Multi-scale analysis based image feature bag constructing method

A multi-scale analysis and image feature technology, applied in the field of computer vision, which can solve problems such as insufficient image detail and texture representation

Inactive Publication Date: 2015-08-19
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

[0004] Local feature extraction and visual dictionary establishment are the two most critical steps in the feature bag model. Currently, the most commonly used local features include features based on image blocks (Patches) and features based on key points (Key Points). Among them, SIFT The local features based on key points are more

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  • Multi-scale analysis based image feature bag constructing method
  • Multi-scale analysis based image feature bag constructing method

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Embodiment Construction

[0015] Specific embodiments of the present invention will be described below in conjunction with the accompanying drawings, so that those skilled in the art can better understand the present invention. It should be noted that in the following description, detailed descriptions of known functions and designs that may dilute the main content of the present invention will be omitted.

[0016] figure 2 It is a technical scheme diagram of an image feature package construction method based on multi-scale analysis in the present invention.

[0017] In this embodiment, a feature package construction method based on multi-scale analysis of the present invention mainly includes the following links: 1. Multi-scale decomposition, 2. Feature extraction, 3. Generate visual dictionary, 4. Generate image feature package, 5. Image classification test.

[0018] The multi-scale decomposition link is mainly realized by performing wavelet transform on the original image. The wavelet transform d...

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Abstract

The invention provides a multi-scale analysis based image feature bag constructing method through introducing a multi-scale analysis concept of images into a feature bag model. The method comprises the steps of firstly carrying out decomposition on an image by using wavelet transformation, then respectively extracting local area features of a high-frequency sub-band and a low-frequency sub-band of the image, constructing a high-frequency visual dictionary and a low-frequency visual dictionary respectively, then describing the image by using the visual dictionaries, and generating an image feature bag. The method provided by the invention focuses on the level of multi-scale feature extraction and semantic description of the image, detail information in the image can be better captured so as to generate visual feature vocabularies, and the new feature bag model can be specifically applied to classification, retrieval and the like of digital image data such as medical images, remote sensing images, network images and the like.

Description

technical field [0001] The invention belongs to the field of computer vision, and more specifically relates to a feature bag construction method based on multi-scale analysis. Background technique [0002] With the progress of the information age, digital images, as an important carrier of information, have shown explosive growth in number. While massive digital image data brings great convenience to people's information collection, transmission and acquisition, it also makes the classification, storage and retrieval of information face many new difficulties. How to analyze, identify and obtain useful information more quickly and accurately from the vast image data is one of the most important research topics in the field of computer vision. [0003] The early image classification and identification were mainly done manually, using the text information attached to the image for classification and retrieval. However, with the geometric increase in the number of images and th...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/23213G06F18/2411
Inventor 秦志光王伟秦臻丁熠肖哲黄若菡张聪陈浩陈圆徐路路
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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