• DocumentCode
    3254352
  • Title

    An Attention-Based Image Retrieval System

  • Author

    Ozyer, Gulsah Tumuklu ; Vural, Fatos Yarman

  • Author_Institution
    Dept. of Comput. Eng., Middle East Tech. Univ., Ankara, Turkey
  • Volume
    1
  • fYear
    2011
  • fDate
    18-21 Dec. 2011
  • Firstpage
    96
  • Lastpage
    99
  • Abstract
    In this study, a new Content Based Image Retrieval system, called Attention-Based Image Retrieval (ABIR) is proposed by using the Itti-Koch visual attention model. For this purpose, first the regions are extracted by using the saliency maps. Then, the attention values, obtained from the saliency maps are used to define a new similarity metric. Finally, this metric is used to retrieve the similar regions. The proposed approach extracts the region of interests without employing any segmentation method. The extra emphasis given to high attention values, provide a better matching criterion, compared to the classical Euclidean distance. The power of the proposed method is demonstrated by the experiments. It is observed that ABIR retrieves with higher precision performance compared to the state of the art object based retrieval methods, in images with cluttered background.
  • Keywords
    content-based retrieval; feature extraction; image matching; image retrieval; Itti-Koch visual attention model; attention value; attention-based image retrieval system; classical Euclidean distance; cluttered background image; content based image retrieval system; matching criterion; object based retrieval method; region extraction; saliency map; similar region retrieval; similarity metric; Computational modeling; Feature extraction; Image color analysis; Image retrieval; Image segmentation; Object recognition; Visualization; CBIR; Visual Attention;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    978-1-4577-2134-2
  • Type

    conf

  • DOI
    10.1109/ICMLA.2011.27
  • Filename
    6146950