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In Content-Based Copy detection(CBCD)literature, numerous state-of-the-art techniques are primarily focusing on visual content of video. Exploiting audio fingerprints for CBCD problem is necessary, because of following reasons: audio content constitutes an indispensable information source;transformations on audio content is limited compared to visual content. In this paper, a novel CBCD approach using audio features and PCA is proposed, which includes two stages:first, multiple feature vectors are computed by utilizing MFCC and four spectral descriptors;second, features are further processed using PCA, to provide compact feature description. The results of experiments tested on TRECVID-2007 dataset, demonstrate the e_ciency of proposed method against various transformations

A Novel Approach to Video Copy Detection Using Audio Fingerprints and PCA