Using Paired Distances of Signal Peaks in Stereo Channels as Fingerprints for Copy Identification

Abstract

This article proposes to use the relative distances between adjacent envelope peaks detected in stereo audio as fingerprints for copy identification. The matching algorithm used is the rough longest common subsequence (RLCS) algorithm. The experimental results show that the proposed approach has better identification accuracy than an MPEG-7 based scheme for distorted and noisy audio. When compared with other schemes, the proposed scheme uses fewer bits with comparable performance. The proposed fingerprints can also be used in conjunction with the MPEG-7 based scheme for lower computational burden.