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Three-dimensional matching method based on union similarity measure and self-adaptive support weighting

A technique of similarity measurement and stereo matching, applied in image data processing, instrumentation, computing, etc., can solve problems such as mismatching, difficult to distinguish pixels from their neighbors, etc., to reduce the rate of mismatching, and the implementation method is simple Ease of operation and improved accuracy

Inactive Publication Date: 2012-12-19
ZHONGBEI UNIV
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Problems solved by technology

Since the brightness values ​​of corresponding pixels are not always equal under different lighting, different viewpoints, and noise, it is difficult to distinguish each pixel from its neighbors, so only relying on the pixel Luminance values ​​will mis-match

Method used

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  • Three-dimensional matching method based on union similarity measure and self-adaptive support weighting
  • Three-dimensional matching method based on union similarity measure and self-adaptive support weighting
  • Three-dimensional matching method based on union similarity measure and self-adaptive support weighting

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Embodiment Construction

[0032] The present invention will be further described below in conjunction with the accompanying drawings.

[0033] figure 1 It is a schematic diagram of binocular stereoscopic imaging with a horizontal parallel configuration, where the baseline distance B is the distance between the projection centers of the two cameras, and the focal lengths of the two cameras are both f. Suppose two cameras watch the same object point of the space object at the same time , obtained images of point P on the “left eye” and “right eye” respectively, and their image coordinates are respectively , . Now that the images of the two cameras are on the same plane, the image coordinate Y coordinates of the object point P are the same, that is .

[0034] figure 1 The schematic in simplifies to figure 2 The schematic diagram in is obtained by the similar triangle geometric relation:

[0035]

[0036] Let the disparity be: , from which the three-dimensional position of the space point...

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Abstract

The invention provides a three-dimensional matching method based on union similarity measure and self-adaptive support weighting. The method comprises the following specific steps: (1) correcting an obtained left and right image as a standard image through a correction algorithm; (2) carrying out the three-dimensional matching cost calculation by using the local union phase similarity so as to obtain initial pixel-based matching cost; (3) setting a support weighting for each pixel in a support domain by using a self-adaptive support weighting algorithm, and filtering by using a guide filter so as to obtain smooth matching cost based on a support domain window; (4) selecting a parallax value as a parallax value of the pixel by using a WTA principle while the matching cost value is minimum; (5) carrying out the left and right consistency check and replacing invalid parallax values and filtering; and (6) calculating a depth value of a target object. The method can be applied to fields of computer vision, robot navigation, mode recognition, medical diagnosis, industrial detection, military application, aerial plotting and the like.

Description

technical field [0001] The invention relates to a stereo matching method in the field of computer vision, in particular to a stereo matching method based on a joint similarity measure and an adaptive support weight. Background technique [0002] Binocular stereo vision is an important branch of computer vision. It obtains the left and right views of the same scene through two cameras at different positions, obtains the corresponding image points of each object point in the scene in the left and right views, and obtains the difference between the two image points. The position difference between them is the parallax. Obtaining the corresponding image points in the left and right views is called stereo matching. Stereo matching is the core of binocular stereo vision, and it is also a difficult point. [0003] The current stereo matching algorithms are mainly divided into two categories: global-based and local-based stereo matching algorithms. Global stereo matching algor...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 韩燮韩慧妍杨晓文熊风光
Owner ZHONGBEI UNIV
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