文章基本信息

标题：Movie Piracy Detection Using Mel-Frequency Cepstral Coefficients and Vector Quantization
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作者：B. Srinivas ; K.Venkata Rao ; P. Suresh Varma 等
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2012
卷号：2
期号：4
页码：27-31
出版社：International Journal of Soft Computing & Engineering
摘要：Along with the increase in the advancement of technology in movie industry over internet, there is also an increase in the movie piracy via internet which affects factors like economy and repudiation of movie industry. Internet movie piracy is the most common means for pirates as well as downloader’s to break copyright laws by anonymous illegal uploads/downloads. In this paper we proposed an automated internet movie piracy detection mechanism based on audio fingerprint, which implements two famous algorithms, one is Mel-Frequency Cepstral Coefficients (MFCC) for feature extraction and the other is Vector Quantization (VQ) for classification. Our trained system initially looks for the sites which offer illegitimate copies of movies and if there is any suspicion based on a particular movie which is similar to the database of copyrighted movies that are registered with our trained system, it simply compares the fingerprints that are generated by implementing the above specified algorithms for both the trained and suspected movies. We collected various audio samples of different movies and we also extracted audio samples of pirated movies via internet with and without noises and trained and tested with our system. Finally, our system rendered efficient results with few error rates. We collected 52 audio samples without noise and 48 samples with noise and the resulted success classification is 96% and 92% respectively.
关键词：Classification; Code Book; Movie Piracy;MFCC; VQ.