A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding axes of skewed symmetry
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Corner detection and curve representation using cubic B-spline
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Edgel-aggregation and edge-description
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An introduction to splines for use in computer graphics & geometric modeling
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Piecewise-circular curves for geometric modeling
IBM Journal of Research and Development
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual organization for computer vision
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B-spline contour representation and symmetry detection
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On characterizing ribbons and finding skewed symmetries
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A new curve tracing algorithm and some applications
Curves and surfaces
Adaptive Smoothing: A General Tool for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Hierarchical Decomposition and Axial Shape Description
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
IEEE Transactions on Pattern Analysis and Machine Intelligence
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International Journal of Computer Vision
Hierarchical Decomposition and Axial Shape Description
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skeletonization of Ribbon-Like Shapes Based on a New Wavelet Function
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Optimal Image and Video Closure by Superpixel Grouping
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Multiscale Symmetric Part Detection and Grouping
International Journal of Computer Vision
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The detection of edges is only one of many steps in the understanding of images. Further processing necessarily involves grouping operations between contours. We present a representation of edge contours by approximating B-splines and show that such a representation facilitates the extraction of symmetries between contours. Our representation is rich, compact, stable, and does not critically depend on feature extraction. We turn our attention to the detection of three types of symmetries: skew symmetries and parallel symmetries, which have proven to be of great importance in inferring shape from contour, and smooth local symmetries, which have been used for planar shape description. We show that our representation facilitates the computation of these symmetries.