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ImageWatermarking

Data protection has become an increasingly significant issue, especially with the rapid development and use of the Internet. Here we tried to make image watermark protection even if image is tampered. Firstly generated a self-recovery image that is robust to tampering attacks. In the preprocessing phase, we used the chaotic mixing algorithm to evenly distribute the hidden information. the resulting information is called “chaotic information”.We used common images that are standard in the field of image processing to train the codebook via the Linde–Buzo–Gray algorithm. Furthermore, we used the resulting codebook to encrypt and decrypt our experimental images. In the last step of the preprocessing phase, we generated a robust image as the self-recovery image. Next, for both the encryption and decryption phases, we used the OMP algorithm to implement the sparse approximation. For the process of sparse approximation, we selected the index yielding the maximum coefficient in the sparse coefficient vector to represent the corresponding vector. So, in encryption phase by using codebook, image, information(watermark) one private key is generated. and in decryption phase using codebok, image, private key informatin(watermark) is generated as the result.

Install / Use

/learn @AMGIRI-1996/ImageWatermarking
About this skill

Quality Score

0/100

Supported Platforms

Universal
View on GitHub
GitHub Stars8
CategoryDevelopment
Updated3y ago
Forks1

Languages

Java

Security Score

60/100

Audited on Oct 12, 2022

No findings