This project implements a reversible LSB steganography algorithm for hiding both text and complete files (e.g., PDFs) inside grayscale images, with high fidelity and measurable security. It extends traditional LSB techniques with reversible recovery and statistical robustness, backed by visual and quantitative metrics.
Reversible-LSB-Steganography/
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├── archive/
│ └── set12/ # SET12 benchmark images used for testing
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├── Papers/ # Research papers referenced in the project
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├── main.ipynb # Complete implementation in Jupyter Notebook
├── ProjectReport.pdf # Final research paper in IEEE format
├── ProjectReport.docx # Editable version of the paper
├── PPT/ # Project presentation slides
├── TestingFileHide.pdf # Sample file used for embedding into images
- Embeds both text and binary files (e.g.PDF,txt,jpg) into grayscale images using reversible LSB.
- Allows exact recovery of both the original image and the hidden data.
- Evaluates performance using PSNR, SSIM, MSE, and statistical measures (mean/std).
- Includes qualitative visual comparisons and a comprehensive IEEE-style report.
- SET12 image set is used for benchmarking.
- Includes 12 standard grayscale test images (e.g., Barbara, Boat, Monarch).
- Quantitative: PSNR, SSIM, MS-SSIM MSE, BPP.
- Statistical: Mean and standard deviation comparisons.
- Qualitative: Side-by-side image visualization.
The repository contains a detailed IEEE-format paper and presentation summarizing:
- Literature review
- Proposed method
- Experimental results
- Conclusions and future work
👉 Watch the algorithm demo and explanation on YouTube: [🔗 https://youtu.be/wtyt7vdbAak]
Title: Reversible LSB Steganography: Secure Image-Based File Hiding with Recovery
Description:
A complete walkthrough of our reversible LSB-based steganography project. Learn how text and files can be securely embedded into grayscale images with full reversibility. Visual results, metrics, and source code covered.
🔗 GitHub: [https://github.com/Vaibhav-Pant/Reversible-LSB-Steganography]