Roopalakshmi, R.Guddeti, G.R.M.2026-02-062011Procedia Computer Science, 2011, Vol.5, , p. 149-15618770509https://doi.org/10.1016/j.procs.2011.07.021https://idr.nitk.ac.in/handle/123456789/33098In 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 rea-sons: 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 efficiency of proposed method against various transformations. © 2011 Published by Elsevier Ltd.Audio fingerprintsContent-based video copy detectionMFCCPCASpectral Descriptors