Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-parametric dominant point detection
Pattern Recognition
An algorithm for detection of dominant points and polygonal approximation of digitized 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
Convexity rule for shape decomposition based on discrete contour evolution
Computer Vision and Image Understanding
Image Editing in the Contour Domain
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reduced-search dynamic programming for approximation of polygonal curves
Pattern Recognition Letters
Polygonal approximation of closed discrete curves
Pattern Recognition
A fast evaluation criterion for the recognition of occluded shapes
Robotics and Autonomous Systems
Dominant point detection by reverse polygonization of digital curves
Image and Vision Computing
Tangential cover for thick digital curves
Pattern Recognition
Polygonal approximation of digital planar curves through break point suppression
Pattern Recognition
Data reduction of large vector graphics
Pattern Recognition
A discrete geometry approach for dominant point detection
Pattern Recognition
Fast Polygonal Approximation of Digital Curves Using Relaxed Straightness Properties
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper presents a non-heuristic and control parameter independent dominant point detection method. It is based on the suppression of break points and provides a more balanced performance than the recent break point suppression methods. It is made non-heuristic using an analytical error bound for digitizing a line segment. It provides a good combination of compression ratio and error metrics by avoiding both over-fitting and under-fitting.