• DocumentCode
    146759
  • Title

    Leaf features based approach for automated identification of medicinal plants

  • Author

    Kumar, E. Sandeep ; Talasila, Viswanath

  • Author_Institution
    Dept. of Telecommun. Eng., M.S Ramaiah Inst. of Technol., Bangalore, India
  • fYear
    2014
  • fDate
    3-5 April 2014
  • Firstpage
    210
  • Lastpage
    214
  • Abstract
    Use of the correct plant extracts is crucial in Ayurvedic treatment. This paper focuses on the automatic identification of medicinal plants that are commonly used in Ayurveda. Previous work indicated a Gaussian distribution for various image related features of the medical plant leaves. This work strengthens this conclusion by extending the results through a better classifier design. In this work, we have considered additional plant species to prove that obtained image features are again Gaussian distributed, with the accuracy of the classifier computed.
  • Keywords
    biology computing; botany; image classification; medical computing; Ayurveda; Ayurvedic treatment; automated medicinal plant identification; classifier design; leaf features based approach; plant extracts; Accuracy; Biomedical imaging; Equations; Feature extraction; Gaussian distribution; Image edge detection; Ayurvedic Medicinal system; Image processing; Statistical parameters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications and Signal Processing (ICCSP), 2014 International Conference on
  • Conference_Location
    Melmaruvathur
  • Print_ISBN
    978-1-4799-3357-0
  • Type

    conf

  • DOI
    10.1109/ICCSP.2014.6949830
  • Filename
    6949830