Indexing of compressed video sequences

Fayez M. Idris, Sethuraman Panchanathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations


In this paper, we propose an algorithm based on vector quantization (VQ) for indexing of video sequences in the compressed form. In VQ, the image to be compressed is decomposed into L-dimensional vectors. Each vector is mapped into one of a finite set of codewords (codebook). Vectors are encoded in the intraframe mode using adaptive VQ. Each frame is represented by a set of labels and a codebook. We note that the codebook reflects the contents of the frame being compressed and similar frames have similar codebooks. The labels are used for cut detection and to generate indices to store and retrieve video sequences. The proposed technique provides fast access to the sequences in the database. In addition, this technique combines video compression and video indexing. Simulation results confirm the substantial gains of the proposed technique in comparison with other techniques reported in the literature.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsIshwar K. Sethi, Ramesh C. Jain
Number of pages7
StatePublished - Jan 1 1996
Externally publishedYes
EventStorage and Retrieval for Still Image and Video Databases IV - San Jose, CA, USA
Duration: Feb 1 1996Feb 2 1996

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherStorage and Retrieval for Still Image and Video Databases IV
CitySan Jose, CA, USA

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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