Journal of Computer and Communications

Journal of Computer and Communications

ISSN Print: 2327-5219
ISSN Online: 2327-5227
www.scirp.org/journal/jcc
E-mail: jcc@scirp.org
"Video Inter-Frame Forgery Identification Based on Consistency of Correlation Coefficients of Gray Values"
written by Qi Wang, Zhaohong Li, Zhenzhen Zhang, Qinglong Ma,
published by Journal of Computer and Communications, Vol.2 No.4, 2014
has been cited by the following article(s):
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[2] A comprehensive survey of image and video forgery techniques: variants, challenges, and future directions
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[3] Digital Video Tampering Detection and Localization: Review, Representations, Challenges and Algorithm
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[5] Multiple forgery detection in video using inter-frame correlation distance with dual-threshold
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[7] Deep feature based forgery detection in video using parallel convolutional neural network: VFID-Net
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[8] VFDHSOG: Copy-Move Video Forgery Detection Using Histogram of Second Order Gradients
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[9] Texture Feature Analysis for Inter-Frame Video Tampering Detection
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[11] 数字视频伪造被动取证技术研究综述.
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[13] Authentication of Video Evidence for Forensic Investigation: A Case of Nigeria
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[14] Video interframe forgery detection: Classification, technique & new dataset
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[15] Detecting and Locating Passive Video Forgery Based on Low Computational Complexity Third-Order Tensor Representation
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[16] A NEW TAMPER DETECTION ALGORITHM FOR VIDEO
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[17] Detecting Video Inter-Frame Forgeries Based on Convolutional Neural Network Models
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[18] A comprehensive survey on passive techniques for digital video forgery detection
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[19] Autenticación de vídeos MOV usando el contenedor H. 264/AVC
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[20] A Novel Video Forgery Detection Model Based on Triangular Polarity Feature Classification
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[21] Video tampering dataset development in temporal domain for video forgery authentication
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[22] Detecting Video Inter-Frame Forgeries Based on Convolutional Neural Network Model
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[23] Tempo Temporal Forgery Video Detection Using Machine Learning Approach.
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[24] Detection And Localization Of Splicing Attacks On Videos Using Block Correlation
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[25] A Review on Digital Video Forgery Detection Techniques in Cyber Forensics
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[26] Tampering Detection in Video Inter-Frame using Watermarking
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[27] A Coarse-to-fine Deep Convolutional Neural Network Framework for Frame Duplication Detection and Localization in Forged Videos
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[28] DETECTING FAKE VIDEOS
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[29] Temporal Copy-Move Forgery Detection and Localization Using Block Correlation Matrix
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[30] Three-dimensional Region Forgery Detection and Localization in Videos
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[31] COPY-MOVE FORGERY DETECTION IN VIDEO FORENSICS USING OPTICAL FLOW FOR COARSE-TO-FINE DETECTION
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[32] Copy Create Video Forgery Detection Techniques Using Frame Correlation Difference by Referring SVM Classifier
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[33] A Coarse-to-fine Deep Convolutional Neural Network Framework for Frame Duplication Detection and Localization in Forged Videos.
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[34] A Comparative study of various Video Tampering detection methods
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[35] A Digital Forensic Technique for Inter–Frame Video Forgery Detection Based on 3D CNN
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[36] A Coarse-to-fine Deep Convolutional Neural Network Framework for Frame Duplication Detection and Localization in Video Forgery
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[37] Coarse-to-Fine Copy-Move Forgery Detection for Video Forensics
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[38] Video Forensics for Detecting Shot Manipulation Using the Information of Deblocking Filtering
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[39] Detection and localization of inter-frame video forgeries based on inconsistency in correlation distribution between Haralick coded frames
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[40] A C3D-based Convolutional Neural Network for Frame Dropping Detection in a Single Video Shot
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[41] A review of video falsifying techniques and video forgery detection techniques
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[42] Inter-frame video forgery detection based on multi-level subtraction approach for realistic video forensic applications
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[43] Video content authentication techniques: a comprehensive survey
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[44] Videolarda çerçeve kopyala yapıştır sahteciliği tespiti
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[45] PRESERVING FRESHNESS AND CONTINUITY IN REMOTE BIOMETRIC AUTHENTICATION
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[46] Detecting tampering in audio-visual content using QIM watermarking
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[47] Detecting video frame-rate up-conversion based on periodic properties of edge-intensity
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[48] Digital video tampering detection: An overview of passive techniques
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[49] Development of a video tampering dataset for forensic investigation
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[50] Tampering Detection and Localization Techniques for Images/Videos Based on Inter-frame Correlation and Classification and Regression Tree
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[51] A constructing vehicle intrusion detection algorithm based on BOW presentation model
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[52] Detection of video forgery: A review of literature
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[53] Exposing video inter-frame forgery by Zernike opponent chromaticity moments and coarseness analysis
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[54] DETECTION OF VIDEO FORGERY: A REVIEW OF LITERATURE.
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[55] Video Forgery Detection: State-of-The-Art
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