A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Preserving Topology by a Digitization Process
Journal of Mathematical Imaging and Vision
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
Computer and Robot Vision
Correction for the Dislocation of Curved Surfaces Caused by the PSF in 2D and 3D CT Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Towards a general sampling theory for shape preservation
Image and Vision Computing
What can we learn from discrete images about the continuous world?
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
Region and edge-adaptive sampling and boundary completion for segmentation
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
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Existing methods for segmentation by edgel linking are based on heuristics and give no guarantee for a topologically correct result. In this paper, we propose an edgel linking algorithm based on a new sampling theorem for shape digitization, which guarantees a topologically correct reconstruction of regions and boundaries if the edgels approximate true object edges with a known maximal error. Experiments on real and generated images demonstrate the good performance of the new method and confirm the predictions of our theory.