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A comparison of measures for detecting natural shapes in cluttered backgrounds

  • Lance R. Williams
  • Karvel K. Thornber
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1407)

Abstract

We propose a new measure of perceptual saliency and quantitatively compare its ability to detect natural shapes in cluttered backgrounds to five previously proposed measures. As defined in the new measure, the saliency of an edge is the fraction of closed random walks which contain that edge. The transition probability matrix defining the random walk between edges is based on a distribution of natural shapes modeled by a stochastic motion. Each of the saliency measures in our comparison is a function of a set of affinity values assigned to pairs of edges. Although the authors of each measure define the affinity between a pair of edges somewhat differently, all incorporate the Gestalt principles of good-continuation and proximity in some form. In order to make the comparison meaningful, we use a single definition of affinity and focus instead on the performance of the different functions for combining affinity values. The primary performance criterion is accuracy. We compute false-positive rates in classifying edges as signal or noise for a large set of test figures. In almost every case, the new measure significantly outperforms previous measures.

Keywords

Directed Edge Saliency Function Affinity Function Illusory Contour Oriented Edge 
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 1998

Authors and Affiliations

  • Lance R. Williams
    • 1
  • Karvel K. Thornber
    • 2
  1. 1.Dept. of Computer ScienceUniversity of New MexicoAlbuquerque
  2. 2.NEC Research InstitutePrinceton

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