Abstract
This work explores novel alternatives to conventional linear homotopy to enhance the quality of resulting transitions from object deformation applications. Studied/introduced approaches extend the linear mapping to other representations that provides smooth transitions when deforming objects while homotopy conditions are fulfilled. Such homotopy approaches are based on transcendental functions (TFH) in both simple and parametric versions. As well, we propose a variant of an existing quality indicator based on the ratio between the coefficients curve of resultant homotopy and that of a less-realistic, reference homotopy. Experimental results depict the effect of proposed TFH approaches regarding its usability and benefit for interpolating images formed by homotopic objects with smooth changes.
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This work is supported by the “Smart Data Analysis Systems - SDAS” group (http://sdas-group.com).
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Salazar-Castro, J.A. et al. (2018). Advances in Homotopy Applied to Object Deformation. In: Rojas, I., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2018. Lecture Notes in Computer Science(), vol 10814. Springer, Cham. https://doi.org/10.1007/978-3-319-78759-6_22
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DOI: https://doi.org/10.1007/978-3-319-78759-6_22
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