Thresholding for segmentation and extraction of extensive objects on digital images

  • Authors:

  • Vladimir Volkov

  • Affiliations:

  • State University of Telecommunications, Saint-Petersburg, Russia

  • Venue:
  • KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
  • Year:
  • 2009

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Abstract

The threshold setting problem is investigated for segmentation and extraction of extensive objects on digital images. Image processing structure is considered which includes thresholding for binarization. A new method for dynamic threshold setting and control is proposed which is based on the analysis of isolated fragments to be extracted in the making of segmentation. Extraction of extensive objects is obtained by the use of sequential erosion of isolated fragments on images. Number of points deleted is used for dynamic thresholding. The method proposed has optimality properties.