Abstract
In the Human life, videos popularity has increased day by day. With the help of high qualityvideo camera and video editing tools peoples easily manipulate video for malicious intent. Sonow a day, this is becoming significant topic in the recent year with more difficulties. The proposed of research work focus in texture features by using Local Binary Pattern (LBP). The object of this work is to detect video inconsistency. The work is addressing in various steps as sequentially such as preprocessing, feature extraction, matching and decision. The evaluation of propose system by using True positive Rate (TPR) and False Positive Rate (FPR). The experimental results were executives on famous dataset REWIND database, which has 20 videos which give efficiency results with evaluation parameter TPR with \(0.0258\%\), FPR with \(0.0786\%\) and Area Under Curve (AUC) = \(0.7903\%\).
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Gaikwad, A., Mahale, V., Ali, M.M.H., Yannawar, P.L. (2019). Detection and Analysis of Video Inconsistency Based on Local Binary Pattern (LBP). In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_9
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