An Enhanced Edge Adaptive Steganography Approach Using Threshold Value for Region Selection

TL;DR

This paper presents an improved edge adaptive steganography method that uses a threshold value to select high-frequency pixels for data embedding, enhancing image quality and modification rate.

Contribution

It introduces a novel threshold-based pixel selection technique combined with LSBMR for better steganography performance over traditional edge detection methods.

Findings

0.2 to 0.6% improvement in image quality (PSNR)

4 to 10% enhancement in modification rate

Outperforms Sobel and Canny edge detection techniques

Abstract

This paper attempts to improve the quality and the modification rate of a Stego Image. The input image provided for estimating the quality of an image and the modified rate is a bitmap image. The threshold value is used as a parameter for selecting the high frequency pixels from the Cover Image. The data embedding process are performed on the pixels that are found with the help of Threshold value by using LSBMR. The quality of an image is estimated by the value of PSNR and the modification rate of an image is estimated by the value of MSE. The proposed approach achieves about 0.2 to 0.6 % of improvement in the quality of an image and about 4 to 10 % of improvement in the modification rate of an image compared to the edge detection techniques such as Sobel and Canny.