Chapter

Computer Vision – ACCV 2009

Volume 5994 of the series Lecture Notes in Computer Science pp 123-134

From Ramp Discontinuities to Segmentation Tree

  • Emre AkbasAffiliated withBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign
  • , Narendra AhujaAffiliated withBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign

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Abstract

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.