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Image registration method based on density clustering

A technology of density clustering and image registration, applied in the field of image processing, to achieve good registration effect, direct method, saving memory and computing power

Active Publication Date: 2022-07-19
ARMY MEDICAL UNIV
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AI Technical Summary

Problems solved by technology

[0005] Registration algorithms based on deep learning have the highest accuracy on specific datasets, but require a large amount of data for training

Method used

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  • Image registration method based on density clustering
  • Image registration method based on density clustering
  • Image registration method based on density clustering

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Embodiment Construction

[0088] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present invention.

[0089] see Figure 1-9 , the present invention provides an image registration method based on density clustering:

[0090] like figure 1 As shown, the image registration method based on density clustering includes:

[0091] S1. Extract the first final feature point set of the template image and the second final feature point set of each frame of the target image.

[0092] Specifically, if the target image is a frame, the S1 includes:

[0093] S11. Extract the first initial feature points of the template image a...

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Abstract

The invention discloses an image registration method based on density clustering, including: an image registration method based on density clustering, comprising: extracting a first final feature point set of a template image and a second final feature of each frame of target image point set; respectively generate description vectors of all the first final feature points in the first final feature point set and all the second final feature points in the second final feature point set; The second final feature points of the target image are matched; the registration parameters are calculated according to all the successfully matched first final feature points and the second final feature points of the current frame target image; the current frame target image is imaged according to the registration parameters. transform. The invention rapidly updates the feature points of the target image frame by frame through the density clustering method, thereby greatly improving the processing speed of registration.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an image registration method based on density clustering. Background technique [0002] The configuration is to select a fixed reference image as a template, an image with a relative offset as the target, and calculate the coordinate offset of the template image through an algorithm, and then make rigid or non-rigid changes to the target image to make the target image. are in the same relative coordinates as the template image. The mainstream algorithms are: registration algorithm based on feature point matching, registration algorithm based on similarity measure, and registration algorithm based on deep learning. [0003] The registration algorithm based on feature point matching is a global search strategy by traversing all pixel points, describing the neighborhood gradient of a certain point and defining points that conform to certain rules as feature points. Good u...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/75G06V10/74G06V10/762G06K9/62
CPCG06F18/23G06F18/22
Inventor 刘伟壹谌小维廖祥
Owner ARMY MEDICAL UNIV
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