451 research outputs found
Contribuciones sobre métodos óptimos y subóptimos de aproximaciones poligonales de curvas 2-D
Esta tesis versa sobre el an álisis de la forma de objetos 2D. En visión articial existen
numerosos aspectos de los que se pueden extraer información. Uno de los más usados es la
forma o el contorno de esos objetos. Esta característica visual de los objetos nos permite,
mediante el procesamiento adecuado, extraer información de los objetos, analizar escenas, etc.
No obstante el contorno o silueta de los objetos contiene información redundante. Este
exceso de datos que no aporta nuevo conocimiento debe ser eliminado, con el objeto de agilizar
el procesamiento posterior o de minimizar el tamaño de la representación de ese contorno, para
su almacenamiento o transmisión. Esta reducción de datos debe realizarse sin que se produzca
una pérdida de información importante para representación del contorno original. Se puede
obtener una versión reducida de un contorno eliminando puntos intermedios y uniendo los
puntos restantes mediante segmentos. Esta representación reducida de un contorno se conoce
como aproximación poligonal.
Estas aproximaciones poligonales de contornos representan, por tanto, una versión comprimida
de la información original. El principal uso de las mismas es la reducción del volumen
de información necesario para representar el contorno de un objeto. No obstante, en los últimos años estas aproximaciones han sido usadas para el reconocimiento de objetos. Para ello los algoritmos
de aproximaci ón poligonal se han usado directamente para la extracci ón de los vectores
de caracter ísticas empleados en la fase de aprendizaje.
Las contribuciones realizadas por tanto en esta tesis se han centrado en diversos aspectos de
las aproximaciones poligonales. En la primera contribución se han mejorado varios algoritmos
de aproximaciones poligonales, mediante el uso de una fase de preprocesado que acelera estos algoritmos permitiendo incluso mejorar la calidad de las soluciones en un menor tiempo. En la segunda contribución se ha propuesto un nuevo algoritmo de aproximaciones poligonales que obtiene soluciones optimas en un menor espacio de tiempo que el resto de métodos que aparecen en la literatura. En la tercera contribución se ha propuesto un algoritmo de aproximaciones que
es capaz de obtener la solución óptima en pocas iteraciones en la mayor parte de los casos. Por último, se ha propuesto una versi ón mejorada del algoritmo óptimo para obtener aproximaciones poligonales que soluciona otro problema de optimización alternativo.This thesis focus on the analysis of the shape of objects. In computer vision there are
several sources from which we can extract information. One of the most important source of
information is the shape or contour of objects. This visual characteristic can be used to extract
information, analyze the scene, etc.
However, the contour of the objects contains redundant information. This redundant data
does not add new information and therefore, must be deleted in order to minimize the processing
burden and reducing the amount of data to represent that shape. This reduction of data
should be done without losing important information to represent the original contour. A
reduced version of a contour can be obtained by deleting some points of the contour and linking
the remaining points by using line segments. This reduced version of a contour is known as
polygonal approximation in the literature.
Therefore, these polygonal approximation represent a compressed version of the original
information. The main use of polygonal approximations is to reduce the amount of information
needed to represent the contour of an object. However, in recent years polygonal approximations
have been used to recognize objects. For this purpose, the feature vectors have been extracted
from the polygonal approximations.
The contributions proposed in this thesis have focused on several aspects of polygonal approximations.
The rst contribution has improved several algorithms to obtain polygonal approximations,
by adding a new stage of preprocessing which boost the whole method. The
quality of the solutions obtained has also been improved and the computation time reduced.
The second contribution proposes a novel algorithm which obtains optimal polygonal approximations
in a shorter time than the optimal methods found in the literature. The third contribution
proposes a new method which may obtain the optimal solution after few iterations
in most cases. Finally, an improved version of the optimal polygonal approximation algorithm
has been proposed to solve an alternative optimization problem
On the Detection of Visual Features from Digital Curves using a Metaheuristic Approach
In computational shape analysis a crucial step consists in extracting meaningful features from digital curves. Dominant points are those points with curvature extreme on the curve that can suitably describe the curve both for visual perception and for recognition. Many approaches have been developed for detecting dominant points. In this paper we present a novel method that combines the dominant point detection and the ant colony optimization search. The method is inspired by the ant colony search (ACS) suggested by Yin in [1] but it results in a much more efficient and effective approximation algorithm. The excellent results have been compared both to works using an optimal search approach and to works based on exact approximation strateg
Thinning-free Polygonal Approximation of Thick Digital Curves Using Cellular Envelope
Since the inception of successful rasterization of curves and objects in the digital space, several algorithms have been proposed for approximating a given digital curve. All these algorithms, however, resort to thinning as preprocessing before approximating a digital curve with changing thickness. Described in this paper is a novel thinning-free algorithm for polygonal approximation of an arbitrarily thick digital curve, using the concept of "cellular envelope", which is newly introduced in this paper. The cellular envelope, defined as the smallest set of cells containing the given curve, and hence bounded by two tightest (inner and outer) isothetic polygons, is constructed using a combinatorial technique. This envelope, in turn, is analyzed to determine a polygonal approximation of the curve as a sequence of cells using certain attributes of digital straightness. Since a real-world curve=curve-shaped object with varying thickness, unexpected disconnectedness, noisy information, etc., is unsuitable for the existing algorithms on polygonal approximation, the curve is encapsulated by the cellular envelope to enable the polygonal approximation. Owing to the implicit Euclidean-free metrics and combinatorial properties prevailing in the cellular plane, implementation of the proposed algorithm involves primitive integer operations only, leading to fast execution of the algorithm. Experimental results that include output polygons for different values of the approximation parameter corresponding to several real-world digital curves, a couple of measures on the quality of approximation, comparative results related with two other well-referred algorithms, and CPU times, have been presented to demonstrate the elegance and efficacy of the proposed algorithm
Mobile robotic network deployment for intruder detection and tracking
This thesis investigates the problem of intruder detection and tracking using mobile robotic networks. In the first part of the thesis, we consider the problem of seeking an electromagnetic source using a team of robots that measure the local intensity of the emitted signal. We propose a planner for a team of robots based on Particle Swarm Optimization (PSO) which is a population based stochastic optimization technique. An equivalence is established between particles generated in the traditional PSO technique, and the mobile agents in the swarm. Since the positions of the robots are updated using the PSO algorithm, modifications are required to implement the PSO algorithm on real robots to incorporate collision avoidance strategies. The modifications necessary to implement PSO on mobile robots, and strategies to adapt to real environments are presented in this thesis. Our results are also validated on an experimental testbed.
In the second part, we present a game theoretic framework for visibility-based target tracking in multi-robot teams. A team of observers (pursuers) and a team of targets (evaders) are present in an environment with obstacles. The objective of the team of observers is to track the team of targets for the maximum possible time. While the objective of the team of targets is to escape (break line-of-sight) in the minimum time. We decompose the problem into two layers. At the upper level, each pursuer is allocated to an evader through a minimum cost allocation strategy based on the risk of each evader, thereby, decomposing the agents into multiple single pursuer-single evader pairs. Two decentralized allocation strategies are proposed and implemented in this thesis. At the lower level, each pursuer computes its strategy based on the results of the single pursuer-single evader target-tracking problem. We initially address this problem in an environment containing a semi-infinite obstacle with one corner. The pursuer\u27s optimal tracking strategy is obtained regardless of the evader\u27s strategy using techniques from optimal control theory and differential games. Next, we extend the result to an environment containing multiple polygonal obstacles. We construct a pursuit field to provide a guiding vector for the pursuer which is a weighted sum of several component vectors. The performance of different combinations of component vectors is investigated. Finally, we extend our work to address the case when the obstacles are not polygonal, and the observers have constraints in motion
Efficient dominant point detection based on discrete curve structure
International audienceIn this paper, we investigate the problem of dominant point detection on digital curves which consists in finding points with local maximum curvature. Thanks to previous studies of the decomposition of curves into sequence of discrete structures [5–7], namely maximal blurred segments of width [13], an initial algorithm has been proposed in [14] to detect dominant points. However, an heuristic strategy is used to identify the dominant points. We now propose a modified algorithm without heuristics but a simple measure of angle. In addition, an application of polygonal simplification is as well proposed to reduce the number of detected dominant points by associating a weight to each of them. The experimental results demonstrate the e and robustness of the proposed method
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