• DocumentCode
    2340189
  • Title

    Intelligent citrus seed identification

  • Author

    Bee Theng, Lau

  • Author_Institution
    Sch. of Inf. Technol. & Multimedia, Swinburne Univ. of Technol. Sarawak, Kuching
  • fYear
    2008
  • fDate
    3-5 June 2008
  • Firstpage
    79
  • Lastpage
    83
  • Abstract
    Feature extraction in image processing is a research domain that changes rapidly. [4] introduces a model for identifying seeds from citrus MRI imagery for fruit packaging industry. Hence this research proposed a model for identifying seeds from MRI imagery preprocessed with wavelet transformation and active region identification. The proposed approach segments a citrus imagery into circular layers and wedges to identify the area of interest for seeds. This reduces searching space (in number of pixels) to find out whether a fruit contain seeds. This paper presents the conceptual design and findings from the research on seed identification from citrus imagery segmentation. The improvement might be suitable for bio systems engineering to differentiate fruits with and without seeds.
  • Keywords
    feature extraction; food products; image segmentation; magnetic resonance imaging; production engineering computing; wavelet transforms; MRI imagery; active region identification; citrus imagery segmentation; feature extraction; fruit packaging industry; image processing; intelligent citrus seed identification; wavelet transformation; Difference equations; Electronic mail; Feature extraction; Image processing; Image segmentation; Information technology; Magnetic resonance imaging; Pixel; Shape; Skin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-1717-9
  • Electronic_ISBN
    978-1-4244-1718-6
  • Type

    conf

  • DOI
    10.1109/ICIEA.2008.4582484
  • Filename
    4582484