• DocumentCode
    541747
  • Title

    Attribute associated image retrieval and similarity reranking

  • Author

    Abubacker, K. A Shaheer ; Indumathi, L.K.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Nat. Coll. of Eng., Tirunelveli, India
  • fYear
    2010
  • fDate
    27-29 Dec. 2010
  • Firstpage
    235
  • Lastpage
    240
  • Abstract
    Existence of countless digital images has given rise to image retrieval in many applications. Conventional image databases being text-annotated pose two major problems of keywords for images and complexity. Hence, retrieval systems based on image´s visual content are more desirable [1]. The content based image retrieval (CBIR) technique, employed here uses visual cues to retrieve images. This technique is query based, extracts the most vital attributes like color, shape and texture. Automatic extraction of spatial based color feature and invariant Fourier descriptors makes it more flexible. The extent of each attribute is obtained from the user, compared with attributes of images in database and most similar images are retrieved based on the degree of similarity.
  • Keywords
    content-based retrieval; feature extraction; image colour analysis; image matching; image retrieval; image texture; shape recognition; text analysis; visual databases; attribute associated image retrieval; color feature extraction; content based image retrieval; digital image database; invariant Fourier descriptor; query based technique; shape attribute; similarity reranking; text annotated pose; texture attribute; Feature extraction; Gabor filters; Image color analysis; Image retrieval; Pixel; Shape; Visualization; CBIR; Gabor filter; Image Retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication and Computational Intelligence (INCOCCI), 2010 International Conference on
  • Conference_Location
    Erode
  • Type

    conf

  • Filename
    5738736