LSB Matching Steganalysis Based on Patterns of Pixel Differences and Random Embedding

03/02/2017
by   Daniel Lerch-Hostalot, et al.
0

This paper presents a novel method for detection of LSB matching steganogra- phy in grayscale images. This method is based on the analysis of the differences between neighboring pixels before and after random data embedding. In natu- ral images, there is a strong correlation between adjacent pixels. This correla- tion is disturbed by LSB matching generating new types of correlations. The pre- sented method generates patterns from these correlations and analyzes their varia- tion when random data are hidden. The experiments performed for two different image databases show that the method yields better classification accuracy com- pared to prior art for both LSB matching and HUGO steganography. In addition, although the method is designed for the spatial domain, some experiments show its applicability also for detecting JPEG steganography.

READ FULL TEXT

page 33

page 35

research
04/23/2015

Edge Detection Based on Global and Local Parameters of the Image

This paper presents an edge detection method based on global and local p...
research
03/10/2016

Template Matching via Densities on the Roto-Translation Group

We propose a template matching method for the detection of 2D image obje...
research
05/24/2020

Networks with pixels embedding: a method to improve noise resistance in images classification

In the task of images classification, usually, the network is sensitive ...
research
06/09/2019

Pixel DAG-Recurrent Neural Network for Spectral-Spatial Hyperspectral Image Classification

Exploiting rich spatial and spectral features contributes to improve the...
research
09/29/2019

RPM-Net: Robust Pixel-Level Matching Networks for Self-Supervised Video Object Segmentation

In this paper, we introduce a self-supervised approach for video object ...
research
07/25/2019

Convolutional Neural Networks on Randomized Data

Convolutional Neural Networks (CNNs) are build specifically for computer...
research
06/14/2021

DFM: A Performance Baseline for Deep Feature Matching

A novel image matching method is proposed that utilizes learned features...

Please sign up or login with your details

Forgot password? Click here to reset