• DocumentCode
    2009694
  • Title

    Image similarity matching retrieval on synergetic neural network

  • Author

    Li, Hui ; Ma, Xiuli ; Wan, Wanggen ; Zhou, Xueli

  • Author_Institution
    Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China
  • fYear
    2010
  • fDate
    23-25 Nov. 2010
  • Firstpage
    1566
  • Lastpage
    1571
  • Abstract
    In this paper, an image similarity matching retrieval algorithm based on synergetic neural network (SNN) is proposed. It is a novel method with advantages of no pseudo-state and closer to natural self-organization process in the field of image retrieval. It utilizes feature vector extraction, attention parameter selection, order parameter calculation, pseudo-inverse matrix and its determinant value comparison to achieve better retrieval effect. Due to the structural characteristic of synergetic neural network, it can save time for iteration and improve efficiency and speed. The experimental results show that this algorithm has fast speediness, strong robustness and high accuracy, and provides greater generality and high real-time performance.
  • Keywords
    feature extraction; image matching; image retrieval; matrix algebra; neural nets; attention parameter selection; determinant value comparison; feature vector extraction; image similarity matching retrieval; natural self-organization process; order parameter calculation; pseudo inverse matrix; synergetic neural network; Accuracy; Artificial neural networks; Euclidean distance; Image retrieval; Pattern recognition; Prototypes; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Audio Language and Image Processing (ICALIP), 2010 International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-5856-1
  • Type

    conf

  • DOI
    10.1109/ICALIP.2010.5684499
  • Filename
    5684499