Image retrieval method based on visual phrases

Abstract

The invention discloses an image retrieval method based on visual phrases in the technical field of computer information processing. The method comprises the following steps of: firstly, extracting salient areas of a standard image and an image to be retrieved, respectively, and extracting characteristic describers from the salient areas; secondly, clustering the characteristic describers in a standard image library by means of a random kd tree; thirdly, representing the characteristic describers of the standard image and the image to be retrieved using visual phrases, respectively, and creating a two-dimensional inverted index according to the visual phases of the standard image; and finally, performing similarity search and space geometrical relationship measurement on the characteristic describers of the image to be retrieved represented by the visual phrases in the two-dimensional inverted index, thus giving a final retrieval result. The method disclosed by the invention reduces the calculation quantity of the retrieval process and improves the instantaneity of retrieval while guaranteeing the accuracy rate of retrieval.

Description

technical field [0001] The invention relates to a method in the technical field of computer information processing, in particular to an image retrieval method based on visual phrases. Background technique [0002] With the lower price of mobile phones with camera functions and the development of the Internet, the acquisition of images has become easier and more convenient, and the number of images has also shown explosive growth. The rapid growth of the number of images poses great challenges and tests to the storage, search and organization of image data. In real life, how to obtain the most useful information from images taken by mobile phones in a large-scale image database has become one of the focuses of people's attention and research. [0003] Image retrieval technology refers to searching in the standard image library and finding relevant images that meet the conditions according to the query image content information or specified query criteria. Most of the tradit...

AI Technical Summary

Problems solved by technology

This method introduces the concept of hierarchy on the basis of K-Means clustering. Although it reduces the time of traditional K-Means clustering, descriptors belonging to the same category are often divided into different categories, and the same category There is no discriminative problem between SIFT descriptors, resulting in greater quantization loss

In the process of querying images to be retrieved, vectorization and inverted index similarity searches are also performed, which also reduces the real-time performance of retrieval

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