Duplicated Audio Segment Detection with Local Binary Pattern

Abstract

Due to the advantages of convenience, and difficulty of detection, copy-move forgery is one of the most common audio forgery forms. It is significant to decide whether there is a duplicated segment in the audio. In order to detect copy-move forgery, a new method is proposed in this paper. In the proposed algorithm, first the audio is segmented into syllables using a pitch tracking method. Second, each syllable analyzed with a 1-D local binary pattern operator. This operator calculates the histogram of each syllable. Mean square error is used to compute the similarities of histograms. The syllables which have similar histograms are detected as forged audio segments. Compared to another 1-D local binary pattern method, the proposed method has better detection results for copy-move forgery. Our experiments show that the proposed algorithm is feasible and effective, and robust against many common post-processing operations such as noise addition, filtering, and compression.