• DocumentCode
    2429811
  • Title

    Regions of Interest extraction based on visual attention model and watershed segmentation

  • Author

    Zhang, Jing ; Zhuo, Li ; Shen, Lansun

  • Author_Institution
    Signal & Inf. Process. Lab., Beijing Univ. of Technol., Beijing
  • fYear
    2008
  • fDate
    7-11 June 2008
  • Firstpage
    375
  • Lastpage
    378
  • Abstract
    The presented research addressed a novel visual attention model and watershed segmentation based approach of regions of interest (ROIs) extraction, which automatically extracts ROIs and copes with the watershed over-segmentation. This approach uses visual attention model to locate salient points, in which the winner point, the most salient point, is selected as the seed point of watershed segmentation. ROIs are extracted by combining salient regions with watershed segmented regions. The focus of attention (FOA) is shifted to measure the importance or interest of the extracted regions. The experimental results show that the proposed method is effective to reduce over-segmentation in auto-extracting ROIs and performs well for different objects.
  • Keywords
    feature extraction; image segmentation; focus of attention; regions of interest extraction; visual attention; watershed segmentation; Chaos; Data mining; Digital images; Focusing; Image retrieval; Image segmentation; Information processing; Neural networks; Object detection; Signal processing; FOA; ROIs; Visual Attention Model; Watershed Segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Signal Processing, 2008 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-2310-1
  • Electronic_ISBN
    978-1-4244-2311-8
  • Type

    conf

  • DOI
    10.1109/ICNNSP.2008.4590375
  • Filename
    4590375