Method and device for identifying garbage pictures

Abstract

The invention relates to the technical field of image processing, in particular to a method and a device for identifying garbage pictures. The method comprises the following steps of: acquiring picture characteristics of a picture to be identified; splitting the picture characteristics to generate a picture characteristic sequence; and quickly comparing the characteristic combination, namely two continuous picture characteristics in the picture characteristic sequence, with a characteristic combination in a pre-stored garbage picture characteristic library through reverse index to obtain a garbage picture set comprising the picture characteristic combination; and calculating the similarity value of the picture to be identified and each garbage picture in the garbage picture set, and when the similarity value of any one garbage picture and the picture to be identified is greater than a set threshold value, determining that the picture to be identified is a garbage picture. By the method, on the one hand, the identification efficiency of garbage pictures can be improved, and on the other hand, the identification effect is improved because the method has strong adaptability to changes of the garbage pictures.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a garbage image identification method and device. Background technique [0002] With the development of Internet technology, blogs, microblogs, post bars, and SNS (Social Network Site, social networking sites) have developed rapidly, providing a wide range of platforms for people to disseminate and exchange various information. The Internet has brought convenience to the dissemination and acquisition of information, but it is followed by the flood of spam information. Spam spreads rapidly and takes various forms. The contents are mostly lottery winnings, scams, advertisements, and pornographic information. Their existence seriously affects the user experience. With the continuous investment of service operators in the field of anti-spam, some spam information has been converted from traditional text information to image information, which has brought certain dif...

AI Technical Summary

Problems solved by technology

The disadvantage of these methods is that most of the calculations are large, and the accuracy of recognition is low

On the other hand, these methods are generally less adaptable to spam image changes. For example, the spam information in the two images remains basically unchanged, but the background color of the image and the text size in the image change. Already in the training library, another picture is a picture to be recognized, it is still difficult to obtain accurate recognition results, so these methods are not ideal methods for identifying junk pictures

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