Two–Stage Detection and Localization of Inter–Frame Tampering in Surveillance Videos Using Texture and Optical Flow

Naheed Akhtar, Muhammad Hussain and Zulfiqar Habib ()
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Naheed Akhtar: Department of Computer Science, University of Education, Lahore 54510, Pakistan
Muhammad Hussain: Department of Computer Science, King Saud University, Riyadh 11543, Saudi Arabia
Zulfiqar Habib: Department of Computer Science, COMSATS University Islamabad, Lahore Campus, Islamabad 45550, Pakistan

Mathematics, 2024, vol. 12, issue 22, 1-27

Abstract: Surveillance cameras provide security and protection through real-time monitoring or through the investigation of recorded videos. The authenticity of surveillance videos cannot be taken for granted, but tampering detection is challenging. Existing techniques face significant limitations, including restricted applicability, poor generalizability, and high computational complexity. This paper presents a robust detection system to meet the challenges of frame duplication (FD) and frame insertion (FI) detection in surveillance videos. The system leverages the alterations in texture patterns and optical flow between consecutive frames and works in two stages; first, suspicious tampered videos are detected using motion residual–based local binary patterns (MR–LBPs) and SVM; second, by eliminating false positives, the precise tampering location is determined using the consistency in the aggregation of optical flow and the variance in MR–LBPs. The system is extensively evaluated on a large COMSATS Structured Video Tampering Evaluation Dataset (CSVTED) comprising challenging videos with varying quality of tampering and complexity levels and cross–validated on benchmark public domain datasets. The system exhibits outstanding performance, achieving 99.5% accuracy in detecting and pinpointing tampered regions. It ensures the generalization and wide applicability of the system while maintaining computational efficiency.

Keywords: inter–frame tampering; motion residual; local binary pattern; optical flow; frame duplication detection; frame insertion detection (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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