Certificate video feature extraction method and device, computer equipment and storage medium

Abstract

The invention discloses a certificate video feature extraction method and device, computer equipment and a storage medium, and belongs to the technical field of video processing. The method comprisesthe following steps: acquiring an image sequence from a video containing a certificate, wherein the image sequence comprises at least one frame of certificate image; extracting a plurality of featuresub-images of each frame of certificate image according to the plurality of anti-counterfeiting features of the certificate; performing corresponding matching calculation on the plurality of feature sub-images of each frame of certificate image and a plurality of preset image templates to obtain matching score vectors of each frame of certificate image corresponding to the plurality of image templates; and forming a matching score matrix according to the matching score vector corresponding to each frame of certificate image, and mapping the matching score matrix into a video feature vector. According to the method, the certificate video features are extracted based on template matching so as to realize certificate authenticity identification, the method has good universality, various features including dynamic features can be considered, and the method has good expandability.

Description

technical field [0001] The present invention relates to the technical field of video processing, in particular to a method, device, computer equipment and storage medium for extracting certificate video features. Background technique [0002] Video classification is widely used in many fields such as anti-fraud and terrorism detection. One of the typical applications is the authenticity identification of documents in the financial field. [0003] General video classification methods, for example, the application number is CN201711420935.5, and the patent application titled "video classification model training method, device, storage medium and electronic equipment", the application number is CN201711172591.0, and the invention name is "video classification The patent applications for "method, video classification device and electronic equipment" all require the use of deep neural networks to extract features, which further requires a large amount of training data or at leas...

AI Technical Summary

Problems solved by technology

[0004] However, in the issue of identifying authenticity of documents, due to factors such as user privacy and difficulty in data collection and labeling, usually there is not a large number of standard data sets, and the anti-counterfeiting features of different documents are also quite different, so it can be used to train algorithms. There are few videos, and it is difficult to find a suitable pre-trained model to extract features, which is not suitable for directly using neural networks to extract features

In addition, since the quality of video collected by users is usually difficult to meet a very high standard, and the accuracy of a single identification feature of a document is often low, it is necessary to use multiple features at the same time to achieve counterfeiting

However, the anti-counterfeiting features of documents are not the same. For example, some dynamic features will change with changes in light angles. If the methods used to extract various anti-counterfeiting features are very different, the system will be too complicated and not easy to maintain. and extension

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