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SHAPE ANALYSIS ALGORITHM BASED ON INFORMATION THEORY D. L. Page, A. F. Koschan, S. R. Sukumar, B. Roui-Abidi, M. A. Abidi
 

Summary: SHAPE ANALYSIS ALGORITHM BASED ON INFORMATION THEORY
D. L. Page, A. F. Koschan, S. R. Sukumar, B. Roui-Abidi, M. A. Abidi
Imaging, Robotics, and Intelligent Systems Laboratory
University of Tennessee, Knoxville, Tennessee 37996-2100, davidpage@ieee.org
ABSTRACT
In this paper, we describe an algorithm to measure the shape com-
plexity for discrete approximations of planar curves in 2D images
and manifold surfaces for 3D triangle meshes. We base our algo-
rithm on shape curvature, and thus we compute shape information
as the entropy of curvature. We present definitions to estimate
curvature for both discrete curves and surfaces and then formu-
late our theory of shape information from these definitions. We
demonstrate our algorithm with experimental results.
1. INTRODUCTION
Claude Shannon's seminal paper in 1948 [1] launched a revolu-
tionary field of mathematics that has become known as informa-
tion theory. Shannon's work formulates a powerful and general
theory to quantize information and in particular to describe in-
formation in a probabilistic framework. Researchers have applied
information theory to such diverse topics as communications, as-

  

Source: Abidi, Mongi A. - Department of Electrical and Computer Engineering, University of Tennessee

 

Collections: Computer Technologies and Information Sciences