Please use this identifier to cite or link to this item: http://monografias.ufrn.br/handle/123456789/6733
Title: Parallel Repairing 3D Fuzzy Images into Well-Composed Images
Authors: Germano, Rafael Lucena
Keywords: well-composedness
Issue Date: 2018
Publisher: Universidade Federal do Rio Grande do Norte
Citation: GERMANO, Rafael Lucena. Parallel Repairing 3D Fuzzy Images into Well-Composed Images. 2018. 52 f. TCC (Graduação) - Curso de Ciência da Computação, Departamento de Informática e Matemática Aplicada, Universidade Federal do Rio Grande do Norte, Natal, 2018.
Portuguese Abstract: This work presents a parallelized version in Compute Unified Device Architecture of the algorithm presented in (SIQUEIRA et al., 2008) for repairing images into well-composed ones, as well as a comparison between heuristics to obtain the well-composed image which minimizes the difference between the generated well-composed image and the original image. The algorithm is based on successively changing the points from one object to another until the image becomes well-composed. Well-composed images are images on which the intersection of the voxels of an object with its complement forms a topological surface. Such images enjoy very useful properties which reduce the processing time of algorithms, such as thinning and surface extraction algorithms. Lastly, the performance of the parallel and sequential versions are compared and an analysis of the produced well-composed images is done.
URI: http://monografias.ufrn.br/jspui/handle/123456789/6733
Other Identifiers: 20170008297
Appears in Collections:Ciência da Computação

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