Method for obtaining compact global characteristic descriptors of images and image searching method

Abstract

The invention provides a method for obtaining compact global characteristic descriptors of images and an image searching method. The method includes obtaining at least one local characteristic descriptor of the images, selecting one or a plurality of local characteristic descriptors, reducing dimensions of the selected local characteristic descriptors to obtain local characteristic descriptors subjected to dimension reduction, converting the local characteristic descriptors which are subjected to dimension reduction into global characteristic descriptors used for expressing image visual characteristics according to first rule, and conducting data compression on the local characteristic descriptors to obtain the compact global characteristic descriptors of the images. Byte size of the global characteristic descriptors can change with change of parameter value in the first rule. The global visual characteristics obtained by the method are more compact and has stretching performance, so that the method overcomes the shortcoming in the prior art of insufficient space of mobile terminals with low internal memory.

Description

technical field [0001] Embodiments of the present invention relate to the field of computers, and in particular to a method for obtaining a compact global feature descriptor of an image and an image retrieval method. Background technique [0002] With the development of smart terminals, there are more and more mobile visual search applications. Currently, image retrieval methods based on intelligent terminals include: 1) extracting local feature descriptors of images on mobile clients; 2) compressing the extracted local feature descriptors; 3) compressing local feature descriptors through the network It is transmitted to the server, so that the server searches the database of the server according to the local feature descriptor, and sends the result of the search to the mobile client. [0003] However, the above-mentioned image retrieval method requires a high amount of computation for local feature compression and establishment of index files such as inversion. In particul...

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Problems solved by technology

[0003] However, the above-mentioned image retrieval method requires a high amount of calculation for local feature compression and establishment of index files such as inversion. In particular, the local feature descriptor obtained in the image retrieval method takes up a large space. Therefore, according to the current network bandwidth , there is a problem that the mobile client cannot send the local feature descriptor to the server quickly

In addition, due to the large space occupied by the local feature descriptor, the process of searching and matching by the server according to the local feature descriptor transmitted by the mobile client is also very slow, which seriously affects the query response time of the retrieval system and reduces the query efficiency.

[0004] In addition, the existing technology also proposes a method for image retrieval using global visual features. In the process of extracting global feature descriptors, the feature dimensionality reduction method and descriptor compression method used in this method require a large amount of storage space for Storage of dimensionality reduction matrices and quantization tables, etc., cannot be realized on mobile terminals with low memory. At the same time, the length of the global feature descriptor is fixed, which cannot be applied to various retrieval conditions, thereby affecting the performance of image search

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