Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Segmentation of edges into lines and arcs
Image and Vision Computing
On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Advanced animation and rendering techniques
Advanced animation and rendering techniques
Detection of significant points and polygonal approximation of digitized curves
Pattern Recognition Letters
Pattern Recognition Letters
Another look at the dominant point detection of digital curves
Pattern Recognition Letters
Techniques for Assessing Polygonal Approximations of Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape description using cubic polynomial Bezier curves
Pattern Recognition Letters
Computer Processing of Line-Drawing Images
ACM Computing Surveys (CSUR)
Pattern Recognition Letters
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Approximation of digital curves with line segments and circular arcs using genetic algorithms
Pattern Recognition Letters
Face Recognition Using Interpolated Bezier Curve Based Representation
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Lossless data embedding in electronic inks
IEEE Transactions on Information Forensics and Security
Curve fitting using coevolutionary genetic algorithms
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part II
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In this paper we present an efficient technique for piecewise cubic Bezier approximation of digitized curve. An adaptive breakpoint detection method divides a digital curve into a number of segments and each segment is approximated by a cubic Bezier curve so that the approximation error is minimized. Initial approximated Bezier control points for each of the segments are obtained by interpolation technique i.e. by the reverse recursion of De Castaljau's algorithm. Two methods, two-dimensional logarithmic search algorithm (TDLSA) and an evolutionary search algorithm (ESA), are introduced to find the best-fit Bezier control points from the approximate interpolated control points. ESA based refinement is proved to be better experimentally. Experimental results show that Bezier approximation of a digitized curve is much more accurate and uses less number of points compared to other approximation techniques.