• DocumentCode
    678413
  • Title

    Traditional Chinese Patterns Analysis Based on Moment Invariants

  • Author

    Li Xiao-Niu ; Guo Hai ; Meng Jia-Na ; Wang Bo

  • Author_Institution
    Coll. of Comput. Sci. & Eng., Dalian Nat. Univ., Dalian, China
  • fYear
    2013
  • fDate
    11-13 Dec. 2013
  • Firstpage
    582
  • Lastpage
    585
  • Abstract
    In this paper, the numerical analysis is studied with the help of computer technology to geometry texture features of traditional Chinese art patterns. First, the gray-scale distribution of an original image is adjusted by using the gray value transformation and a new image with five gray levels is formed. Second, by using the geometry invariant moment method in image analysis and processing, 12 geometry invariant moments of the new gray image as its geometric texture feature vector is calculated. Lastly, it carries on the classification using k-means clustering method in clustering analysis. Through specific examples, it shows that the method is simple in principle, easy realized, and it will provide a reference method for computer analysis and the processing of traditional Chinese art pattern.
  • Keywords
    art; computational geometry; image texture; pattern clustering; Chinese art pattern; Chinese art patterns; Chinese patterns analysis; computer analysis; computer technology; geometric texture feature vector; geometry invariant moment method; geometry texture features; gray value transformation; gray-scale distribution; image analysis; image processing; k-means clustering method; moment invariants; Art; Computers; Educational institutions; Gray-scale; Histograms; Pattern analysis; Pattern recognition; histogram equalization; moment invariants; texture feature analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mobile Ad-hoc and Sensor Networks (MSN), 2013 IEEE Ninth International Conference on
  • Conference_Location
    Dalian
  • Print_ISBN
    978-0-7695-5159-3
  • Type

    conf

  • DOI
    10.1109/MSN.2013.18
  • Filename
    6726401