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http://dx.doi.org/10.5392/JKCA.2012.12.05.001

Energy and Statistical Filtering for a Robust Audio Fingerprinting System  

Jeong, Byeong-Jun ((주)다이렉트미디어)
Kim, Dae-Jin ((주)다이렉트미디어)
Publication Information
The Journal of the Korea Contents Association / v.12, no.5, 2012 , pp. 1-9 More about this Journal
Abstract
The popularity of digital music and smart phones led to develope noise-robust real-time audio fingerprinting system in various ways. In particular, The Multiple Hashing(MLH) of fingerprint algorithms is robust to noise and has an elaborate structure. In this paper, we propose a filter engine based on MLH to achieve better performance. In this approach, we compose a energy-intensive filter to improve the accuracy of Q/R from music database and a statistic filter to remove continuity and redundancy. The energy-intensive filter uses the Discrite Cosine Transform(DCT)'s feature gathering energy to low-order bits and the statistic filters use the correlation between searched fingerprint's information. Experimental results show that the superiority of proposed algorithm consists of the energy and statistical filtering in noise environment. It is found that the proposed filter engine achieves more robust to noise than Philips Robust Hash(PRH), and a more compact way than MLH.
Keywords
Music Retrieval; Fingerprint; Energy-intensive Filter; Remove Continuity; Remove Redundancy;
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  • Reference
1 J. Haitsma and T. Kalker, "Speed-change resistant audio fingerprinting using autocorrelation," Acoustics, Speech and Signal Processing, 2003.
2 서용석, 김원겸, 이선화, 서영호, 황치정, "이미지 콘텐츠 출력물의 저작권보호를 위한 디지털 핑거 프린팅 기술에 관한 연구", 한국콘텐츠학회 추계종합학술대회 논문집, 제4권, 제2호, 2006(11).
3 J. Haitsma and T. Kalker, "A Highly Robust Audio Fingerprinting System," Proc. 3rd Int. Conf. Music Information Retrieval, pp.107-115, 2002(10).
4 Yu Liu, H. S.Yun, J. S. Sung, and N. S. Kim, "A Novel Audio Fingerprinting Scheme based on Subband Envelop Hashing," Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, pp.813-816, 2009(10).
5 P. Doets and R. Lagendijk, "Distortion estimation in compressed music using only audio fingerprints," IEEE Trans. Audio, Speech, and Language Processing, Vol.16, No.2, pp.302-317, 2008(2).   DOI   ScienceOn
6 N. Ahmed, T. Natarajan, and K. Rao, "Discrete cosine transform," IEEE Trans. Computers, pp.90-93, 1974(1).
7 K. Rao and P. Yip, "Discrete Cosine Transform: Algorithms, Advantages, Applications," Academic Press, 1990.
8 Cerling Wold, Thom Blum, Douglas Keislar, and James Wheaton, "Content-Based Classification, Search, and Retrieval of Audio," IEEE Multimedia, Vol.3, No.3, pp.27-36, Fall, 1996.   DOI   ScienceOn
9 Jianping Chen and Tiejun Huang, "A Robust Feature Extraction Algorithm for Audio Fingerprinting," Computer Science, advances in multimedia information processing, Vol.5353/2008, pp.887-890, 2008.
10 Avery Li-Chun Wang, "An Industrial-Strength Audio Search Algorithm," 4th Symposium Conference on Music Information Retrieval, pp.7-13, 2003(10).