Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-01-26T17:46:31Z No. of bitstreams: 1 JoseFranciscoDaSilvaNeto_DISSERT.pdf: 5950864 bytes, checksum: 5306cd9802b9aa1c09288d75c32ccbe2 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2016-01-28T18:00:31Z (GMT) No. of bitstreams: 1 JoseFranciscoDaSilvaNeto_DISSERT.pdf: 5950864 bytes, checksum: 5306cd9802b9aa1c09288d75c32ccbe2 (MD5) / Made available in DSpace on 2016-01-28T18:00:31Z (GMT). No. of bitstreams: 1 JoseFranciscoDaSilvaNeto_DISSERT.pdf: 5950864 bytes, checksum: 5306cd9802b9aa1c09288d75c32ccbe2 (MD5) Previous issue date: 2014-09-25 / Segmenta??o digital de imagens ? o processo de atribuir r?tulos distintos a diferentes objetos em uma imagem digital, e o algoritmo de segmenta??o fuzzy tem sido utilizado com sucesso na segmenta??o de imagens de diversas modalidades. Contudo, o algoritmo tradicional de segmenta??o fuzzy falha ao segmentar objetos que s?o caracterizados por texturas cujos padr?es n?o podem ser descritos adequadamente por simples estat?sticas computadas sobre uma ?rea restrita. Neste trabalho apresentamos uma extens?o do algoritmo de segmenta??o fuzzy que realiza segmenta??o de texturas empregando fun??es de afinidade adaptativas e o estendemos a imagens tridimensionais. Fun??es de afinidade adaptativas mudam o tamanho da ?rea em que s?o calculados os descritores da textura de acordo com as caracter?sticas da textura processada, enquanto imagens tridimensionais podem ser descritas como um conjunto finito de imagens bidimensionais. O algoritmo ent?o segmenta o volume com uma ?rea apropriada calculada para cada textura, tornando poss?vel obter boas estimativas dos volumes reais das estruturas alvo do processo de segmenta??o. Experimentos ser?o realizados com dados sint?ticos e reais obtidos no estudo de segmenta??o de tumores cerebrais em imagens m?dicas adquiridas atrav?s de exames de Resson?ncia Magn?tica / Digital image segmentation is the process of assigning distinct labels to different objects in a digital image, and the fuzzy segmentation algorithm has been used successfully in the segmentation of images from several modalities. However, the traditional fuzzy segmentation algorithm fails to segment objects that are characterized by textures whose patterns cannot be successfully described by simple statistics computed over a very restricted area. In this paper we present an extension of the fuzzy segmentation algorithm that achieves the segmentation of textures by employing adaptive affinity functions as long as we extend the algorithm to tridimensional images. The adaptive affinity functions change the size of the area where they compute the texture descriptors, according to the characteristics of the texture being processed, while three dimensional images can be described as a finite set of two-dimensional images. The algorithm then segments the volume image with an appropriate calculation area for each texture, making it possible to produce good estimates of actual volumes of the target structures of the segmentation process. We will perform experiments with synthetic and real data in applications such as segmentation of medical imaging obtained from magnetic rosonance