A method for recognizing counterfeit data based on online dictionary learning data matching model

Abstract

The invention discloses a method for identifying counterfeit goods data based on an online dictionary learning data matching model, the technical proposal of the invention is that the hardware equipment is installed and debugged at first, networking and learning from images of counterfeit data matching models are performed, the data matching model of online dictionary learning is established, theversion of the goods to be inspected, Batch, packing and time patterns are placed beneath the scanning device; collection of image information and similarity matching are carried out through online dictionary learning data matching model, so that that final similarity is obtained, a threshold is set, and the final similarity is compared with the threshold. As the final similarity is greater than the threshold value, it is judged that the identify goods are authentic, when the final similarity is less than the threshold value, it is judged that the goods are counterfeit, and the information ofthe genuine goods and the counterfeit goods is saved for self-adjustment and self-proofreading, which effectively improves the accuracy of the identification judgment, saves the running time of the whole algorithm, and greatly improves the efficiency and success rate of the identification.

Description

technical field [0001] The invention relates to the technical field of image intelligent processing of computer vision and pattern recognition, in particular to a fake data recognition method based on an online dictionary learning data matching model. Background technique [0002] In recent years, counterfeit goods have been rampant. Whether it is Internet e-commerce channels or offline physical store channels, a large number of counterfeit goods have been exposed in the news, which has become a major issue affecting the current social and people's livelihood that cannot be ignored. Therefore, it is of great significance to study the data state identification method of counterfeit goods in the market to prevent the occurrence of counterfeit goods and public suffering. Fake products refer to products that appear in the market with similar product packaging or the same packaging but cannot be verified for anti-counterfeiting. Due to the repeated appearance of fake products and...

AI Technical Summary

Problems solved by technology

[0003] At present, the identification method based on the key information of product packaging is mainly based on the genuine product packaging as a reference, and it is difficult for ordinary users to distinguish through their own judgment. At the same time, the key packaging information is relatively different according to different time periods, and it is not necessarily accurate.

The identification method based on anti-counterfeiting parameters is costly for manufacturers, but it must be verified for users

The identification method based on packaging batches is mainly determined by time period or different sales areas, it is difficult to distinguish related batches, and sometimes the manufacturer cannot control

The recognition method based on computer vision has a good application prospect, but the algorithm is relatively complicated, mainly through product image detection and target recognition, which is inefficient and does not consider individual differences in the database

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