• DocumentCode
    3429535
  • Title

    Automatic ship classification by superstructure moment invariants and two-stage classifier

  • Author

    Zhongliang, Qian ; Wenjun, Wang

  • Author_Institution
    Dept. of Inf. & Electron. Eng., Zhejiang Univ., Hangzhou, China
  • fYear
    1992
  • fDate
    16-20 Nov 1992
  • Firstpage
    544
  • Abstract
    Moment invariants have been used as descriptive feature in a variety of object recognition applications. A new descriptive scheme called superstructure moment invariants is presented. The authors calculate moment invariants only for the superstructure of a ship, which are different from the general moment invariants for the entire ship. The analysis of the theory and the statistics of the experimental results shows that the classification accuracy using superstructure moment invariants for the ship is higher than that of general ones. A modified 1-NN classifier, two stage classification is presented, which reduces the time expense and has a high classification accuracy
  • Keywords
    pattern recognition; ships; automatic ship classification; object recognition; superstructure moment invariants; two-stage classifier; Aircraft; Azimuth; Ear; Libraries; Marine vehicles; Neural networks; Object recognition; Sea measurements; Shape; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Singapore ICCS/ISITA '92. 'Communications on the Move'
  • Print_ISBN
    0-7803-0803-4
  • Type

    conf

  • DOI
    10.1109/ICCS.1992.254892
  • Filename
    254892