Thesis (Ph. D.)--University of Washington, 1987. / Vita. Bibliography: leaves [121]-125.

A common method for finding an object's pose is the generalized Hough transform, which accumulates evidence for possible coordinate transformations in a parameter space and takes large clusters of similar transformations as evidence of a correct solution. We analyze this approach by deriving theoretical bounds on the set of transformations consistent with each data-model feature pairing, and by deriving bounds on the likelihood of false peaks in the parameter space, as a function of noise, occlusion, and tessellation effects. We argue that blithely applying such methods to complex recognition tasks is a risky proposition, as the probability of false positives can be very high.

Thesis (M.S.)--Humboldt State University, 2007. / Includes bibliographical references (leaves 90-91). Also available via Humboldt Digital Scholar.

Neste trabalho é descrito um software denominado Scanc implementado no ambiente Windows, para a identificação de formas circulares em imagens digitais do tipo BMP. Dois métodos foram implementados para esse fim: a Transformada de Hough e Template Matching. Incluídos neste software encontram-se recursos para detecção de bordas e binarização da imagem, entre outros. O software tem aplicação nas mais diversas áreas, que requeiram a identificação de formas circulares. / The present work describes a software named Scanc, developed for circular pattern identification in digital bitmap images (BMP). Scanc was developed for Microsoft Windows environment and it takes advantage of two methods: Hough Transform and Template Matching. Image tools such as border detection and binarization are also available among other resources. The software finds several applications wherever circular forms identification is requered.

Neste trabalho é descrito um software denominado Scanc implementado no ambiente Windows, para a identificação de formas circulares em imagens digitais do tipo BMP. Dois métodos foram implementados para esse fim: a Transformada de Hough e Template Matching. Incluídos neste software encontram-se recursos para detecção de bordas e binarização da imagem, entre outros. O software tem aplicação nas mais diversas áreas, que requeiram a identificação de formas circulares. / The present work describes a software named Scanc, developed for circular pattern identification in digital bitmap images (BMP). Scanc was developed for Microsoft Windows environment and it takes advantage of two methods: Hough Transform and Template Matching. Image tools such as border detection and binarization are also available among other resources. The software finds several applications wherever circular forms identification is requered.

Neste trabalho é proposto a técnica da Transformada de Hough para a Inspeção Visual Automática de placas retangulares, visando a determinação de características tais como perímetro, ortogonalidade, centro de massa, área, independente de rotação e translação do objeto dentro da imagem. Os resultados obtidos por essa técnica são avaliados pela comparação com o método dos Momentos, o recurso mais utilizado para a determinação de área e centro de massa para imagens bi-dimensionais. A análise estatística dos dados mostra a robustez da técnica da Transformada Hough para imagens ruidosas. / In this work, is proposed the Hough transform method for the Automated Visual lnspection of rectangular boards. The aim is to extract features such as position, perimeter and area, despite of object translation and rotation. The results obtained by this method are evaluated by comparing them with the method of Moments, the most used method to determine the area and center of mass for bi-dimensional images. Statistical analysis show the robustness of Hough transform for noisy images visual inspection.

Neste trabalho é proposto a técnica da Transformada de Hough para a Inspeção Visual Automática de placas retangulares, visando a determinação de características tais como perímetro, ortogonalidade, centro de massa, área, independente de rotação e translação do objeto dentro da imagem. Os resultados obtidos por essa técnica são avaliados pela comparação com o método dos Momentos, o recurso mais utilizado para a determinação de área e centro de massa para imagens bi-dimensionais. A análise estatística dos dados mostra a robustez da técnica da Transformada Hough para imagens ruidosas. / In this work, is proposed the Hough transform method for the Automated Visual lnspection of rectangular boards. The aim is to extract features such as position, perimeter and area, despite of object translation and rotation. The results obtained by this method are evaluated by comparing them with the method of Moments, the most used method to determine the area and center of mass for bi-dimensional images. Statistical analysis show the robustness of Hough transform for noisy images visual inspection.

This thesis deals with automatic localization and tracking of surgical tools such as needles in Magnetic Resonance Imaging(MRI). The accurate and precise localization of needles is very important for medical interventions such as biopsy, brachytherapy, anaesthesia and many other needle based percutaneous interventions. Needle tracking has to be really precise, because the target may reside adjacent to organs which are sensitive to injury. More over during the needle insertion, Magnetic Resonance Imaging(MRI) scan plane must be aligned such that needle is in the field of view (FOV) for surgeon. Many approaches were proposed for needle tracking and automatic MRI scan plane control over last decade that use external markers, but they are not able to account for possible needle bending. Significant amount of work has already been done by using the image based approaches for needle tracking in Image Guided Therapy (IGT) but the existing approaches for surgical robots under MRI guidance are purely based on imaging information; they are missing the important fact that, a lot of important information (for example, depth of insertion, entry point and angle of insertion) is available from the kinematic model of the robot. The existing approaches are also not considering the fact that the needle insertion results in a time sequence of images. So the information about needle positions from the images seen so far can be used to make an approximate estimate about the needle position in the subsequent images. During the course of this thesis we have investigated an image based approach for needle tracking in real-time MR images that leverages additional information available from robot's kinematics model, supplementing the acquired images. The proposed approach uses Standard Hough Transform(SHT) for needle detection in 2D MR image and uses Kalman Filter for tracking the needle over the sequence of images. We have demonstrated experimental validation of the method on Real MRI data using gel phantom and artificially created test images. The results proved that the proposed method can track the needle tip position with root mean squared error of 1.5 mm for straight needle and 2.5mm for curved needle.

" In the field of Robotics, Monocular Simultaneous Localization and Mapping (Monocular SLAM) has gained immense popularity, as it replaces large and costly sensors such as laser range finders with a single cheap camera. Additionally, the well-developed area of Computer Vision provides robust image processing algorithms which aid in developing feature detection technique for the implementation of Monocular SLAM. Similarly, in the field of digital electronics and embedded systems, hardware acceleration using FPGAs, has become quite popular. Hardware acceleration is based upon the idea of offloading certain iterative algorithms from the processor and implementing them on a dedicated piece of hardware such as an ASIC or FPGA, to speed up performance in terms of timing and to possibly reduce the net power consumption of the system. Good strides have been taken in developing massively pipelined and resource efficient hardware implementations of several image processing algorithms on FPGAs, which achieve fairly decent speed-up of the processing time. In this thesis, we have developed a very simple algorithm for feature detection in an indoor environment by means of a single camera, based on Canny Edge Detection and Hough Transform algorithms using OpenCV library, and proposed its integration with existing feature initialization technique for a complete Monocular SLAM implementation. Following this, we have developed hardware accelerators for Canny Edge Detection & Hough Transform and we have compared the timing performance of implementation in hardware (using FPGAs) with an implementation in software (using C++ and OpenCV). "

Tracking multiple targets in a high cluttered environment where multiple receivers are used is a challenging task due to the high level of false alarms and uncertainty in the track hypothesis. The multi-static active sonar scenario is an example for such systems where multiple source-receiver combinations are deployed. Due to the nature of the underwater environment and sound propagation characteristics, tracking targets in the underwater environment becomes a complex operation. Conventional tracking approaches (such as the Kalman and particle filter) require a predetermined kinematic model of the target. Moreover, tracking an unknown and changing number of targets within a certain search area requires complex mathematical association filters to identify the number of targets and associate measurements to different target tracks. As the number of false detections increases, the computational complexity of conventional tracking system grows introducing further challenges for real-time target tracking situations. The methodology presented in this thesis provides a rapid and reliable tracking system capable of tracking multiple targets without depending on a kinematic model of the target movement. In this algorithm, Self Organizing Maps, Dynamic Programming and the Hough transform are combined to produce tracks of possible targets’ paths and estimate of targets’ locations. Evaluation of the performance of the tracking algorithm is performed using three types of simulations and a set of real data obtained from a sea trial. This research documents the results of experimental testing and analysis of the tracking system. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2009-08-07 13:21:06.869