• DocumentCode
    496330
  • Title

    Iris Recognition System Design and Development of Large Animals for Tracing Source of Infection

  • Author

    Wang, Xiaoqiang ; Zhao, Lindu ; Kong, Qiang

  • Author_Institution
    Inst. of Syst. Eng., Southeast Univ., China
  • Volume
    1
  • fYear
    2009
  • fDate
    24-26 April 2009
  • Firstpage
    610
  • Lastpage
    613
  • Abstract
    Iris recognition system design and development of large animals is used to make the large animals be recognizable and traceability from the farm to the slaughterhouse. We can identify the animals when people find it carrying infectious diseases. On the basis of experiments on cows, this paper introduces the iris recognition system design; and we mainly introduce the algorithms of edge detection and iris-encoding used in this system. Iris images are acquired by special capture device. The images will be translated to iris-encoding by image preprocessing, feature extraction and matching operations. By calculating the hamming distance between iris-encoding of different individuals, we can distinguish different individuals. The result of the iris recognition can help us to identify where the animals carrying infection virus come from, and then find the source of infection.
  • Keywords
    biometrics (access control); diseases; edge detection; feature extraction; image coding; image matching; medical image processing; veterinary medicine; edge detection; encoding; feature extraction; hamming distance; image preprocessing; infection virus; infectious disease; iris recognition system design; large animal infection source tracing; matching operation; Animals; Design engineering; Design optimization; Diseases; Hardware; Humans; Image coding; Image edge detection; Iris recognition; Prototypes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
  • Conference_Location
    Sanya, Hainan
  • Print_ISBN
    978-0-7695-3605-7
  • Type

    conf

  • DOI
    10.1109/CSO.2009.271
  • Filename
    5193770