Back close

Linear Coding Method to Improve Embedding Efficiency of Cover Image in Image Steganography

Project Incharge:Mrs.Malathi P
Co-Project Incharge:Meera M
Linear Coding Method to Improve Embedding Efficiency of Cover Image in Image Steganography

This project aims to propose a method for improve the embedding efficiency of a grayscale cover image for image steganography. Linear coding (matrix embedding) method is used for embedding the message in the cover image so that the capacity of the cover image is utilised efficiently. Compressed domain embedding techniques has proven to be resistant against many steganalysis techniques, yet the capacity of the medium is constraint. The number of non-zero quantized coefficients will be less than the actual number of DCT coefficients, which reduces the capacity of the cover image. This project proposes a method to embed the message using an extension to hamming code, which was proven to improve the embedding capacity. It also compares the results with existing techniques.

Sample screenshots

Related Projects

Design and Optimization of Joint Torque Sensor for Robotic Applications
Design and Optimization of Joint Torque Sensor for Robotic Applications
WADI
WADI
(BWEF Learnings) Building Sustainable and Disaster Resilient Communities: Navigating Shocks to the Biodiversity-Water-Food-Energy Nexus through Learnings from Japan, India, and the UK
(BWEF Learnings) Building Sustainable and Disaster Resilient Communities: Navigating Shocks to the Biodiversity-Water-Food-Energy Nexus through Learnings from Japan, India, and the UK
Developing Suitable Pedagogical Methods for Various Classes, Intellectual Calibers and Research in E-learning- Main Phase
Developing Suitable Pedagogical Methods for Various Classes, Intellectual Calibers and Research in E-learning- Main Phase
Modernization of Metallurgy Laboratory for Mechanical Testing, Metal Forming and Quantitative Metallurgical Microstructure Analysis
Modernization of Metallurgy Laboratory for Mechanical Testing, Metal Forming and Quantitative Metallurgical Microstructure Analysis
Admissions Apply Now