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JBE, vol. 23, no. 6, pp.886-895, November, 2018

DOI: https://doi.org/10.5909/JBE.2018.23.6.886

Detection of Frame Deletion Using Convolutional Neural Network

Jin Hyung Hong, Yoonmo Yang, and Byung Tae Oh

C.A E-mail: byungoh@kau.ac.kr

Abstract:

In this paper, we introduce a technique to detect the video forgery by using the regularity that occurs in the video compression process. The proposed method uses the hierarchical regularity lost by the video double compression and the frame deletion. In order to extract such irregularities, the depth information of CU and TU, which are basic units of HEVC, is used. For improving performance, we make a depth map of CU and TU using local information, and then create input data by grouping them in GoP units. We made a decision whether or not the video is double-compressed and forged by using a general three-dimensional convolutional neural network. Experimental results show that it is more effective to detect whether or not the video is forged compared with the results using the existing machine learning algorithm.



Keyword: Video Forensics, Frame Deletion, HEVC, CNN, Coding Pattern

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