Quick binocular stereo matching method based on superpixel segmentation

A binocular stereo matching and super-pixel segmentation technology, applied in the field of binocular stereo vision image processing, can solve the problems of slow calculation speed and poor matching effect

Inactive Publication Date: 2017-05-24
ZHEJIANG UNIV
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AI Technical Summary

Problems solved by technology

The local-based matching algorithm is fast, but the matching effect is poor in low-texture and depth discontinuity areas
The global-based matching algorithm can obtain higher-precision matching results, but the calculation speed is slow

Method used

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  • Quick binocular stereo matching method based on superpixel segmentation
  • Quick binocular stereo matching method based on superpixel segmentation
  • Quick binocular stereo matching method based on superpixel segmentation

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Embodiment Construction

[0056] The present invention will be further described below in conjunction with the drawings and implementation examples.

[0057] The invention provides a fast binocular stereo matching method based on super pixel segmentation, including the following steps:

[0058] 1) Image preprocessing. For the five-dimensional vector of each pixel with the reference image and the target image [l i ,a i ,b i ,x i ,y i ] Respectively do Z-score standardization processing: calculate the mean value x of all pixels in the image separately avg And the standard deviation σ, such as preprocessing the image X:

[0059] Normalize each dimension of each pixel to obtain a new image X′:

[0060]

[0061] 2) SLIC super pixel segmentation. Initialize the clustering center, the initial center of the algorithm is the center of the divided area, that is, according to the given number of areas k=1000, delimit the initial area of ​​the category, and then use a certain step To divide the super pixel, the node at...

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Abstract

The invention discloses a quick binocular stereo matching method based on superpixel segmentation. The method comprises the following steps that: (1) adopting a SLIC (Simple Linear Iterative Clustering) superpixel segmentation method to carry out regional division on an original reference diagram and a target diagram; (2) on the basis of a local matching algorithm of adaptive weighting, calcuating an original parallax spatial diagram; (3) carrying out regional parallax plane fitting based on a confidence point; (4) applying a clustering algorithm to combine adjacent regional parallax planes; and (5) on the basis of a superpixel region, constructing an energy cost function to carry out stereo matching. A stereo matching unit is the superpixel region combined on the basis of the edge information of an image, so that the algorithm is guaranteed to be suitable for a large no-texture region, a depth boundary can be accurately positioned, a matching cost better than the matching cost of a traditional stereo matching method is obtained and is combined with a parallax postprocessing method to effectively obtain a high-accuracy parallax diagram, and the method exhibits good instantaneity.

Description

Technical field [0001] The invention relates to the technical field of binocular stereo vision image processing, in particular to a fast binocular stereo matching method based on super pixel segmentation. Background technique [0002] Binocular stereo vision is a method that simulates the human binocular vision system, based on the principle of parallax and using imaging equipment to obtain two images of the measured object from different positions, and obtain the three-dimensional geometric information of the object by calculating the position deviation between the corresponding points of the image . The binocular stereo vision algorithm mainly includes five parts: image acquisition, camera calibration, image correction, stereo matching and 3D reconstruction. Among them, stereo matching is the core part of the whole algorithm, and the quality of the disparity map generated by the matching directly affects the effect of 3D reconstruction. Due to many factors in the scene, such ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/593G06T7/11G06T7/33G06T7/187
CPCG06T2207/10012
Inventor 刘云海邬亚菲
Owner ZHEJIANG UNIV
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