Big data watermarking method based on artificial intelligence

A technology of artificial intelligence and big data, applied in the direction of image data processing, image data processing, instruments, etc., can solve the problems that affect the image quality, cannot guarantee the image quality, cannot know whether the image has a watermark, etc., to achieve strong identification and guarantee The effect of stability

Inactive Publication Date: 2020-08-28
BEIJING TONGTECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the watermark embedding of data is mainly based on the existence of a certain degree of redundancy in the numerical attributes. By introducing a certain error into the least significant bit LSB of the numerical attributes, the watermark embedding and extraction are realized. The existing watermark embedding and Extraction does not have a detection method, it is impossible to know the quality of the watermark after encountering an attack after the embedding of the watermark, the quality of the image after the embedding of the watermark cannot be guaranteed, and it is impossible to know whether there is a watermark in the image before the embedding of the watermark, resulting in multiple watermarks overlapping, affecting image quality

Method used

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  • Big data watermarking method based on artificial intelligence
  • Big data watermarking method based on artificial intelligence
  • Big data watermarking method based on artificial intelligence

Examples

Experimental program
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Embodiment 1

[0060] see Figure 1-7 , a big data watermarking method based on artificial intelligence, comprising the following steps:

[0061] S1 watermark preprocessing detection: including an image information storage module, a control execution module, a watermark detection module and a watermark removal module;

[0062] S2: Watermark embedding: When embedding the watermark, the repeated embedding strategy is adopted. First, the blocks are scrambled, and then adjacent blocks are grouped into groups. Several flippable pixels are selected from each group, and their values ​​are all modified. For the bit information to be embedded, compile the watermark information into a watermark sequence, divide the original data into tuples according to the length of the watermark sequence, and mark and sort each data tuple;

[0063] S3: Watermark extraction: When extracting the watermark, receive the data to be verified, match it with the watermarked data in the watermark parameter database, obtain ...

Embodiment 2

[0083] see Figure 8-10 , a big data watermarking method based on artificial intelligence, comprising the following steps:

[0084] S1 watermark preprocessing detection: including an image information storage module, a control execution module, a watermark detection module and a watermark removal module;

[0085] S2: Watermark embedding: When embedding the watermark, the repeated embedding strategy is adopted. First, the blocks are scrambled, and then adjacent blocks are grouped into groups. Several flippable pixels are selected from each group, and their values ​​are all modified. For the bit information to be embedded, compile the watermark information into a watermark sequence, divide the original data into tuples according to the length of the watermark sequence, and mark and sort each data tuple;

[0086] S3: Watermark extraction: When extracting the watermark, receive the data to be verified, match it with the watermarked data in the watermark parameter database, obtain...

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Abstract

The invention discloses a big data watermarking method based on artificial intelligence, and belongs to the technical field of big data watermarking methods. The method comprises steps: S1, preprocessing and detecting a watermark; S2, embedding the watermark; s3, extracting the watermark; and S4, detecting the digital watermark. The invention discloses a big data watermarking method based on artificial intelligence. By detecting a watermark, it can be shown that the watermark obtained by the method is high in identifiability; after the embedding of the watermark, the original image is not influenced; the stability of visual transmission of the original image and the visual effect of the original image are ensured; image imaging can be effectively controlled; he visual effect of the image is prevented from being influenced, the watermark embedding efficiency and quality are improved, the anti-shearing attack performance is good, if large-area shearing is carried out, the integrity of the original image can be damaged, the watermark cannot be completely or mostly sheared while the integrity of the image is ensured, the phenomenon of image stealing is avoided, and the watermark effectis enhanced.

Description

technical field [0001] The invention relates to the technical field of big data watermarking methods, in particular to a big data watermarking method based on artificial intelligence. Background technique [0002] With big data initiating major changes in human life, work and thinking, personal data has become a treasure with great value. When its value is discovered, it can continue to create value in various ways. Through deep mining of personal data, companies can achieve more detailed market segmentation and design and produce more targeted products to achieve precise marketing; the formulation of government policies and regulations will be more wise and scientific. In the era of big data, the collection, processing, transaction and application of personal data will be unprecedentedly active. At the same time, frequent transaction activities will also put personal data privacy in danger of leakage at any time. Therefore, how to solve the problem of personal data privacy...

Claims

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Application Information

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IPC IPC(8): G06T1/00
CPCG06T1/0021G06T2201/0065
Inventor 张春林李利军李春青刘志杰
Owner BEIJING TONGTECH CO LTD
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