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Method for quickly extracting sift features based on optimal space, computer equipment and storage medium

An extraction method and fast technology, applied in the field of image processing, can solve the problem of low efficiency in SIFT feature extraction, and achieve the effect of improving the efficiency of extraction and matching

Active Publication Date: 2022-05-27
JILIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a method for quickly extracting SIFT features based on an optimal space, aiming at solving the problem of low efficiency in extracting SIFT features of images in the prior art.

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  • Method for quickly extracting sift features based on optimal space, computer equipment and storage medium
  • Method for quickly extracting sift features based on optimal space, computer equipment and storage medium
  • Method for quickly extracting sift features based on optimal space, computer equipment and storage medium

Examples

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specific Embodiment 1

[0137] In this application, coin images in the application scenario of coin contamination detection are used for experiments. Some sample images are as follows: figure 1 As shown, the coins in (a)-(h) are placed at different angles. All images are 1600×1200 in size. First, based on the method proposed in this application, the preferred feature space is determined; then, the efficiency of SIFT feature extraction, matching and registration based on the preferred feature space is verified.

[0138] This application uses 10 coin images to determine the preferred feature space for SIFT features. For the coin fouling detection application scenario, the coins are the same size in the image. Therefore, the image normalization step is omitted.

[0139] According to formula (1), O=10 is obtained from the image size. Considering that when the image resolution is small, the details of the image content cannot be distinguished, so take O=7. In addition, it is assumed that S=3. Thus t...

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Abstract

The invention discloses a method for quickly extracting SIFT features based on a preferred space, comprising the steps of: obtaining a learning sample set for determining a preferred feature space; determining a preferred feature space according to the learning sample set; The number of registration features is arranged in order; based on the preferred feature space, SIFT feature extraction and matching are performed on the known image and the image to be matched; when the number of registration features of the known image and the image to be matched meets the preset requirements, the image to be matched The match was successful. First determine the optimal feature space corresponding to the learning sample set, and the feature space layers in the optimal feature space are arranged in sequence according to the number of registration features of the feature space layer, and then based on the optimal feature space, SIFT feature extraction and match. In this application, the extraction and matching of SIFT features are concentrated in the preferred feature space, which can significantly improve the efficiency of SIFT feature extraction and matching.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for fast extraction of SIFT features based on a preferred space. Background technique [0002] Computer vision is the use of computers to simulate human visual functions to achieve tasks such as classification, measurement, localization, and detection. Feature point extraction and description is one of the important image analysis techniques for computer vision, which is widely used in medical image analysis, remote sensing image analysis, image retrieval and visual positioning applications. By comparing the features at the position of the feature points and the spatial relationship of the feature points, the problems of grayscale change, scale change and angle change of the image are overcome, and the measurement, positioning and detection of objects are realized. The SIFT algorithm is a classic method based on feature point matching. [0003] The SIFT algori...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/46
CPCG06V10/462
Inventor 陈绵书张雅琦张子墨李晓妮桑爱军
Owner JILIN UNIV