Scale-space line curvature estimation for straight line and circle detection

Authors:
E. V. Semeikina;D. V. Yurin;A. S. Krylov;Kuo-Liang Chung;Yong-Huai Huang
Affiliations:
Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetic, Moscow State University, Moscow, Russia 119991;Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetic, Moscow State University, Moscow, Russia 119991;Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and Cybernetic, Moscow State University, Moscow, Russia 119991;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, R.O.C. 10672;Institute of Computer and Communication Engineering and Department of Electronic Engineering Jinwen University of Science and Technology, Hsin-Tien, Taipei, Taiwan, R.O.C. 23154
Venue:
Pattern Recognition and Image Analysis
Year:
2012

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Abstract

A scale-space algorithm for estimating the local curvature of lines (edges or isolines) is presented. Two variants of edge curvature estimation based on differential invariants are suggested and compared. The first variant uses the edge curvature formula derived in the paper and the second is based on image preprocessing, which allows one to use the isoline curvature formula for edge curvature estimation. An analysis of scale selection needed to reach a desired accuracy is presented. Also, noise influence analysis has been performed. The application of curvature estimation to detection of straight lines and circles is suggested and implemented. Curvature information usage in parametric curve detection speeds up search algorithms and makes the results more stable.