Fuzzy clustering based image retrieval method

A fuzzy clustering and picture technology, applied in the field of information retrieval, can solve problems such as failure to reach real-time retrieval, retrieval load and response time increase, and achieve the effect of satisfying real-time retrieval, ensuring retrieval efficiency, and narrowing the scope

Active Publication Date: 2015-01-21
BEIHANG UNIV
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AI Technical Summary

Problems solved by technology

The results of image retrieval come from the collected image library. If it is to meet the needs of different visitors, or apply to the retrieval input of different types of images, the size of the image library needs to be large enough to ensure the accuracy of retrieval, but too large The image library doubles the retrieval load and response time, which cannot meet the requirements of real-time retrieval

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Embodiment Construction

[0035] The technical content of the present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0036] The present invention provides a method for image retrieval based on fuzzy clustering, which includes the following steps: first select an appropriate number of representative points according to the similarity calculation model on which the image library depends and the density of the image distribution in the high-dimensional feature space, These representative points themselves can also be pictures, to ensure that the higher the degree of image aggregation, the greater the number of representative points. On the contrary, the lower the degree of image aggregation, the less the number of representative points. The relative distance of the representative points should be as high as possible according to the density. Separate, to ensure that other pictures can reflect enough tendency when categorized; after selecting repr...

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Abstract

The invention discloses a fuzzy clustering based image retrieval method. The fuzzy clustering based image retrieval method comprises the following steps of S11, establishing a characteristic value library for images in an image library and numbering the images ; S12, selecting N images with image separation distances larger than a distance threshold value A1 from the image library and conducting first-time classification on the residual images to form N categories of image sets; S13, conducting the step S12 on the image sets with image quantities larger than a quantity threshold value in the N categories of image sets till the image quantity of each image set is smaller than the quantity threshold value and obtaining M representative points; S14, partitioning all images in the image library into the image sets represented by highest-similarity-level representative points according to similarity levels between the images and the M representative points; S15, conducting characteristic valuing on input images to be retrieved, respectively calculating the similarity levels between the input images and all representative points and selecting a plurality of highest-similarity-level representative points to perform retrieval. The fuzzy clustering based image retrieval method narrows a retrieval range on the basis that retrieval efficiency is ensured, and reduces retrieval working amount.

Description

Technical field [0001] The invention relates to a picture retrieval method, in particular to a picture retrieval method based on fuzzy clustering, and belongs to the technical field of information retrieval. Background technique [0002] Picture is one of the important presentation forms of multimedia information. It visualizes and presents abstract data to the public intuitively and vividly through rich visual features such as color, texture, and shape. With the increasing convenience of Internet information dissemination and the continuous improvement of mobile terminal functions, image information will become another major information carrier after text, which is widely used in information retrieval, data mining, human-computer interaction and other fields. However, due to the complex information contained in the picture itself, the strong environmental relevance, the difficulty of high-level semantic abstraction, the large amount of retrieval mode calculations and the imperf...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/5838
Inventor 刘瑞左源张辉
Owner BEIHANG UNIV
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