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You can find the source codes and algorithms proposed by this "Bit Plane Slicing and Quantization-Based Color Image Watermarking in Spatial Domain" study

License: MIT License

Python 100.00%
blind-watermarking frequency-domain image-compression image-hiding image-processing pseudo-random-generator stenography watermarking-algorithm image-processing-python latest

bit-plane-slicing-and-quantization-based-color-image-watermarking-in-spatial-domain's Introduction

Bit-Plane-Slicing-and-Quantization-Based-Color-Image-Watermarking-in-Spatial-Domain

You can find the source codes and algorithms proposed by this "Bit Plane Slicing and Quantization-Based Color Image Watermarking in Spatial Domain" study. The link of this article: https://link.springer.com/chapter/10.1007/978-981-16-0586-4_30
Please give a star to this repository and cite the work. Thank you.

Abstract

In this paper, a robust and fast watermarking scheme in spatial domain is introduced to embed a color watermark image over a color host image. The host image was converted from RGB to YCbCr. The watermark image was compressed using bit plane slicing followed by embedding into the luminance channel of the host image. Quantization process with pseudo-random steps was incorporated to embed the watermark into the host image and minimize the security vulnerabilities in the watermarked image. The experimental results indicate that the proposed watermarking scheme has better performance compared to existing related works in terms of robustness, time complexity and invisibility.

Keywords

Arnold transform DC-coefficient of 2D discrete Fourier transform (2D-DFT) Quantization Bit plane slicing

Code

  • In arnold.py the implementation of Arnold Transformation which is one of the most used scrambling techniques to permute an image or signal can be found.
  • In single_channel.py the implementation of two algorithms: i. Watermark Embedding Process and ii. Watermark Extraction Process , proposed by this study can be found.
  • In proposed_embed.py and proposed_extract.py the implementation of Proposed Watermarking Technique proposed (including Pre-processing of the Host Image and Watermark Image and Post-processing the bit sequence ) by this study can be found.

    Experimental Results

  • Host images: (a) Avion, (b) Baboon, (c) Lena, (d) Peppers and (e) Sailboat Can't display it this time
  • Color watermark image Can't display it this time
  • Extracted watermark images from watermarked images after different attacks. Can't display it this time
  • Average time for Watermark Embedding / Extraction Time is found 0.3445/0.2700 which outperforms the existence works hence the proposed mmethod can be implement in real-time applications.
  • bit-plane-slicing-and-quantization-based-color-image-watermarking-in-spatial-domain's People

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    bit-plane-slicing-and-quantization-based-color-image-watermarking-in-spatial-domain's Issues

    about cvg-ugr image database

    Dear author, your article is very well written I have already starred in github and ready to cite in the references, but I am now encountering a problem, I can't download the image of the official website of the cvg-ugr image database, please can you share the zip of the cvg-ugr image database, thank you very much!

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