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Image retrieval method based on BoVW (Bag of Visual Words) optimization and query expansion

A visual dictionary, query expansion technology, applied in character and pattern recognition, special data processing applications, instruments, etc., can solve problems such as poor anti-interference ability and low retrieval accuracy

Inactive Publication Date: 2016-11-23
HUAQIAO UNIVERSITY
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AI Technical Summary

Problems solved by technology

[0007] The present invention overcomes the problems of low retrieval accuracy and poor anti-interference ability in the current image retrieval in the prior art, and provides an image retrieval method based on visual dictionary optimization and query expansion for the purpose of improving image retrieval accuracy

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  • Image retrieval method based on BoVW (Bag of Visual Words) optimization and query expansion
  • Image retrieval method based on BoVW (Bag of Visual Words) optimization and query expansion

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Embodiment Construction

[0060] Specifically, the invention will be described in three parts as follows, including: implementation premise, detailed implementation mode, specific operation process and specific examples. The premise of the first part includes the establishment of a visual dictionary model; the second part corresponds to the steps of the present invention, giving the overall process and the specific operation method of each step; the third part gives a specific example and analyzes the obtained results.

[0061] 1. Building a visual dictionary model

[0062] An image has hundreds or thousands of local features. If an index is built with a single local feature as a unit, all local features need to be matched one by one during retrieval. This not only greatly increases the retrieval time overhead, but also affects the practicability of the system. . In order to reduce the time cost of image retrieval, Sivic et al. proposed a visual dictionary method (Bag of Visual Words, BoVW) by referri...

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Abstract

The invention discloses an image retrieval method based on BoVW (Bag of Visual Words) optimization and query expansion. The image retrieval method comprises: extracting SIFT features of a training image, and carrying out clustering on the SIFT features by utilizing a density-based clustering method to generate a BoVW set; analyzing correlation of visual words and a target category by a chi-square model, and simultaneously, filtering out a certain number of visual stop words by combining word frequencies of the visual words; carrying out mapping matching on the SIFT features and an optimized BoVW to obtain a visual word histogram; carrying out similarity matching on a visual word histogram of an query image and the visual word histogram of the training image, and according to a primary matching result, carrying out secondary or repeated retrieval by combining a query expansion strategy so as to obtain a final retrieval result. The invention provides the image retrieval method based on BoVW optimization and query expansion, which aims to improve image retrieval accuracy.

Description

technical field [0001] The invention relates to an image retrieval method, in particular to an image retrieval method based on visual dictionary optimization and query expansion. Background technique [0002] The visual dictionary method (Bag of Visual Words, BoVW) quantifies the local features of the image into word frequency vectors for retrieval through the visual dictionary, which can not only use the local information of the image, but also achieve a faster speed than the direct retrieval of local features, and has become the current image retrieval method. mainstream method. However, the image retrieval method based on BoVW has the following problems: First, the current clustering algorithm for generating visual dictionaries has low time efficiency and a large amount of calculation, which makes it difficult for BoVW to be applied to large-scale data sets; second, due to the limitations of clustering algorithms and image The existence of background noise causes visual ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/583G06F18/23
Inventor 李弼程柯圣财赵永威杜吉祥刘海建
Owner HUAQIAO UNIVERSITY
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