{'fraction_non_alphanumeric': 0.011178861788617886, 'fraction_numerical': 0.0, 'mean_word_length': 5.118012422360248, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Matrix Decomposition based Digital Video Forgery Detection

There are widespread growth of high quality and low cost cameras in our lives. Likewise different powerful video editing tools are also available, using this editing tools, people are intentionally or unintentionally edit contents and make to destroy the originality of the video. In this paper an effective method to detect and locate video frame duplication forgery is proposed. The proposed method converts the video forgery detection problem into an anomaly detection. A video patch cube is sampled from the given video and it is arranged as a matrix. Then it is decomposed into a low rank and sparse component using RPCA. The sparse component which represents anomaly is analyzed further using clustering techniques to detect the presence of forgery. Experimental result indicates that, the proposed method outperforms the state of art methods and offers low computational complexity as well as high degree of accuracy.