Made available in DSpace on 2014-12-17T14:54:48Z (GMT). No. of bitstreams: 1 DiogoPFP_Tese.pdf: 4402228 bytes, checksum: 17eacb6b5f1731f405518c976d32f701 (MD5) Previous issue date: 2006-05-19 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / The objective of this thesis is proposes a method for a mobile robot to build a hybrid map of an indoor, semi-structured environment. The topological part of this map deals with spatial relationships among rooms and corridors. It is a topology-based map, where the edges of the graph are rooms or corridors, and each link between two distinct edges represents a door. The metric part of the map consists in a set of parameters. These parameters describe a geometric figure which adapts to the free space of the local environment. This figure is calculated by a set of points which sample the boundaries of the local free space. These points are obtained with range sensors and with knowledge about the robot s pose. A method based on generalized Hough transform is applied to this set of points in order to obtain the geomtric figure. The building of the hybrid map is an incremental procedure. It is accomplished while the robot explores the environment. Each room is associated with a metric local map and, consequently, with an edge of the topo-logical map. During the mapping procedure, the robot may use recent metric information of the environment to improve its global or relative pose / Esta tese tem o objetivo de propor uma metodologia para constru??o de um mapa h?brido de um ambiente interno. A parte topol?gica da representa??o trata das rela??es de conectividade existentes entre as salas e corredores, sendo assim um grafo que representa a topologia do ambiente global. A parte m?trica consiste em armazenar um conjunto de par?metros que descreve uma figura geom?trica plana que melhor se ajusta ao espa?o livre local. Esta figura ? calculada atrav?s do conhecimento de pontos, ou amostras, dos limites do espa?o livre. Estes pontos s?o obtidos com sensores de dist?ncia e a informa??o ? complementada com a estimativa da pose do rob?. Uma vez que estes pontos est?o determinados, o rob? ent?o aplica uma ferramenta baseada na transformada generalizada de Hough para obter a figura em quest?o. O processo de constru??o do mapa ? incremental e totalmente realizado enquanto o rob? explora o ambiente. Cada sala ? representada por este mapa local e cada n? do grafo que representa a topologia do ambiente est? associado a este mapa. Durante o mapeamento o rob? pode utilizar as informa??es rec?m-adquiridas do ambiente para obter uma melhor estimativa de sua pose global ou relativa a uma sala ou corredor

Automated spine or vertebra detection and segmentation from CT images is a difficult task for several reasons. One of the reasons is unclear vertebra boundaries and indistinct boundaries between vertebra. Next reason is artifacts in images and high degree of anatomical complexity. This paper describes the design and implementation of vertebra detection and classification in CT images of cancer patients, which adds to the complexity because some of vertebrae are deformed. For the vertebra segmentation, the Otsu’s method is used. Vertebra detection is based on search of borders between individual vertebra in sagittal planes. Decision trees or the generalized Hough transform is applied for the identification whereas the vertebra searching is based on similarity between each vertebra model shape and planes of CT scans.

This paper deals with object detection and tracking using iterest points. Existing approaches are described here. Inovated method based on Generalized Hough transform and iterative Hough-space searching is  proposed in this paper. Generality of proposed detector is shown in various types of objects. Object tracking is designed as frame by frame detection.