Compact color descriptor for fast image and video segment retrieval

Santhana Krishnamachari, Mohamed Abdel-Mottaleb

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations

Abstract

Histograms are the most prevalently used representation for the color content of images and video. An elaborate representation of the histograms requires specifying the color centers of the histogram bins and the count of the number of image pixels with that color. Such an elaborate representation, though expressive, may not be necessary for some tasks in image search, filtering and retrieval. A qualitative representation of the histogram is sufficient for many applications. Such a representation will be compact and greatly simplify the storage and transmission of the image representation. It will also reduce the computational complexity of search and filtering algorithms without adversely affecting the quality. We present such a compact binary descriptor for color representation. This descriptor is the quantized Haar transform coefficients of the color histograms. We show the use of this descriptor for fast retrieval of similar images and search for similar video segments from a large database. We also show the use of this descriptor for browsing large image databases without the need for computationally expensive clustering algorithms. The compact nature of the descriptor and the associated simple similarity measure allows searching over a database of about four hours of video in less than 5-6 seconds without the use of any sophisticated indexing scheme.

Original languageEnglish (US)
Pages (from-to)581-589
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3972
StatePublished - Jan 1 2000
Externally publishedYes
EventProceedings of the 2000 'Storage and Retrieval for Media Databases 2000' - San Jose, CA, USA
Duration: Jan 26 2000Jan 28 2000

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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