• DocumentCode
    1694231
  • Title

    Produce recognition system using data mining algorithm

  • Author

    Chaw, J.K. ; Mokji, M.M.

  • Author_Institution
    Dept. of Microelectron. & Comput. Eng., Univ. Teknol. Malaysia, Skudai, Malaysia
  • fYear
    2012
  • Firstpage
    39
  • Lastpage
    43
  • Abstract
    Produce recognition system is a system that can categorize types of vegetables and fruits based on features extracted from the images. However, there are numerous features that can be extracted from fruits and vegetables such as colour, texture and shape. As a result, it is effort consuming to identify suitable features ad hoc. Thus, data mining is required to discover the most discriminative features for recognition. This paper aims to extend the usage of data mining algorithm to image domain. Data mining algorithm is preferred to other feature selection algorithms because it discovers nuggets of knowledge that can be understood by human whereas classic feature selection techniques provide outputs that can only be managed by learning algorithms.
  • Keywords
    agricultural products; data mining; feature extraction; image colour analysis; image texture; learning (artificial intelligence); shape recognition; data mining algorithm; extracted features; feature selection algorithms; fruits; image domain; learning algorithms; produce recognition system; vegetables; WEKA; data mining; produce recognition system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control System, Computing and Engineering (ICCSCE), 2012 IEEE International Conference on
  • Conference_Location
    Penang
  • Print_ISBN
    978-1-4673-3142-5
  • Type

    conf

  • DOI
    10.1109/ICCSCE.2012.6487112
  • Filename
    6487112