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Method for eliminating Brisk (binary robust invariant scale keypoint) error matching point pair by utilizing RANSAC (random sampling consensus)

A technology for matching point pairs and wrong matching, which is applied in image data processing, instruments, calculations, etc., can solve the problems of reducing key point repeatability and wrong matching, and achieve high matching speed, high quality, and improved matching accuracy.

Active Publication Date: 2013-11-20
INST OF OPTICS & ELECTRONICS - CHINESE ACAD OF SCI
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Problems solved by technology

However, due to environmental factors and other influences, there will be a mismatch between multiple points corresponding to one point, thereby reducing the repeatability of key points

Method used

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  • Method for eliminating Brisk (binary robust invariant scale keypoint) error matching point pair by utilizing RANSAC (random sampling consensus)
  • Method for eliminating Brisk (binary robust invariant scale keypoint) error matching point pair by utilizing RANSAC (random sampling consensus)
  • Method for eliminating Brisk (binary robust invariant scale keypoint) error matching point pair by utilizing RANSAC (random sampling consensus)

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Embodiment Construction

[0036] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. This embodiment is carried out on the premise of the technical solution of the present invention, and the detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

[0037] The invention is based on Brisk (Binary Robust Invariant Scale Keypoint) key point detection, description and matching, and the input image is a data set published on the Internet.

[0038] Such as figure 1 As shown, the present invention provides a method of using RANSAC (Random Sampling Consensus) to eliminate Brisk (Binary Robust Invariant Scale Keypoint) key point mismatch point pairs, including the following steps:

[0039] Step 1. Image preprocessing. Due to defects in lighting or imaging systems, acquired images to be processed will be affected by noise, thereby affecting su...

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Abstract

The invention provides a method for eliminating a Brisk (binary robust invariant scale keypoint) error matching point pair by utilizing RANSAC (random sampling consensus). The method comprises the following steps: firstly, preprocessing images to be processed by adopting Gaussian smooth filter, so as to remove the influence of noise on a follow-up algorithm; secondly, carrying out keypoint detection, description and matching on the above two smoothed images by adopting the Brisk, so as to obtain the matching point pair; and finally, further processing the obtained matching point pair by utilizing the RANSAC, so as to eliminate the error matching point pair, so that the matching precision is improved. Compared with the method for detecting, describing and matching the keypoint only by utilizing the Brisk, the method provided by the invention has the advantage that the matching precision is further improved on the basis of keeping the high-speed matching and calculation speed in the original method; and the method provides a foundation for follow-up high-precision tracking.

Description

technical field [0001] The present invention relates to a method for improving matching accuracy, especially a method for eliminating wrong matching point pairs of Brisk (Binary Robust Invariant Scale Keypoint) key points by using RANSAC (Random Sampling Consensus), thereby improving the matching accuracy. It is mainly used for image processing, computer vision, object recognition and matching, 3D scene reconstruction, and object tracking. Background technique [0002] Decomposing an image into local regions of interest or 'features' is a widely used technique in computer vision. Image representation, object recognition and matching, 3D scene reconstruction, and motion tracking all rely on stable, expressive features in images, which have led to increasing research on feature extraction methods. [0003] An ideal keypoint detector finds salient regions of the image so that it can still be detected repeatedly when viewing angle changes; more generally, it is robust to all im...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 胡锦龙彭先蓉魏宇星李红川
Owner INST OF OPTICS & ELECTRONICS - CHINESE ACAD OF SCI
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