Image retrieval method, device and apparatus and computer readable storage medium

Abstract

The embodiment of the invention discloses an image retrieval method, device and apparatus and a computer readable storage medium. The method comprises the steps of enabling image pairs in an image database to serve as input, the distance between Hash coding pairs obtained through mapping of the image pairs, enabling the label category and the feature similarity of the image pairs to serve as lossvalues, and adopting a machine learning optimization algorithm to optimize the loss values so as to obtain a deep Hash mapping model through training; mapping the to-be-retrieved image into a to-be-retrieved Hash code by using a deep Hash mapping model; And searching a pre-constructed Hash code library for a target image whose Hamming distance difference with the to-be-retrieved Hash code satisfies a preset condition, outputting the target image as a retrieval result of the to-be-retrieved image in the image database, and mapping each image in the image database through a deep Hash mapping model to obtain the Hash code library. According to the image retrieval method and device, the problem that Hash codes of the same category of images are too consistent in the related art is effectivelysolved, and therefore accurate retrieval of the same category of images is achieved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of image processing, and in particular, relate to an image retrieval method, device, equipment, and computer-readable storage medium. Background technique [0002] In recent years, with the further popularization of the Internet and the in-depth application of big data technology, hundreds of millions of images are generated every day. The concentration of image data resources and the increase in scale make it increasingly difficult for existing technologies to meet the needs of user image retrieval. Therefore, how to effectively describe the feature information of images, and which data structure to use for efficient indexing and fast similarity retrieval have become research hotspots in this direction. [0003] In the face of large-scale image data, given that binary codes are easy to compare and store, it can greatly increase the speed of similarity retrieval and save more computer ...

AI Technical Summary

Problems solved by technology

[0005] However, there is such a problem in the binary codes obtained by this training: the hash codes of the same kind of images are too consistent, so the same kind of images are almost indistinguishable, and it is impossible to distinguish the images that are more similar to the retrieved images, that is to say, the related technology cannot Retrieve images of the same category

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