• DocumentCode
    3418320
  • Title

    A new method for fruits recognition system

  • Author

    Seng, Woo Chaw ; Mirisaee, Seyed Hadi

  • Author_Institution
    Fac. of Comput. Sci. & Inf. Technol., Univ. of Malaya, Kuala Lumpur, Malaysia
  • Volume
    01
  • fYear
    2009
  • fDate
    5-7 Aug. 2009
  • Firstpage
    130
  • Lastpage
    134
  • Abstract
    Several fruit recognition techniques are developed based upon color and shape attributes. However, different fruit images may have similar or identical color and shape values. Hence, using color features and shape features analysis methods are still not robust and effective enough to identify and distinguish fruits images. A new fruit recognition system has been proposed, which combines three features analysis methods: color-based, shape-based and size-based in order to increase accuracy of recognition. The proposed method classifies and recognizes fruit images based on obtained feature values by using nearest neighbours classification. Consequently, our system shows the fruit name and a short description to user. The proposed fruit recognition system analysis classifies and identifies fruits successfully up to 90% accuracy. This system also serves as a useful tool in a variety of fields such as education, image retrieval and plantation science.
  • Keywords
    computer vision; feature extraction; image recognition; color features; computer vision; education; feature extraction; fruit images; fruits recognition system; image retrieval; nearest neighbours classification; plantation science; shape features; Classification algorithms; Computer science; Feature extraction; Image analysis; Image color analysis; Image recognition; Machine learning algorithms; Pattern recognition; Robustness; Shape; KNN classification; computer vision; feature extraction; fruit; recognition; shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Engineering and Informatics, 2009. ICEEI '09. International Conference on
  • Conference_Location
    Selangor
  • Print_ISBN
    978-1-4244-4913-2
  • Type

    conf

  • DOI
    10.1109/ICEEI.2009.5254804
  • Filename
    5254804