SIFT-based image feature texture tracking recognition algorithm

A tracking recognition and image feature technology, applied in the field of image recognition, can solve the problems of low accuracy of feature points, mismatch of feature points, quantitative matching degree, etc., to improve the efficiency and accuracy of image recognition, enhance practicability, and expand use. effect of the scene

Pending Publication Date: 2022-01-21
深圳视觉航空科技有限公司
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AI Technical Summary

Problems solved by technology

Although the SIFT algorithm can output the feature point set of the image, there is a problem of feature point mismatch, the matching feature point accuracy is low, and it does not give how to use the output feature point set to quantify the matching degree between two images

Method used

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  • SIFT-based image feature texture tracking recognition algorithm
  • SIFT-based image feature texture tracking recognition algorithm
  • SIFT-based image feature texture tracking recognition algorithm

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Embodiment Construction

[0043] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0044] In describing the present invention, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", The orientations or positional relationships indicated by "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and It is not to indicate or imply that the device or element referred to m...

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Abstract

The invention belongs to the technical field of image recognition, and particularly relates to an SIFT-based image feature texture tracking recognition algorithm. The algorithm comprises the steps of performing feature point extraction on a first image and a second image by using an SIFT algorithm; performing distance calculation, screening and matching on the feature points to obtain a first matching feature point set and a second matching feature point set of which elements correspond to each other; respectively calculating an angle relationship between the feature points in the two matched feature point sets to obtain a first angle set and a second angle set; calculating the difference values of the corresponding angles in the two angle sets , and counting the matching number which does not exceed a preset difference value threshold value in all the difference values; and calculating the ratio of the matching number to the number of the difference values. According to the method, image feature texture tracking identification is realized by eliminating the angle relation between the interference feature points and the calculation feature points, the problem of mismatching of the feature points provided by the SIFT algorithm is solved, the matching degree between the two images is effectively quantified, the image identification efficiency and accuracy are improved, and the practicability is enhanced.

Description

technical field [0001] The invention belongs to the technical field of image recognition, in particular to a SIFT-based image feature texture tracking recognition algorithm. Background technique [0002] SIFT (Scale-invariant feature transform scale-invariant feature transformation) image feature matching algorithm is used to detect and describe local features in images. It looks for extreme points in the spatial scale and extracts its position, scale, and rotation. Invariant, widely used in image search, feature matching, image classification detection, etc., often used in object recognition, robot map perception and navigation, image stitching, 3D model building, gesture recognition, image tracking and action comparison and other fields . Although the SIFT algorithm can output the feature point set of the image, there is a problem of feature point mismatching. The accuracy of the matched feature point is low, and it does not give how to use the output feature point set to...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V10/46G06V10/75G06V40/16G06K9/62
CPCG06F18/22
Inventor 宋学安
Owner 深圳视觉航空科技有限公司
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