• DocumentCode
    497310
  • Title

    An Approach for Image Thresholding Using CNN Associated with Histogram Analysis

  • Author

    Kang, Jiayin ; Zhang, Wenjuan

  • Author_Institution
    Sch. of Electron. Eng., Huaihai Inst. of Technol., Lianyungang, China
  • Volume
    1
  • fYear
    2009
  • fDate
    11-12 April 2009
  • Firstpage
    421
  • Lastpage
    424
  • Abstract
    Thresholding is one of the old, simple, and popular techniques for image segmentation, and has been widely studied. In this paper, an approach for image thresholding based on cellular neural network (CNN) associated with histogram analysis is presented. The approach realized by threshold CNN (T-CNN), in which the threshold is obtained via histogram-based automatic searching algorithm. Experimental results on real images show that the proposed approach can extract the objects from the background effectively with better visual quality than other methods.
  • Keywords
    cellular neural nets; image segmentation; T-CNN; cellular neural network; histogram-based automatic searching algorithm; image segmentation; image thresholding; Automation; Cellular neural networks; Histograms; Hopfield neural networks; Image analysis; Image processing; Image segmentation; Mechatronics; Pixel; Robot vision systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
  • Conference_Location
    Zhangjiajie, Hunan
  • Print_ISBN
    978-0-7695-3583-8
  • Type

    conf

  • DOI
    10.1109/ICMTMA.2009.311
  • Filename
    5203002