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Perceptual Grouping Based on Iterative Multi-scale Tensor Voting
[chapter]
2006
Lecture Notes in Computer Science
We propose a new approach for perceptual grouping of oriented segments in highly cluttered images based on tensor voting. Segments are represented as second-order tensors and communicate with each other through a voting scheme that incorporates the Gestalt principles of visual perception. An iterative scheme has been devised which removes noise segments in a conservative way using multi-scale analysis and re-voting. We have tested our approach on data sets composed of real objects in real
doi:10.1007/11919629_87
fatcat:wgrdhviiangbvkwfa4tgmfa7na