Image retrieval method and device, equipment and medium

Abstract

The embodiment of the invention discloses an image retrieval method and device, equipment and a medium, and relates to an intelligent search technology. The method comprises the following steps: extracting global features and local features of a to-be-retrieved image by utilizing a preset neural network model, and extracting global features and local features of a to-be-recalled image; determininga candidate image set through global feature matching and local feature matching between the to-be-retrieved image and the to-be-recalled image; and determining a retrieval result from the candidateimage set by performing local feature verification on the to-be-retrieved image and the candidate images in the candidate image set. According to the embodiment of the invention, the accuracy of imageretrieval under the condition of a large number of database images can be improved, and meanwhile, the retrieval efficiency is ensured.

Description

technical field [0001] The embodiments of the present application relate to computer technology, in particular to intelligent search technology, and in particular to an image retrieval method, device, equipment and medium. Background technique [0002] Image retrieval refers to finding an image result that is exactly the same as the object on the image requested by the user (or called the image to be retrieved), or finding an image that is exactly the same as the image requested by the user in a certain amount of image database. At present, the more common solutions for image retrieval include: a retrieval method based on image feature descriptors to extract image features, and a method for extracting global features of images using a convolutional neural network model for image retrieval. [0003] However, the use of image feature descriptors to extract image features is usually suitable for situations where the angle and illumination changes between images are not very lar...

AI Technical Summary

Problems solved by technology

[0003] However, the use of image feature descriptors to extract image features is usually suitable for situations where the angle and illumination changes between images are not very large, and when the number of images is large, the retrieval efficiency and accuracy cannot be guaranteed; based on convolution The existing image retrieval method of the neural network model, although the retrieval efficiency is relatively high, but the retrieval accuracy is not ideal

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