• DocumentCode
    3202011
  • Title

    Combining image features for image classification

  • Author

    Baharudin, B. ; Qahwaji, R. ; Jiang, J. ; Rahman, P.

  • fYear
    2007
  • fDate
    25-28 Nov. 2007
  • Firstpage
    268
  • Lastpage
    272
  • Abstract
    In this paper, we use neural networks and support vector machines (SVMpsilas) to compare the classification performances of four proposed image features. Of the four image features, two are developed by the authors, whereas the other two are well-known image features which we included for benchmark purposes. Indirectly the performances of the two image classifiers are compared. Based on the experiments that were carried out, it was found that our proposed combined image features gave the best performance amongst the four image features. In terms of the classifiers, SVM proved to be the better classifier.
  • Keywords
    feature extraction; image classification; learning (artificial intelligence); neural nets; support vector machines; feature extraction; image classification; image features; machine learning; neural networks; support vector machines; Artificial neural networks; Feature extraction; Image classification; Image retrieval; Machine learning; Machine learning algorithms; Neural networks; Shape; Support vector machine classification; Support vector machines; Feature extraction; image classification; machine learning; neural networks; support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
  • Conference_Location
    Kuala Lumpur
  • Print_ISBN
    978-1-4244-1355-3
  • Electronic_ISBN
    978-1-4244-1356-0
  • Type

    conf

  • DOI
    10.1109/ICIAS.2007.4658388
  • Filename
    4658388