Overcome the Brightness and Jitter Noises in Video Inter-Frame Tampering Detection.

Han Pu,Tianqiang Huang,Chenbin Zhao,Bin Weng,Feng Ye

doi:10.3390/s21123953

Han Pu, Tianqiang Huang + Show 3 more

Open Access

https://doi.org/10.3390/s21123953

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Abstract

Digital video forensics plays a vital role in judicial forensics, media reports, e-commerce, finance, and public security. Although many methods have been developed, there is currently no efficient solution to real-life videos with illumination noises and jitter noises. To solve this issue, we propose a detection method that adapts to brightness and jitter for video inter-frame forgery. For videos with severe brightness changes, we relax the brightness constancy constraint and adopt intensity normalization to propose a new optical flow algorithm. For videos with large jitter noises, we introduce motion entropy to detect the jitter and extract the stable feature of texture changes fraction for double-checking. Experimental results show that, compared with previous algorithms, the proposed method is more accurate and robust for videos with significant brightness variance or videos with heavy jitter on public benchmark datasets.

Highlights

The rapid development and spread of low-cost and easy-to-use video editing software, such as Adobe Premiere, Photoshop, and Lightworks, makes it easier to tamper with digital video without efforts
We conduct extensive experiments in diverse and realistic forensic setups to evaluate the performance of the proposed detection framework
In a real-life scenario, the forensic investigator has no control over the parameters of the environment where the video was captured or the parameters used by the video tamper

Summary

Introduction

The rapid development and spread of low-cost and easy-to-use video editing software, such as Adobe Premiere, Photoshop, and Lightworks, makes it easier to tamper with digital video without efforts. It includes inserting frames into a video sequence or removing frames from a video sequence [1]. These tampered videos may be indistinguishable to the naked eye. They may harm judicial forensics, media reports, e-commerce, finance, and public security. It is necessary to develop methods to help human eyes identify tampered videos [1]

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