The accuracy and precision of curvature estimation methods

Deals with the estimation of curvature from digital image data, especially the selection of a curvature estimation procedure based on its accuracy and precision. The authors establish that almost all curvature estimation techniques from literature suffer from a severe directional inaccuracy and/or poor precision (errors depend on the method, orientation and scale ranging from 1% to more than 200%). A practical solution to the curvature estimation problem is presented.<<ETX>>

[1]  James C. Bezdek,et al.  Curvature and Tangential Deflection of Discrete Arcs: A Theory Based on the Commutator of Scatter Matrix Pairs and Its Application to Vertex Detection in Planar Shape Data , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Farzin Mokhtarian,et al.  Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Michael Brady,et al.  The Curvature Primal Sketch , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Yiu-Tong Chan,et al.  A simple approach for the estimation of circular arc center and its radius , 1989, Comput. Vis. Graph. Image Process..

[5]  Ian T. Young,et al.  An Analysis Technique for Biological Shape. I , 1974, Inf. Control..

[6]  Arnold W. M. Smeulders,et al.  Best Linear Unbiased Estimators for Properties of Digitized Straight Lines , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  G. Medioni,et al.  Corner detection and curve representation using cubic B-splines , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.