Quick retrieval method and system of vehicle image on the basis of feature geometric constraint

Abstract

The invention discloses a quick retrieval method and system of a vehicle image on the basis of a feature geometric constraint. The method comprises the following steps of: adopting a convolutional neural network to position the vehicle image, wherein the vehicle image comprises a query picture and a storage picture; carrying out feature extraction on the positioned image to obtain image features; adopting a hierarchical clustering method and a minimal hash method to carry out compressed encoding on the image features to obtain the hash code of the vehicle image features; according to the hash code of the vehicle image, adopting a visual phrase maintained by a geometric attribute to carry out image similarity calculation to obtain a quick matching retrieval result; and adopting a histogram of oriented gradients to carry out accurate matching on the quick matching retrieval result to obtain an accurate matching retrieval result. The method has the advantages of high retrieval accuracy and high retrieval speed, and can be widely applied to the field of image processing.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a vehicle image fast retrieval method and system based on feature geometric constraints. Background technique [0002] In recent years, with the development of our country's economy, the increase in the transportation demand of the whole society has led to a rapid increase in the number of vehicles, which has brought many conveniences to people's life and work. However, while bringing convenience, there are more and more car-related cases of using cars to commit illegal and criminal acts, car theft and various traffic violations, threatening the personal and property safety of residents. In order to deal with such problems, the management department has added various smart devices such as bayonet cameras, speedometers and fixed-point sensors in the city. Monitoring equipment and technology have been developed rapidly, and a large amount of monitoring data has been collected, whic...

AI Technical Summary

Problems solved by technology

Existing image retrieval methods represent images by using or combining shallow physical features such as color, texture, structure, and shape, which cannot effectively express image semantics, which will affect the accuracy of subsequent vehicle retrieval; at the same time, existing Image retrieval methods directly use shallow physical features for similarity matching, which will greatly reduce the subsequent retrieval speed (because the number and dimensions of shallow physical features will be too redundant in order to retain image information as much as possible

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