Image retrieval method and device

Abstract

The invention provides an image retrieval method and device, and relates to the field of image retrieval. The method comprises the following steps: receiving query images sent by a user; according to an image classification method, obtaining the confidence coefficients, which correspond to each category, of the query images; according to a descending order of the confidence coefficients of the query images, retrieving image characteristics corresponding to the category of each confidence coefficient in a current confidence coefficient segment from an image characteristic library; according to the order of priority of retrieval, loading the retrieved image characteristics step by step; carrying out sorting processing on the loaded image characteristics; and sending a sorting processing result obtained by processing to a display interface step by step so as to bring convenience for the display interface to display. A situation that a result is output after all image characteristics in an established image database are retrieved is avoided, the time promptness and the stability of retrieval result feedback time are guaranteed, the problem that a true target is missed due to classification errors is unlikely to happen, indexes including a retrieval detection rate, a retrieval recall rate and the like are guaranteed, and the image retrieval method and device is more suitable for application scenes including security and protection video surveillance and the like.

Description

technical field [0001] The present invention relates to the field of image retrieval, in particular to an image retrieval method and device. Background technique [0002] At present, the image retrieval methods in the prior art are all content-based massive image retrieval, which mainly includes two stages: 1) the image entry stage, which establishes a database of image features, specifically classifying the entry images according to their shapes; For each category, select representative sample pictures from the image library to form a sample library; extract the image features of all input images in the sample library and store them in the corresponding database; 2) query stage, which is image retrieval stage, specifically extracting the image features of the input query image, traversing the image features in the above database, and calculating the correlation between the traversed image features and the image features of the query image, and then displaying the images fro...

AI Technical Summary

Problems solved by technology

[0003] The inventor found in the research that the above-mentioned image retrieval method in the prior art is prone to misclassification and leads to the problem of missing the real target, and the above-mentioned method also needs to retrieve all the features in the database before outputting, so that the retrieval results Long feedback time and poor stability

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