• DocumentCode
    135488
  • Title

    Garabato: A proposal of a sketch-based Image Retrieval system for the Web

  • Author

    Miguelena Bada, Ana Maria ; de Jesus Hoyos Rivera, Guillermo ; Marin Hernandez, Antonio

  • Author_Institution
    Dept. of Artificial Intell., Univ. Veracruzana, Xalapa, Mexico
  • fYear
    2014
  • fDate
    26-28 Feb. 2014
  • Firstpage
    183
  • Lastpage
    188
  • Abstract
    A proposal for a queried-by-sketch image retrieval system is introduced as an alternative to text-based image search on the Web. The user will create a sketch as a query that will be matched with the edges extracted from natural images. The main challenge regarding edge detection for Content-based Image Retrieval consists in finding edges for larger regions and avoiding the ones corresponding to textures. For this purpose, a combination of selective smoothing and color segmentation is applied prior edge extraction. An evolutionary algorithm is deployed to optimize the image-processing parameters. Similarity between the user´s sketch and the image´s edges will be measured regarding two local aspects: spatial proximity and edge orientation. A full architecture for image search on the Web is proposed and preliminary results are reported using a trial database.
  • Keywords
    Internet; content-based retrieval; edge detection; evolutionary computation; image colour analysis; image retrieval; image segmentation; Garabato; World Wide Web; color segmentation; content-based image retrieval; edge detection; edge extraction; edge orientation; evolutionary algorithm; image-processing parameter; queried-by-sketch image retrieval system; selective smoothing; spatial proximity; text-based image search; Feature extraction; Image color analysis; Image edge detection; Image retrieval; Proposals; Smoothing methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Communications and Computers (CONIELECOMP), 2014 International Conference on
  • Conference_Location
    Cholula
  • Print_ISBN
    978-1-4799-3468-3
  • Type

    conf

  • DOI
    10.1109/CONIELECOMP.2014.6808588
  • Filename
    6808588