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Energy and Statistical Filtering for a Robust Audio Fingerprinting System

강인한 오디오 핑거프린팅 시스템을 위한 에너지와 통계적 필터링

  • Received : 2012.02.29
  • Accepted : 2012.05.08
  • Published : 2012.05.28

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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