• DocumentCode
    3272402
  • Title

    Image retrieval for compressed and uncompressed images

  • Author

    Khapli, Vidya R. ; Bhalchandra, Anjali S.

  • Author_Institution
    K.K. Wagh Women´´s Polytech., Nashik, India
  • fYear
    2009
  • fDate
    8-10 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    To reduce the storage and transmission requirements in image applications, images are compressed while maintaining acceptable visual quality. In this paper, image retrieval using Vector Quantization (VQ) is explored. The VQ technique is tested on uncompressed images (UCID) as well as compressed images (JPG). In order to reduce the retrieval time, the images are converted into thumbnails and the retrieval performance in both the domains is observed. The testing is performed with various thumbnail sizes. Performance is evaluated by using Precision and Recall. It is observed that the retrieval performance using VQ for compressed images remains comparable with that with uncompressed images.
  • Keywords
    image coding; image retrieval; vector quantisation; JPG; UCID; acceptable visual quality; compressed images; image retrieval; retrieval time reduction; storage transmission requirements; thumbnail sizes; uncompressed images; vector quantization; Discrete Fourier transforms; Discrete wavelet transforms; Image coding; Image retrieval; Image storage; Indexing; Information retrieval; Pixel; Testing; Vector quantization; Vector Quantization; compressed domain image retrieval; compressed domain indexing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information, Communications and Signal Processing, 2009. ICICS 2009. 7th International Conference on
  • Conference_Location
    Macau
  • Print_ISBN
    978-1-4244-4656-8
  • Electronic_ISBN
    978-1-4244-4657-5
  • Type

    conf

  • DOI
    10.1109/ICICS.2009.5397711
  • Filename
    5397711