• DocumentCode
    2576454
  • Title

    Improvement of Texture Image Retrieval Algorithm Based on Sparse Coding

  • Author

    Yang, Yansi ; Yang, Yingyun ; Zeng, Xuan

  • Author_Institution
    Inf. Eng. Sch., Commun. Univ. of China, Beijing, China
  • fYear
    2012
  • fDate
    10-12 Oct. 2012
  • Firstpage
    501
  • Lastpage
    506
  • Abstract
    The demerits of the texture image retrieval algorithm based on sparse coding are found expression in the low recall and inconspicuous serial priority of qualified images. Several methods are presented in this paper to improve the performance of the image retrieval algorithm. Firstly, Brodatz texture image filter basis function is used for processing the texture images, thereafter, the kurtosis is added to generate the eigenvector, finally, the joint-scale filter basis is utilized to advance the filter effect. Experimental results indicate that the performance of the proposed methods is positive.
  • Keywords
    eigenvalues and eigenfunctions; filtering theory; image coding; image retrieval; image texture; Brodatz texture image filter basis function; eigenvector; image retrieval algorithm improvement; inconspicuous serial priority; joint-scale filter basis; kurtosis; low recall; sparse coding; Filtering algorithms; Filtering theory; Hidden Markov models; Image coding; Image retrieval; Libraries; Mathematical model; Feature Extraction; Image Retrieval; Natural Images; Sparse Coding Theory of Visual Perception; Texture Image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2012 International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4673-2624-7
  • Type

    conf

  • DOI
    10.1109/CyberC.2012.92
  • Filename
    6385019