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Previous issue date: 2008-08-04 / A 3D binary image is considered well-composed if, and only if, the union of the faces shared by the foreground and background voxels of the image is a surface in R3. Wellcomposed images have some desirable topological properties, which allow us to simplify and optimize algorithms that are widely used in computer graphics, computer vision and image processing. These advantages have fostered the development of algorithms to repair bi-dimensional (2D) and three-dimensional (3D) images that are not well-composed.
These algorithms are known as repairing algorithms. In this dissertation, we propose two repairing algorithms, one randomized and one deterministic. Both algorithms are
capable of making topological repairs in 3D binary images, producing well-composed images similar to the original images. The key idea behind both algorithms is to iteratively change the assigned color of some points in the input image from 0 (background)to 1 (foreground) until the image becomes well-composed. The points whose colors are changed by the algorithms are chosen according to their values in the fuzzy connectivity map resulting from the image segmentation process. The use of the fuzzy connectivity map ensures that a subset of points chosen by the algorithm at any given iteration is the one with the least affinity with the background among all possible choices / Uma imagem bin?ria 3D ? considerada bem-composta se, e somente se, a uni?o das faces compartilhadas pelos voxels do foreground e do background da referida imagem ? uma superf?cie em R3 . Imagens bem-compostas se beneficiam de propriedades topol?gicas desej?veis, as quais nos permitem simplificar e otimizar algoritmos amplamente usados na computa??o gr?fica, vis?o computacional e processamento de imagens. Estas vantagens t?m motivado o desenvolvimento de algoritmos para reparar imagens bi e tridimensionais que n?o sejam bem-compostas. Estes algoritmos s?o conhecidos como algoritmos reparadores. Nesta disserta??o, propomos dois algoritmos reparadores, um aleat?rio e um determin?stico. Ambos s?o capazes de fazer reparos topol?gicos em imagens bin?rias 3D, produzindo imagens bem-compostas similares ?s imagens originais. A id?ia fundamental por tr?s de ambos algoritmos ? mudar iterativamente a cor atribu?da de alguns pontos da imagem de entrada de 0 (background) para 1 (foreground) at? a imagem se tornar bem-composta. Os pontos cujas cores s?o mudadas pelos algoritmos s?o escolhidos de acordo com seus valores no mapa de conectividade fuzzy, resultante do processo de segmenta??o da imagem. O uso do mapa de conectividade fuzzy garante que um subconjunto dos pontos escolhidos pelo algoritmo em qualquer itera??o seja um com a menor afinidade com o background dentre todas as escolhas poss?veis
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/17991 |
| Date | 04 August 2008 |
| Creators | Cosme, ?ria Caline Saraiva |
| Contributors | CPF:79228860472, http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4791070J6, Siqueira, Marcelo Ferreira, CPF:67285619434, http://lattes.cnpq.br/7340736676138238, Bedregal, Benjamin Ren? Callejas, CPF:90688384404, http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4781417E7, Gon?alves, Luiz Marcos Garcia, CPF:32541457120, http://lattes.cnpq.br/1562357566810393, Carvalho, Bruno Motta de |
| Publisher | Universidade Federal do Rio Grande do Norte, Programa de P?s-Gradua??o em Sistemas e Computa??o, UFRN, BR, Ci?ncia da Computa??o |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Format | application/pdf |
| Source | reponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN |
| Rights | info:eu-repo/semantics/openAccess |
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