• DocumentCode
    2495287
  • Title

    An improved image segmentation algorithm for salient object detection

  • Author

    Liu, Yuee ; Zhang, Jinglan ; Tjondronegoro, Dian ; Geva, Shlomo ; Li, Zhengrong

  • Author_Institution
    Fac. of Inf. Technol., Queensland Univ. of Technol., Brisbane, QLD
  • fYear
    2008
  • fDate
    26-28 Nov. 2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Semantic object detection is one of the most important and challenging problems in image analysis. Segmentation is an optimal approach to detect salient objects, but often fails to generate meaningful regions due to over-segmentation. This paper presents an improved semantic segmentation approach which is based on JSEG algorithm and utilizes multiple region merging criteria. The experimental results demonstrate that the proposed algorithm is encouraging and effective in salient object detection.
  • Keywords
    image segmentation; object detection; image analysis; image segmentation; multiple region merging criteria; salient object detection; semantic object detection; Humans; Image color analysis; Image segmentation; Image texture analysis; Information technology; Layout; Merging; Object detection; Robustness; Shape; JSEG; region merging; salient object; semantic segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Vision Computing New Zealand, 2008. IVCNZ 2008. 23rd International Conference
  • Conference_Location
    Christchurch
  • Print_ISBN
    978-1-4244-3780-1
  • Electronic_ISBN
    978-1-4244-2583-9
  • Type

    conf

  • DOI
    10.1109/IVCNZ.2008.4762141
  • Filename
    4762141