DoG (differenceofGaussian) space. First, Gaussian convolution is performed on the image to obtain the scale space, and then two adjacent frames of images in the scale space are subtracted to obtain the Gaussian difference space. In the Gaussian difference space, the value of each pixel reflects t...

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Abstract

The invention proposes a stereo matching method based on graph cut. The method comprises the steps: extracting supporting points from left and right images through employing an MSERDoG operator; enabling the pixel gray values of the supporting points to serve as matching cost and fixed windows which are used as cost aggregation for the matching of the supporting points of the left and right images, and obtaining the parallax of the supporting points; calculating a DAISY descriptor operator of each pixel of the left and right images; enabling the parallax of the supporting points to serve as a symbol in graph cut, and enabling the DAISY descriptor operator of each pixel to serve a data item of an energy function in a graph cut algorithm, wherein the data item is used in the in a graph cut algorithm; finally solving a dense parallax graph through solving the minimum value of the energy function, and achieving stereo matching. The method can improve the matching efficiency under the condition of guaranteeing the imaging matching precision.

Description

technical field [0001] The invention belongs to the field of stereo matching of images in binocular stereo vision, and in particular relates to a stereo matching method based on graph cuts. Background technique [0002] Stereo matching is the most important and difficult part of binocular stereo vision and the core technology of 3D reconstruction. Stereo matching is actually the process of looking at the same scene from different viewpoints for the left and right cameras, and finding corresponding points in the overlapping areas of the left and right images. It uses the imaging model of the spatial object point in the left and right cameras to obtain the process of imaging parallax. The stereo matching algorithm is decomposed into four steps: matching cost calculation, matching cost aggregation, disparity calculation, and disparity refinement. According to different constraints, stereo matching algorithms can be divided into regional matching algorithms and global matching...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 钱惟贤李娇周骁骏刘琳吕芳顾国华陈钱徐富元任建乐任侃呙星田杰王伟杰
Owner NANJING UNIV OF SCI & TECH
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