• DocumentCode
    3077168
  • Title

    Irregularity-based saliency identification and evaluation

  • Author

    Al-Azawi, Mohammad ; Yingjie Yang ; Istance, Howell

  • Author_Institution
    Center for Comput. Intell., De Montfort Univ., Leicester, UK
  • fYear
    2013
  • fDate
    26-28 Dec. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Saliency or Salient regions extractions form images is still a challenging field since it needs some understanding for the image and the nature of the image. The technique that is suitable in some application is not necessarily useful in other application, thus, saliency enhancement is application oriented. In this paper, a new technique of extracting the salient regions from an image is proposed which utilizes the local features of the surrounding region of the pixels. The level of saliency is then decided based on the global comparison of the saliency-enhanced image. To make the process fully automatic a new Fuzzy-Based thresholding technique has been proposed also. The paper contains a survey of the state-of-the-art methods of saliency evaluation and a new saliency evaluation technique was proposed.
  • Keywords
    feature extraction; fuzzy set theory; image enhancement; image segmentation; fuzzy-based thresholding technique; irregularity-based saliency evaluation; irregularity-based saliency identification; local features; saliency-enhanced image; salient region extraction; Computational intelligence; Computer vision; Conferences; Data mining; Feature extraction; Histograms; Visualization; Attention; Image; Irregularity; Saliency;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Computing Research (ICCIC), 2013 IEEE International Conference on
  • Conference_Location
    Enathi
  • Print_ISBN
    978-1-4799-1594-1
  • Type

    conf

  • DOI
    10.1109/ICCIC.2013.6724128
  • Filename
    6724128