Graph-Based Video Sequence Matching Using Dominant Colour Graph Profile (DCGP)

Saddam Bekhet*, Amr Ahmed

*Corresponding author for this work

Research output: Contribution to journalArticle (journal)peer-review

2 Citations (Scopus)


This paper presents a fast and effective technique for videos’ visual similarity detection and measurement using compact fixed-length signatures. The proposed technique (dominant colour graph profile DCGP) extracts and encodes the spatio-temporal information of a given video shot into a graph-based structure (tree) that fully captures this vital information. The graph structured properties are utilized to construct a fixed-length video signature of 112 decimal values per video shot. The encoded spatio-temporal information is extracted following channelling each video frame into a block-based structure, where the positions of respective blocks are tracked across video frames and encoded into multiple DCGP trees. The proposed technique provides a high matching speed (>2000 fps) and robust retrieval performance. The experiments on various standard and challenging datasets shows the framework’s robust performance, in terms of both, retrieval and computational performances.
Original languageEnglish
Pages (from-to)291-298
Number of pages8
JournalSignal, Image and Video Processing
Issue number2
Publication statusPublished - 1 Feb 2018


  • DC-image
  • DCGP
  • Dominant colour graph profile
  • Graph
  • Video matching

Research Centres

  • Centre for Intelligent Visual Computing Research


Dive into the research topics of 'Graph-Based Video Sequence Matching Using Dominant Colour Graph Profile (DCGP)'. Together they form a unique fingerprint.

Cite this