Detection of Non-convex Objects by Dynamic Programming

  • Authors:

  • Andree Große;Kai Rothaus;Xiaoyi Jiang

  • Affiliations:

  • Department of Mathematics and Computer Science, University of Münster, Münster, Germany D-48149;Department of Mathematics and Computer Science, University of Münster, Münster, Germany D-48149;Department of Mathematics and Computer Science, University of Münster, Münster, Germany D-48149

  • Venue:
  • CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
  • Year:
  • 2009

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Abstract

In this work we present the Rack algorithm for the detection of optimal non-convex contours in an image. It represents a combination of an user-driven image transformation and dynamic programming. The goal is to detect a closed contour in a scene based on the image's edge strength. For this, we introduce a graph construction technique based on a "rack" and derive the image as a directed acyclic graph (DAG). In this graph, the shortest path with respect to an adequate cost function can be calculated efficiently via dynamic programming. Results demonstrate that this approach works well for a certain range of images and has big potential for most other images.