Image feature extraction method and device, equipment and storage medium

Abstract

The invention relates to the technical field of artificial intelligence, and discloses an image feature extraction method and device, equipment and a storage medium, and the method comprises the steps: obtaining a to-be-extracted image; inputting the to-be-extracted image into a target image feature extraction model for image feature extraction, the target image feature extraction model being a model obtained by training based on a VGG model, a residual module and a pyramid pooling module; and obtaining an image feature output by the target image feature extraction model as a target image feature corresponding to the to-be-extracted image. Therefore, the target image feature extraction model is obtained through training based on the VGG model, the residual module and the pyramid pooling module, the problem that time is often consumed when SIFT or ORB is adopted to extract image corner features is avoided, and the accuracy of image feature extraction is improved. The method can be applied to the fields of intelligent government affairs, digital medical treatment, science and technology finance and the like.

Description

Technical field

[0001] The present application relates to artificial intelligence technology, and in particular, an extraction method, apparatus, device, and storage medium relating to an image feature. Background technique

[0002] Similar image retrieval is an important technical field of image processing, and images can be quickly locked in the same or similar image in massive image data by similar image retrieval techniques. Similar image retrieval techniques retrieve images by comparing image features. The extraction method of the traditional image feature is generally extracted with an image angular characteristic with SIFT (scale constant feature transformation) or ORB (Oriented Fast and Rotated Brief), or extracts image features using depth learning. Extracting image angle characteristics using SIFT or ORB is often time consuming, while the depth learning method extracts image feature accuracy, which affects the development of similar image retrieval techniques. Inventiv...

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