• DocumentCode
    2351330
  • Title

    Image Classification in CBIR Systems with Color Histogram Features

  • Author

    Arjunan, R. Vijaya ; Kumar, V. Vijaya

  • Author_Institution
    SCSVMV Univ., Kanchipuram, India
  • fYear
    2009
  • fDate
    27-28 Oct. 2009
  • Firstpage
    593
  • Lastpage
    595
  • Abstract
    Content based image retrieval (CBIR) refers to the ability to retrieve images on the basis of image content. In our work, we describe an approach to CBIR for various database images that relies on human input machine learning and computer vision. More specifically we apply expert level human interaction for solving that aspect of the problem and we employ machine learning algorithms to allow the system to be adapted to new image domains. We present empirical results for the domain of high resolution computed image of flowers. Our results illustrate the efficacy of loop approach to image characterization and the ability of our approach to adapt the retrieval process image domain through the application of machine learning algorithms.
  • Keywords
    computer vision; content-based retrieval; image classification; image colour analysis; image resolution; image retrieval; learning (artificial intelligence); CBIR system; color histogram features; computer vision; content based image retrieval; database image; image characterization; image classification; image content; image resolution; loop approach; machine learning; Computer vision; Content based retrieval; Histograms; Humans; Image classification; Image databases; Image retrieval; Machine learning; Machine learning algorithms; Spatial databases; API- Application Program Interface; CBIR- Content based Image retrieval; GUI- Graphical user interface; HSV- Hue Saturation & Value;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Recent Technologies in Communication and Computing, 2009. ARTCom '09. International Conference on
  • Conference_Location
    Kottayam, Kerala
  • Print_ISBN
    978-1-4244-5104-3
  • Electronic_ISBN
    978-0-7695-3845-7
  • Type

    conf

  • DOI
    10.1109/ARTCom.2009.233
  • Filename
    5329102