• DocumentCode
    2520442
  • Title

    Fast retrieval on compressed images for internet applications

  • Author

    Albanesi, Maria Grazia ; Giacane, A.

  • Author_Institution
    Dipt. di Inf. e Sistemistica, Pavia Univ., Italy
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    136
  • Lastpage
    141
  • Abstract
    In this paper we present a method to incorporate a content-based retrieval algorithm on compressed images with a digital image transform scheme to achieve a low cost and fast indexing method. The target application is the access and interaction with huge amount of visual data on Internet. The approach exploits a modified Wavelet multiresolution decomposition and reconstruction scheme and a multiresolution algorithm for feature extraction and index generation. The efficacy of the method has been proved by extensive tests on YUV compressed JPEG images and the performance have been compared with other approaches on uncompressed, original images, even with the addition of noise. The results suggest a great opportunity to embed in a unique paradigm a fast retrieval technique and a good compression algorithm of low computational complexity, very suitable for Internet imaging applications
  • Keywords
    Internet; computational complexity; content-based retrieval; data compression; database indexing; feature extraction; image coding; Internet; Internet imaging; YUV compressed JPEG images; compressed images retrieval; computational complexity; content-based retrieval algorithm; digital image transform scheme; feature extraction; index generation; indexing; modified Wavelet multiresolution decomposition; multiresolution algorithm; performance; visual data; Content based retrieval; Costs; Digital images; Feature extraction; Image coding; Image reconstruction; Image retrieval; Indexing; Internet; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Architectures for Machine Perception, 2000. Proceedings. Fifth IEEE International Workshop on
  • Conference_Location
    Padova
  • Print_ISBN
    0-7695-0740-9
  • Type

    conf

  • DOI
    10.1109/CAMP.2000.875970
  • Filename
    875970