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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Segmenta??o fuzzy de imagens e v?deos

Oliveira, Lucas de Melo 23 February 2007 (has links)
Made available in DSpace on 2014-12-17T15:48:12Z (GMT). No. of bitstreams: 1 LucasMO.pdf: 1455032 bytes, checksum: 6bc4218b3d779cfc9915c6a2efda34f1 (MD5) Previous issue date: 2007-02-23 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / Image segmentation is the process of subdiving an image into constituent regions or objects that have similar features. In video segmentation, more than subdividing the frames in object that have similar features, there is a consistency requirement among segmentations of successive frames of the video. Fuzzy segmentation is a region growing technique that assigns to each element in an image (which may have been corrupted by noise and/or shading) a grade of membership between 0 and 1 to an object. In this work we present an application that uses a fuzzy segmentation algorithm to identify and select particles in micrographs and an extension of the algorithm to perform video segmentation. Here, we treat a video shot is treated as a three-dimensional volume with different z slices being occupied by different frames of the video shot. The volume is interactively segmented based on selected seed elements, that will determine the affinity functions based on their motion and color properties. The color information can be extracted from a specific color space or from three channels of a set of color models that are selected based on the correlation of the information from all channels. The motion information is provided into the form of dense optical flows maps. Finally, segmentation of real and synthetic videos and their application in a non-photorealistic rendering (NPR) toll are presented / Segmenta??o de imagens ? o processo que subdivide uma imagem em partes ou objetos de acordo com alguma caracter?stica comum. J? na segmenta??o de v?deos, al?m dos quadros serem divididos em fun??o de alguma caracter?stica, ? necess?rio obter uma coer?ncia temporal entre as segmenta??es de frames sucessivos do v?deo. A segmenta??o fuzzy ? uma t?cnica de segmenta??o por crescimento de regi?es que determina para cada elemento da imagem um grau de pertin?ncia (entre zero e um) indicando a confian?a de que esse elemento perten?a a um determinado objeto ou regi?o existente na imagem. O presente trabalho apresenta uma aplica??o do algoritmo de segmenta??o fuzzy de imagem, e a extens?o deste para segmentar v?deos coloridos. Nesse contexto, os v?deos s?o tratados como volumes 3D e o crescimento das regi?es ? realizado usando fun??es de afinidade que atribuem a cada pixel um valor entre zero e um para indicar o grau de pertin?ncia que esse pixel tem com os objetos segmentados. Para segmentar as seq??ncias foram utilizadas informa??es de movimento e de cor, sendo que essa ?ltima ? proveniente de um modelo de cor convencional, ou atrav?s de uma metodologia que utiliza a correla??o de Pearson para selecionar os melhores canais para realizar a segmenta??o. A informa??o de movimento foi extra?da atrav?s do c?lculo do fluxo ?ptico entre dois frames adjacentes. Por ?ltimo ? apresentada uma an?lise do comportamento do algoritmo na segmenta??o de seis v?deos e um exemplo de uma aplica??o que utiliza os mapas de segmenta??o para realizar renderiza??es que n?o sejam foto real?sticas

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