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Video image matching method based on mesh statistical constraints

A technology of statistical constraints and video images, applied in computing, computer components, instruments, etc., can solve problems such as expensive, unsuitable for real-time occasions, and large amount of calculations

Inactive Publication Date: 2019-01-01
GEOVIS CO LTD
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AI Technical Summary

Problems solved by technology

Although consistency is an effective constraint, sparse features lack clear neighborhoods, which makes coherence-based feature matching calculations and complex implementations expensive and computationally intensive, and is not suitable for real-time applications. It is even more unsuitable for the real-time requirements of video for image matching

Method used

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  • Video image matching method based on mesh statistical constraints
  • Video image matching method based on mesh statistical constraints
  • Video image matching method based on mesh statistical constraints

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Embodiment Construction

[0038] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0039] figure 1 A video image matching method based on grid statistical constraints is shown, and its overall process is:

[0040] Step 1. Perform FAST feature point detection on the input reference image Ia and the image to be matched Ib:

[0041] a. Set the threshold h. When the absolute value of the difference between the gray values ​​of two pixels is greater than h, the two pixels are considered to be different;

[0042] b. Select a pixel point P from the picture, and set its density (ie gray value) as Ip;

[0043] c. If among the 16 pixel points around the pixel point P, there are n consecutive points that are different from the pixel point P, then P is a feature point; n is set to 12 in this embodiment;

[0044] d. Efficiently test the feature points obtained in step c to quickly exclude a large number of non-feature points,...

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Abstract

The invention discloses a video image matching method based on mesh statistical constraint. The overall steps are as follows: FAST feature point detection is carried out on the input reference image Ia and the image Ib to be matched; After the feature points are obtained, the descriptor of a feature point is calculated by BRIEF algorithm. M point pairs are selected around the key pixel points P, and the comparison results of m point pairs are combined as descriptors; Searching for the nearest neighbor of each feature point on the image Ib to be matched on the reference image Ia; the two imagesare mesh-processed respectively, and all the mesh are matched. The real-time, super-robust matching method based on mesh statistics of the present invention takes motion smoothness as statistical likelihood of matching in a certain number of regions, and can quickly and reliably distinguish true from false matching, thereby obtaining high-quality matching point pairs.

Description

technical field [0001] The invention relates to a video image matching method, in particular to a video image matching method based on grid statistics constraints. Background technique [0002] Image matching was first proposed in the United States in the 1970s in the application research of aircraft auxiliary navigation systems and terminal guidance of weapon projection systems. Since the 1980s, its application has gradually expanded from the original pure military application to other fields. With the development of science and technology, image matching technology has become an extremely important technology in the field of modern information processing, and has extensive and practical applications in many fields, such as: pattern recognition, automatic navigation, medical diagnosis, computer vision, 3D image reconstruction, remote sensing image processing and other fields. Image matching is the bottleneck problem in these application fields. At present, many important ...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/443G06V10/462G06F18/22
Inventor 吴方才范晓敏白晓辉何晓宁
Owner GEOVIS CO LTD
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