Segmentação de imagens por texturas através de um método de agrupamento de dados

• Ano de defesa: 2018
• Autor(a) principal: Carvalho, Taiane Viana de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Brasil; UFRN; PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA ELÉTRICA E DE COMPUTAÇÃO
• Palavras-chave em Português: Processamento de imagens; Segmentação de imagens; Texturas; Mistura de gaussianas; Clustering; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA
• Link de acesso: https://repositorio.ufrn.br/jspui/handle/123456789/25963

Segmentation is one of the most complex process in image processing and the focus on research in this area has been increasing. Segmentation, consists of dividing an image into distinct regions from pixel properties, as gray level and texture. This paper presents a new method of images segmentation based on extraction of textures features in images. The method consists of forming a dataset based on the pixel values in the image and then group the data into classes that represent the textures that make up the image. Pixel grouping occurs through the clustering application technique. This technique group the points in the data set in auxiliary centers using vector quantization. The distance between the auxiliary centers is estimated and all centers that have a distance less than a threshold are linked together. Conventional distances used in clustering basically grow with the square of the distance in means. An alternative used in this paper is a new method based on gaussian mixture concept, witch estimates the separation between a data set modeled by Gaussians with model of one single Gaussian. The purpose of this approach is to perform the separation of regions with different textures in an image using an efficient algorithm.