A non-parametric sequential method for polygonal approximation of digital curves
Pattern Recognition Letters
Optimum polygonal approximation of digitized curves
Pattern Recognition Letters
Techniques for Assessing Polygonal Approximations of Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
An efficient algorithm for the optimal polygonal approximation of digitized curves
Pattern Recognition Letters
Generalization of Spatial Data: Principles and Selected Algorithms
Algorithmic Foundations of Geographic Information Systems, this book originated from the CISM Advanced School on the Algorithmic Foundations of Geographic Information Systems
A Survey of Polygonal Simplification Algorithms
A Survey of Polygonal Simplification Algorithms
Hierarchical representation of digitized curves through dominant point detection
Pattern Recognition Letters
IEEE Transactions on Circuits and Systems for Video Technology
Computational Geometry: Theory and Applications
Equivalent key frames selection based on iso-content principles
IEEE Transactions on Circuits and Systems for Video Technology
Signal segmentation and modelling based on equipartition principle
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Lymphocyte segmentation using the transferable belief model
ICPR'10 Proceedings of the 20th International conference on Recognizing patterns in signals, speech, images, and videos
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In this paper, we present an algorithm based on equal errors principle, which solves the general version of polygonal approximation problem (GPA). The approximation nodes of GPA can be selected anywhere on the original polygonal curve, while the ''classical'' (usually used) polygonal approximation problem (PA) demands the vertices to be a subset of the original polygon vertices. Although the proposed algorithm does not guarantee global minimum distortion, in many cases almost optimal solutions are achieved. Moreover, it is very flexible on changes of error criteria and on curve dimension yielding an alternative and in many cases approximations with lower error (by relaxing the simplification constraint) than the optimal PA methods with about the same computation cost.