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In: Perceptual Organization for Artificial Vision Systems, K. Boyer and S. Sarkar, Eds., Kluwer Academic, Boston, 2000
 

Summary: In: Perceptual Organization for Artificial Vision Systems,
K. Boyer and S. Sarkar, Eds., Kluwer Academic, Boston, 2000
Chapter 15
THE CURVE INDICATOR RANDOM FIELD:
CURVE ORGANIZATION VIA
EDGE CORRELATION
Jonas August
Yale University
Steven W. Zucker
Yale University
Abstract Can the organization of local edge measurements into curves be directly related to
natural image structure? By viewing curve organization as a statistical estimation
problem, we suggest that it can. In particular, the classical Gestalt perceptual
organization cues of proximity and good continuation---the basis of many current
curve organization systems---can be statistically measured in images. As a
prior for our estimation approach we introduce the curve indicator random field.
In contrast to other techniques that require contour closure or are based on
a sparse set of detected edges, the curve indicator random field emphasizes
the short­distance, dense nature of organizing curve elements into (possibly)
open curves. Its explicit formulation allows the calculation of its properties

  

Source: August, Jonas - Robotics Institute, School of Computer Science, Carnegie Mellon University

 

Collections: Engineering; Chemistry