From Ramp Discontinuities to Segmentation Tree

  • Emre Akbas
  • Narendra Ahuja
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5994)


This paper presents a new algorithm for low-level multiscale segmentation of images. The algorithm is designed to detect image regions regardless of their shapes, sizes, and levels of interior homogeneity, by doing a multiscale analysis without assuming any prior models of region geometry. As in previous work, a region is modeled as a homogeneous set of connected pixels surrounded by ramp discontinuities. A new transform, called the ramp transform, is described, which is used to detect ramp discontinuities and seeds for all regions in an image. Region seeds are grown towards the ramp discontinuity areas by utilizing a relaxation labeling procedure. Segmentation is achieved by analyzing the output of this procedure at multiple photometric scales. Finally, all detected regions are organized into a tree data structure based on their recursive containment relations. Experiments on real and synthetic images verify the desired properties of the proposed algorithm.


Segmentation Algorithm Synthetic Image Boundary Pixel Tree Data Structure Connected Pixel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Emre Akbas
    • 1
  • Narendra Ahuja
    • 1
  1. 1.Beckman Institute for Advanced Science and TechnologyUniversity of Illinois at Urbana-Champaign 

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