TR2000-35

Regions-of-Interest and Spatial Layout for Content-Based Image Retrieval


    •  Baback Moghaddam, Henning Biermann, Dimitris Margaritis, "Regions-of-Interest and Spatial Layout for Content-Based Image Retrieval", Tech. Rep. TR2000-35, Mitsubishi Electric Research Laboratories, Cambridge, MA, November 2000.
      BibTeX TR2000-35 PDF
      • @techreport{MERL_TR2000-35,
      • author = {Baback Moghaddam, Henning Biermann, Dimitris Margaritis},
      • title = {Regions-of-Interest and Spatial Layout for Content-Based Image Retrieval},
      • institution = {MERL - Mitsubishi Electric Research Laboratories},
      • address = {Cambridge, MA 02139},
      • number = {TR2000-35},
      • month = nov,
      • year = 2000,
      • url = {https://www.merl.com/publications/TR2000-35/}
      • }
  • Research Area:

    Computer Vision

Abstract:

To date most \"content-based image retrieval\" (CBIR) techniques rely on global attributes such as color or texture histograms which tend to ignore the spatial composition of the image. In this paper, we present an alternative image retrieval system based on the principle that it is the user who is most qualified to specify the query \"content\" and not the computer. With our system, the user can select multiple \"regions-of-interest\" and can specify the relevance of their spatial layout in the retrieval process. We also derive similarity bounds on histogram distances for pruning the database search. This experimental system was found to be superior to global indexing techniques as measured by statistical sampling of multiple users\' \"satisfaction\" ratings.