• DocumentCode
    2364676
  • Title

    Fruit defect detection from color images using ACM and MFCM algorithms

  • Author

    Moradi, Ghobad ; Shamsi, Mousa ; Sedaghi, Mohammad H. ; Alsharif, Mohammad R.

  • Author_Institution
    Branch of Kermanshah Azad Univ., Kermanshah, Iran
  • fYear
    2011
  • fDate
    25-27 April 2011
  • Firstpage
    182
  • Lastpage
    186
  • Abstract
    Segmentation of an image into its components plays an important role in most of the image processing applications. In this article an important application of image processing in determination of fruit quality is studied, and an automatic algorithm is proposed in order to determine fruits skin color defects. Removing of image background and extraction of fruit shape, exactly, at presence of shadow and complex background is considered as an important preprocessing stage. In proposed algorithm at first, background in image is omitted by using active counter model (ACM) algorithm. Finally, the image is segmented using modified FCM (MFCM) algorithm. Experimental results on fruit color images show that proposed algorithm increases accuracy and speed of fruit skin defect detection, considerably.
  • Keywords
    agricultural products; feature extraction; image colour analysis; image segmentation; object detection; pattern clustering; ACM algorithms; MFCM algorithms; active counter model algorithm; color images; fruit quality; fruit shape extraction; fruit skin color defect determination; image background removal; image segmantation; modified fuzzy c-means method; Image segmentation; active contour model; defect detection; fruit color image; fuzzy c-means; image segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Devices, Systems and Applications (ICEDSA), 2011 International Conference on
  • Conference_Location
    Kuala Lumpur
  • ISSN
    2159-2047
  • Print_ISBN
    978-1-61284-388-9
  • Type

    conf

  • DOI
    10.1109/ICEDSA.2011.5959033
  • Filename
    5959033