• DocumentCode
    685654
  • Title

    CBIR: Retrieval of similar images using median vector algorithm

  • Author

    Elumalaivasan, P. ; Suthir, S. ; Ravikumar, S. ; Pandiyaraju, V. ; Munirathinam, T.

  • Author_Institution
    CEG, Anna Univ., Chennai, India
  • fYear
    2013
  • fDate
    12-14 Dec. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    In content based image retrieval (CBIR) system, target images are sorted by feature similarities in terms of related query. Image classification is the important field in applications like security, biometrics, and in medical applications. An efficient image retrieval system is Hue, Saturation and Value (HSV) color space. This Classify the image into n number of areas based on different selected ranges of hue and value, then each area is partitioned into m number of segments based on the number of pixels it contains, the area which has more pixels will be partitioned into more segments and which has less pixels will be partitioned into less number of segments. This is used as a feature vector. Here color feature is one of the important features for image retrieval and content based image retrieval of clustering is the best method to sort the similar images. The proposed algorithms, inverse, inverse of engrave, double emboss, 3D shape detection, edge detection, gray scale, gray scale extended, color reduction and high color mode are used in the image enhancement process and color median vector algorithm is used to retrieve the similar images.
  • Keywords
    content-based retrieval; edge detection; feature extraction; image classification; image colour analysis; image enhancement; image retrieval; image segmentation; vectors; 3D shape detection; CBIR system; color median vector algorithm; color reduction; content based image retrieval system; double emboss; edge detection; engrave inverse; feature similarities; feature vector; gray scale; gray scale extended; high color mode; hue-saturation-and-value color space; image classification; image enhancement process; Clustering algorithms; Image color analysis; Image retrieval; Image segmentation; Shape; Vectors; Content-Based Image Retrieval (CBIR); HSV color space; color feature vector; image classification; image retrieval; similarity measure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Green Computing, Communication and Conservation of Energy (ICGCE), 2013 International Conference on
  • Conference_Location
    Chennai
  • Type

    conf

  • DOI
    10.1109/ICGCE.2013.6823389
  • Filename
    6823389