• DocumentCode
    457293
  • Title

    A novel Virus Infection Clustering for Flower Images Identification

  • Author

    Cho, Siu-Yeung ; Lim, Peh-Ti

  • Author_Institution
    Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1038
  • Lastpage
    1041
  • Abstract
    Computer-aided flower identification is a very useful tool for plant species identification aspect. In this paper, a study was made on a development of content based image retrieval system to characterize flower images efficiently. In this system, a novel virus infection clustering is proposed to cluster the image database to improve the searching efficiency. Experimental results show that the developed system can yield promising results for flower image retrieval
  • Keywords
    botany; content-based retrieval; image recognition; image retrieval; visual databases; computer-aided flower identification; content based image retrieval system; flower images identification; image database; plant species identification; virus infection clustering; Content based retrieval; Feature extraction; Feedback; Humans; Image databases; Image recognition; Image retrieval; Image segmentation; Pattern recognition; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.144
  • Filename
    1699385