Compressed bit stream classification using VQ and GMM

Wenhua Chen; C.-C. Jay Kuo

doi:10.1117/12.284191

24 October 1997 Compressed bit stream classification using VQ and GMM

Wenhua Chen, C.-C. Jay Kuo

Author Affiliations +

Proceedings Volume 3162, Advanced Signal Processing: Algorithms, Architectures, and Implementations VII; (1997) https://doi.org/10.1117/12.284191
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

Algorithms of classifying and segmenting bit streams with different source content (such as speech, text and image, etc.) and different coding methods (such as ADPCM, (mu) -law, tiff, gif and JPEG, etc.) in a communication channel are investigated. In previous work, we focused on the separation of fixed- and variable-length coded bit streams, and the classification of two variable-length coded bit streams by using Fourier analysis and entropy feature. In this work, we consider the classification of multiple (more than two sources) compressed bit streams by using vector quantization (VQ) and Gaussian mixture modeling (GMM). The performance of the VQ and GMM techniques depend on various parameters such as the size of the codebook, the number of mixtures and the test segment length. It is demonstrated with experiments that both VQ and GMM outperform the single entropy feature. It is also shown that GMM generally outperforms VQ.

Citation Download Citation

Wenhua Chen and C.-C. Jay Kuo "Compressed bit stream classification using VQ and GMM", Proc. SPIE 3162, Advanced Signal Processing: Algorithms, Architectures, and Implementations VII, (24 October 1997); https://doi.org/10.1117/12.284191

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE