MDCT-Based Perceptual Hashing for Compressed Audio Content Identification

In this paper, a perceptual audio hashing method in compressed domain is proposed for content identification, in which MDCT coefficients as the intermediate decoding result are selected for perceptual feature extraction and hash generation. The perceptual feature extraction is based on psychoacoustic model and exhibits good discrimination ability for different audio contents but robustness against common audio signal processing operations. Via feature extraction in the compressed domain, the MDCT-based compressed audios, such as MP3, AAC, etc., could be efficiently identified without complete decoding which facilitates those practical applications with strict requirements of memory and computational complexity, such as online audio retrieval, indexing of massive compressed audio data, audio identification by mobile phone, etc. The algorithm is highly robust against MDCT compression which is widely used in audio coding. Experiments demonstrate the effectiveness of the proposed scheme.