Video Steganalysis Against Motion Vector-Based Steganography by Adding or Subtracting One Motion Vector Value (2014)


This paper presents a method for detection of motion vector-based video steganography. First, the modification on the least significant bit of the motion vector is modeled. The influence of the embedding operation on the sum of absolute difference (SAD) is illustrated, which allows us to focus on the difference between the actual SAD and the locally optimal SAD after the adding-or-subtracting-one operation on the motion value. Finally, based on the fact that most motion vectors are locally optimal for most video codecs, two feature sets are extracted and used for classification. Experiments are carried out on videos corrupted by various steganography methods and encoded by various motion estimation methods, in various bit rates, and in various video codecs. Performance results demonstrate that our scheme outperforms previous works in general, and is more favorable for real-world applications.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Accurate and Robust Video Saliency Detection via Self-Paced Diffusion ABSTRACT: In order to estimate video saliency in the short term, traditional video saliency detection algorithms usually follow the common
PROJECT TITLE : Video Behavior Profiling for Anomaly Detection ABSTRACT: The goal of this study is to solve the challenge of modeling video behavior acquired in surveillance cameras for online normal behavior recognition and anomaly
PROJECT TITLE : A Convex Optimization Framework for Video Quality and Resolution Enhancement From Multiple Descriptions ABSTRACT: Streaming and compressing methods Of the last decade, technological advancements have led to a migration
PROJECT TITLE : Action-Stage Emphasized Spatiotemporal VLAD for Video Action Recognition ABSTRACT: However, convolutional neural networks (CNNs) have yet to attain the same spectacular results in video action detection as in image
PROJECT TITLE : Advanced Spherical Motion Model and Local Padding for 360 Video Compression ABSTRACT: The geometry distortion and the face boundary discontinuity are two of the key issues in 360Á video compression because of

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry