Estimation of a circular arc center and its radius
Computer Vision, Graphics, and Image Processing
Corner detection and curve representation using cubic B-spline
Computer Vision, Graphics, and Image Processing
Segmentation of edges into lines and arcs
Image and Vision Computing
A simple approach for the estimation of circular arc center and its radius
Computer Vision, Graphics, and Image Processing
Adaptive Smoothing: A General Tool for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Based Detection of Corners of Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A non-parametric sequential method for polygonal approximation of digital curves
Pattern Recognition Letters
Optimum polygonal approximation of digitized curves
Pattern Recognition Letters
Optimal spline fitting to planar shape
Signal Processing
Segmentation of digital plane curves: a dynamic focusing approach
Pattern Recognition Letters
A new method for polygonal approximation using genetic algorithms
Pattern Recognition Letters
Pattern Recognition Letters
Digitized Circular Arcs: Characterization and Parameter Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Curve-fitting with piecewise parametric cubics
SIGGRAPH '83 Proceedings of the 10th annual conference on Computer graphics and interactive techniques
Least-squares smoothing of 3D digital curves
Real-Time Imaging - Special issue on multi-dimensional image processing
A randomized knot insertion algorithm for outline capture of planar images using cubic spline
Proceedings of the 2007 ACM symposium on Applied computing
Outline Capture of Images by Multilevel Coordinate Search on Cubic Splines
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
ACM SIGGRAPH Asia 2010 papers
Circular arc reconstruction of digital contours with chosen Hausdorff error
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
Decomposition of a curve into arcs and line segments based on dominant point detection
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Segmentation and multi-model approximation of digital curves
Pattern Recognition Letters
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This paper presents a new method to produce a representation of a digital curve. The method first finds a curvature representation for a Gaussian-filtered curve. The curvature representation is then smoothed by using the adaptive smoothing technique. Finally, we segment the digital curve and fit each segment with a line segment or a circular arc based on the smoothed curvature representation. Experimental results show the applicability and efficiency of the proposed method.