A method and device for image retrieval based on deep learning

Abstract

The invention relates to an image retrieval method and device based on deep learning. The method includes: building a deep neural network; inputting training set images into the deep neural network for training; loading the trained deep neural network model, inputting all images of the training set into the deep neural network, and obtaining a binary hash with semantic information At the same time, the traditional binary hash coding method is used to obtain the binary hash code with visual information, and a local feature library is established; the image to be retrieved is input into the deep neural network, and the corresponding binary hash code with semantic information is obtained, and the binary hash code with semantic information is obtained. The traditional binary hash coding method obtains the binary hash code with visual information of the image to be retrieved, compares it with the local feature library, and obtains the retrieval result by calculating the similarity. The present invention can preserve important image information as much as possible, and can realize fast and accurate image retrieval of massive image data.

Description

technical field [0001] The invention belongs to the application of deep learning in the field of image processing, and in particular relates to a method and device for performing binary hash coding on images by using a deep neural network for retrieval. Background technique [0002] Image retrieval technology aims at the image content that users are interested in, and presents related images to users in a manner of increasing similarity from high to low according to a specific similarity measurement standard. The core problem is how to condense the information of the image, obtain the feature descriptor of the image, and fully express the content information of the image. [0003] The traditional image retrieval technology extracts image features based on basic features such as texture, color, and shape of the image, and uses the corresponding image similarity measurement method to calculate the similarity. However, these basic image features cannot describe the semantic co...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the disadvantage that the existing image retrieval method based on deep learning often adopts a single pooling method in the network design process, the present invention adopts the output structure of each layer in the design process of the network structure Two pooling methods, maximum pooling and average pooling, greatly preserve the semantic information of images to achieve better image retrieval results

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