3 February 2011 Image segmentation refinement by modeling in turning function space
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Abstract
This work proposes a different approach for the use of turning function space to change shapes in accordance with shape descriptions and consistent with spectral information. The main steps are: (1) segmentation; (2) contour extraction; (3) turning function space transform; (4) classification; (5) shape analysis; and (6) blob enhancement on image space. In the analysis of shape the boundary is modified based on both image and model and constraints are imposed to portions of the turning function. Shape modeling can be done by defining criteria such as linearity, angles and sizes. Results on synthetic examples are presented.
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Carlos F. S. Volotão, Guaraci J. Erthal, Rafael D. C. Santos, Luciano V. Dutra, "Image segmentation refinement by modeling in turning function space", Proc. SPIE 7870, Image Processing: Algorithms and Systems IX, 78701B (3 February 2011); doi: 10.1117/12.876728; https://doi.org/10.1117/12.876728
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