Image search method based on space symbiosis of visual words

Abstract

The invention provides an image search method based on space symbiosis of visual words. The image search method comprises the following steps of: counting the symbiosis probability between any two visual words in a training database, and constructing a visual word symbiosis table; extracting a size constant characteristic of an input query image; randomly selecting the partial characteristic from the size constant characteristic as a central characteristic, and performing precise mapping on the central characteristic; counting neighboring characteristics in an affine constant region of the central characteristic; forecasting candidate visual words for the neighboring characteristics through a high-order probability forecaster according to the visual word symbiosis table and a precise mapping result; and comparing distances between the candidate words and the size constant characteristic, determining the optimal visual word, and performing image search. By the symbiosis of the visual words, the visual words can be produced effectively and quickly, and image search can be performed.

Description

technical field [0001] The invention belongs to the technical field of image retrieval and high-dimensional data search, and relates to an image retrieval technology based on a bag-of-words model, in particular to an image retrieval method utilizing the spatial symbiosis of visual words. Background technique [0002] In content-based image retrieval systems, images are represented as a collection of scale-invariant local features. By clustering and quantifying image features in the database, a visual dictionary can be obtained. The features of any new image can be mapped to corresponding visual words according to this visual dictionary, and the image is represented as a bag of visual words, which is the generation of the bag of words model. How to map image features to corresponding visual words, that is, the so-called visual word generation stage, is an important part of the bag-of-words model, and its time and accuracy directly determine the retrieval efficiency and effec...

AI Technical Summary

Problems solved by technology

[0010] Although the above algorithm has been well applied in the traditional problem of finding approximate nearest neighbors, for the process of mapping image features to visual dictionaries, the above methods all establish an ordered index on the visual dictionary, and then put each image feature in this index Searching above separately does not consider the correlation between image features (R.Xu, M.Shi, B.Geng, C.Xu. Fast visual word assignment via spatial neighborhood boosting[C].In Proc.ICME, pages 262–270, 2011.)

Images