Efficient image retrieval method based on improved SIFT (scale invariant feature transform) feature

An image retrieval and image technology, which is applied in the field of image processing and computer vision, and can solve the problems of feature point mismatch, occupation, and multiple memory.

Active Publication Date: 2016-05-04
BEIJING UNIV OF TECH
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Problems solved by technology

The SIFT feature satisfies the robustness requirements of image retrieval based on the copyright review of digital publications, but the SIFT feature also has many shortcomings, such as the complexity of the algorithm, the number of extracted feature points is too lar...

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  • Efficient image retrieval method based on improved SIFT (scale invariant feature transform) feature
  • Efficient image retrieval method based on improved SIFT (scale invariant feature transform) feature
  • Efficient image retrieval method based on improved SIFT (scale invariant feature transform) feature

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Embodiment Construction

[0029] In order to make the purpose of the present invention, content of the invention and advantages clearer, the following in conjunction with the following in conjunction with the attached Figure 1-2 And embodiment the present invention is described in further detail.

[0030] In the implementation manner, an expanded image library based on the Oxford image library and the Zurich architectural image library is selected as the reference image library, and there are 8,000 images in the library. The library contains not only 50 different types of images and their different types of deformed images, such as rotation transformation, scale transformation, illumination transformation, affine transformation, etc., but also includes a variety of other images to enrich the diversity of the image library . In this embodiment, 50 images of different categories are sequentially used as images to be retrieved. Concrete implementation steps of the present invention are as follows:

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Abstract

The invention discloses an efficient image retrieval method based on an improved SIFT (scale invariant feature transform) feature, relates to the field of image processing and computer vision and belongs to a content-based image retrieval method. The method comprises the steps of establishing a gauss difference scale space, taking scale space detection extreme points as feature points, calculating the direction of the feature points and gradient module values in the direction, generating a global feature vector of the image feature points through a geographical statistical method, conducting global feature vector similarity matching to finish rough retrieval, generating feature descriptors on the basis of rough retrieval, and conducting feature descriptor matching to finish accurate retrieval. The novel image retrieval method is superior to a traditional SIFT algorithm, and is more suitable for requirements of image infringement examination in digital prints than an existing retrieval algorithm.

Description

technical field [0001] The invention relates to the fields of image processing and computer vision, and belongs to a content-based image retrieval method. technical background [0002] With the rapid development of computer technology, communication technology, network technology, streaming media technology and storage technology and other high-tech technologies, digital publishing is booming and has become a strategic emerging industry and the main direction of publishing industry development. At the same time, the protection of intellectual property rights brought about by digital publishing has aroused great attention from the society. If the review of copyright issues is not comprehensive or in-depth, it will likely lead to copyright disputes after digital publications are disseminated. Therefore, the review of infringement issues before digital publications has become an important task for digital publishing houses. In reality, the infringement review of digital public...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/583
Inventor 孙光民王晨阳
Owner BEIJING UNIV OF TECH
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