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Computer binocular vision matching method based on global and local algorithms

A binocular vision and matching method technology, applied in mathematics, computing, computer vision, image processing, and numerical fields, can solve problems such as inability to take into account global optimality and local features, and inaccurate matching results

Active Publication Date: 2010-01-13
日照东方缘日用制品有限公司
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Problems solved by technology

[0006] In order to overcome the shortcomings of the existing computer binocular stereo vision matching method that cannot take into account the global optimum and local features, and the matching results are inaccurate, the present invention provides a method that can take into account the global optimum and local features and obtain more accurate matching results. Computer Binocular Stereo Vision Matching Method Based on Global and Local Algorithms

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  • Computer binocular vision matching method based on global and local algorithms
  • Computer binocular vision matching method based on global and local algorithms
  • Computer binocular vision matching method based on global and local algorithms

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Embodiment Construction

[0045] The present invention will be further described below in conjunction with the accompanying drawings.

[0046] refer to figure 1 , a computer binocular stereo vision matching method based on global and local algorithms, said computer binocular stereo vision matching method comprising the following steps:

[0047] (1), using the graph cut method to obtain a layered matching result for the left and right images obtained by the binocular stereo vision sensor;

[0048] (2), using the window matching method of different window sizes to obtain multiple different local matching results in a small field of the global matching results;

[0049] (3) Place the multiple local matching results in a Markov random field with a second-order smooth energy function and use the QPBO algorithm for iterative optimization to obtain matching results.

[0050] Global matching process: A good global matching result is the basis of subsequent optimization algorithms. In the algorithm described...

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Abstract

The invention relates to a computer binocular vision matching method based on global and local algorithms, which comprises the following steps: (1) obtaining a layered matching result from a left image and a right image which are obtained by a binocular three-dimensional vision sensor by using an image cutting method; (2) obtaining different local matching results in a local matching result by using a window matching method with different windows; (3) putting the local matching results into a markov random field with a second-order smooth energy function for iterating and optimizing to obtain the matching result. The computer binocular vision matching method can integrate global optimized and local characteristics and obtain a more accurate matching result.

Description

technical field [0001] The invention relates to the fields of image processing, computer vision, calculation method, mathematics and numerical method, especially the binocular image matching method of computer vision. Background technique [0002] At present, the research on stereo vision matching problem has made great progress. Especially the matching algorithm based on global optimization has become the main method to solve the matching problem and has been widely used. The reason it has received so much attention is because the matching problem can be well modeled as an optimization problem of Markov Random Field (MRF) or Conditional Random Field (CRF). This type of problem has been designed in many disciplines, and many of the resulting algorithms can be used to solve matching problems, such as Graph Cuts (1, Y.Boykov, O.Veksler, and R. Zabih, "Fast approximate energy minimization via graph cuts", IEEE Transaction on Pattern Analysis and Machine Intelligence, 2001, 23...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 陈胜勇王中杰刘盛管秋毛国红
Owner 日照东方缘日用制品有限公司
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