Dissertations / Theses on the topic 'Hough Transform'
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Galambos, Charles. "The Progressive Probabilistic Hough Transform." Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/842944/.
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This thesis presents the Progressive Probabilistic Hough Transform (PPHT). Unlike the Probabilistic HT [46] where the Standard HT is performed on a pre-selected fraction of input points, the PPHT minimises the amount of computation needed to detect lines by exploiting the difference in the fraction of votes needed to reliably detect lines with different numbers of supporting points. The fraction of points used for voting need not be specified ad hoc or using a priori knowledge, as in the probabilistic HT; it is a function of the inherent complexity of data. The algorithm is ideally suited for real-time applications with a fixed amount of available processing time, since voting and line detection is interleaved. The most salient features are likely to be detected first. While retaining its robustness, experiments show PPHT has, in many circumstances, advantages over the Standard HT.
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Stephens, Richard Sturge. "The Hough Transform : a probabilistic approach." Thesis, University of Cambridge, 1990. https://www.repository.cam.ac.uk/handle/1810/251579.
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Nordstrand, Lindgren Emelie, and Johan Sandmark. "Hough transform vid identifiering av hudförändringar." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166607.
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Att med bildigenkänning identifiera hudförändringar (ofta kallade födelsemärken) kan leda till snabbare upptäckt och diagnos jämfört med dagens manuella metoder. Hough transform är en känd algoritm inom bildigenkänning men har ännu inte applicerats direkt på hudförändringar. Uppsatsen undersöker om Hough transform kan användas med tillräckligt hög pålitlighet för att identifiera hudförändringar hos patienter. Den valda metoden är att med bildbehandling förbereda testbilder för att minimera brus och störningar, för att sedan med hjälp av MATLAB tillämpa algoritmen. Resultatet från uppsatsen med den valda metoden är att cirka 30% av hudförändringarna kunde identifieras. Slutsatsen är därmed att algoritmen, i denna implementation, inte ger ett tillräckligt korrekt resultat för att vara ett verktyg inom sjukvården. En annan slutsats är att mer undersökning behövs för att eliminera brus och störningar i testbilderna från bland annat kroppsbehåring.Using image recognition to identify skin moles could lead to faster detection and diagnosis of skin cancer compared to the manual workflow used in health care today. Hough transform is a well known algorithm for image recognition but have not yet been applied directly to skin moles. This report examines if Hough transform can be used with sufficient reliability to identify skin moles on dermatology patients. The method is to prepare the test images to minimize noise and distrubence and then apply a MATLAB implementation of the algorithm. The results shows that about 30% of the skin moles could be identified. The conclusion from the report is that the algorithm, with the choosen method, does not provide a sufficiently accurate result to be used as a reliable tool in health care. Another conclusion is that more research is needed to eliminate noice and disturbance in the test images derived from e.g. bodyhair.
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Rodriguez, Artolazabal Jose Antonio. "Exploiting invariance in Hough transform algorithms." Thesis, University of Surrey, 2007. http://epubs.surrey.ac.uk/972/.
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Eriksson, Edvin. "Coordinate conversion for the Hough transform." Thesis, Uppsala universitet, Högenergifysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-448782.
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This thesis attempts to develop a conversion algorithm between local coordinates in constituent detector modules and global coordinates encompassing the whole detector structure in a generic detector. The thesis is a part of preparatory work for studying the Hough Transform as a means of track reconstruction in the level-1 hardware trigger in the upgraded trigger and data acquisition (TDAQ) system in the phase 2 upgrade of the ATLAS detector at CERN. The upgrades being made are to withstand much more extreme conditions that come with the high-Luminosity Large Hadron Collider (HL-LHC). Two algorithms have been made and then implemented in Python scripts to test their feasibility and to compare them against each-other. The Rotation algorithm uses several rotations to correctly place the local coordinates in the global system. The second, the Shear algorithm, simplifies the process into two shears and one rotation, using the small angle approximation. Both algorithms need to be extended to work with more parts of the detector to be considered complete. Despite having lower maximum precision the second algorithm is considered the most promising attempt, since it is much less sensitive to the truncation error that results from working in an integer environment, which is a requirement for use in FPGAs.I denna uppsats görs ett försök att skapa en omvandlingsalgoritm mellan lokala koordinater i konstituerande detektormoduler och globala koordinater i hela detektorstrukturen för en generisk detektor. Uppsatsen är en del i förberedande arbete för att undersöka hur Houghtransformen kan användas för spårrekonstruktion i den hårdvarubaserade level-1 triggern i det uppgraderade trigger- och datainsamlingssystemet (TDAQ) i fas två-uppgraderingen av ATLAS detektorn vid CERN. Uppgraderingarna som görs är för att kunna utstå de mycket mer extrema förhållanden som medförs av högluminositetsuppgraderingen av Large Hadron Collider (HL-LHC). Två algoritmer har skapats och implementerats i Pythonskript för att testa genomförbarhet och för att jämföra med varandra. Rotationsalgoritmen använder ett antal rotationer för att korrekt placera ut de lokala koordinaterna i det globala systemet. Den andra, Skjuvalgortimen, förenklar processen till två skjuvningar och en rotation med hjälp av liten vinkel-approximationen. Båda algoritmerna behöver utökas för att fungera för fler delar av detektorn för att anses kompletta. Trots lägre maximal precision bedöms den andra algoritmen vara det mest lovande försöket, eftersom den är mycket mindre känslig för trunkeringsfelet som kommer av att arbeta i en heltalsmiljö, som är ett krav för FPGA-implementationen.
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Segalini, Lorenzo. "Implementazione in Java dell'algoritmo "Circle Hough Transform"." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
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La tesi si concentra sullo studio della tecnica denominata "Circle Hough Transform" ed ha come obiettivo principale quello di dimostrare attraverso l’implementazione in linguaggio Java l’utilità e la validità dell’algoritmo trattato, mostrandone l’efficacia e il funzionamento generale di ogni sua sezione.
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Kim, Jongwoo. "A robust hough transform based on validity /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9842545.
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Zou, Rucong, and Hong Sun. "Building Extraction in 2D Imagery Using Hough Transform." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-17597.
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The purpose of this paper is to find out whether Hough transform if it is helpful to building extraction or not. This paper is written with the intention to come up with a building extraction algorithm that captures building areas in images as accurately as possible and eliminates background interference information, allowing the extracted contour area to be slightly larger than the building area itself. The core algorithm in this paper is based on the linear feature of the building edge and it removes interference information from the background. Through the test with ZuBuD database in Matlab, we can detect images successfully. So according to this study, the Hough transform works for extracting building in 2D images.
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Tyler, Jonathan. "Muon identification with Veritas using the Hough Transform." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=107695.
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Imaging atmospheric Cherenkov telescope (IACT) arrays such as VERITAS are used to perform very high-energy gamma-ray astronomy. This is accomplished by detecting and analyzing the Cherenkov light produced by gamma-ray initiated atmospheric air showers. IACTs also detect the Cherenkov light produced by individual muons. The Cherenkov light produced by muons is well understood, and can be used as a calibrated light source for the telescopes. Muons create characteristic annular patterns in the cameras of IACTs, which may be identified using parametrization algorithms. One such algorithm, the Hough transform, has been used to identify muons in VERITAS data. The details of the Hough transform and its implementation on VERITAS data will be described, as well as the use of parameters derived from the Hough transform for muon identification. In addition, the selection of muon rings appropriate for calibration purposes will be described. Finally, the Hough transform-based muon selection technique will be compared to the standard VERITAS muon selection technique.Les systèmes de télescopes par imagerie Cherenkov tel que VERITAS sont utilisés pour l'astronomie à rayons gammas de très hautes énergies. Ceci est accompli par la détection et l'analyse de la lumière Cherenkov produite par les gerbes de particules causées par l'interaction des rayons gammas avec l'atmosphère. Ces télescopes détectent aussi la lumière Cherenkov produite par les muons. La lumière Cherenkov produite par les muons est bien comprise, et peut être utilisée comme source de calibration pour les télescopes. Les muons forment un anneau dans leur caméra, et peuvent être identifiés en utilisant des algorithmes de paramétrisation. La transformée de Hough est un de ces algorithmes, et a été utilisé afin d'identifier les muons dans les données de VERITAS. Les détails de la transformée de Hough et son application avec VERITAS seront présentés, ainsi que l'utilisation des paramêtres en découlant pour l'identification de muons. De plus, la sélection d'anneaux de muons appropriés pour des besoins de calibration sera décrite. Finalement, la technique de sélection de muons basé sur les transformées de Hough sera comparée à la technique de sélection de muons standard de VERITAS.
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Slininger, Timothy. "Robust hough transform for noisy and cluttered images." Thesis, Southern Connecticut State University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1525183.
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Finding arbitrary shapes within image data is a problem with applications ranging from Internet searching to intelligence data processing to analyzing zoning maps. This task is further complicated when the images are not pristine but contain noise. The effect of noise on the Generalized Hough Transform is analyzed using idealized images with variable amounts of noise. The ability of the algorithm to detect the desired shapes is reported as a function of the amount of noise. Time performance degradation is considered as are methods for increasing the ability of the algorithm to detect objects under various scale and rotation variations. As part of this thesis, a modular software platform was developed to support custom image processing algorithms including filtering, gradient transformations, edge detection, and implementations of the Hough Transform.
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Eghtesadi, Shirin. "Parallel implementations of the Hough transform on transputers." Thesis, King's College London (University of London), 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321689.
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Costa, Luciano da Fontoura. "Effective detection of line segments with Hough transform." Thesis, King's College London (University of London), 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320507.
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Muammar, Hani Kamal. "Extending the Hough transform through alternative shape parameterisations." Thesis, University of Southampton, 1990. https://eprints.soton.ac.uk/253035/.
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Zahran, Mohamed. "Shape matching using a modified Generalized Hough Transform /." The Ohio State University, 1997. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487947908401423.
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Li, Duwang. "Invariant pattern recognition algorithm using the Hough Transform." PDXScholar, 1989. https://pdxscholar.library.pdx.edu/open_access_etds/3899.
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A new algorithm is proposed which uses the Hough Transform to recognize two dimensional objects independent of their orientations, sizes and locations. The binary image of an object is represented by a set of straight lines. Features of the straight lines, namely the lengths and the angles of their normals, their lengths and the end point positions are extracted using the Hough Transform. A data structure for the extracted lines is constructed so that it is efficient to match the features of the lines of one object to those of another object, and determine if one object is a rotated and/or scaled version of the other. Finally a generalized Hough Transform is used to match the end points of the two sets of lines. The simulation experiments show good results for objects with significant linear features .
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Elazar, Moshe. "Search radar track-before-detect using the Hough transform." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1995. http://handle.dtic.mil/100.2/ADA295245.
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Patterson, Colleen. "Feature extraction from digital imagery using the Hough transform." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0016/MQ48455.pdf.
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Chaudhary, Priyanka. "SPHEROID DETECTION IN 2D IMAGES USING CIRCULAR HOUGH TRANSFORM." UKnowledge, 2010. http://uknowledge.uky.edu/gradschool_theses/9.
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Three-dimensional endothelial cell sprouting assay (3D-ECSA) exhibits differentiation of endothelial cells into sprouting structures inside a 3D matrix of collagen I. It is a screening tool to study endothelial cell behavior and identification of angiogenesis inhibitors. The shape and size of an EC spheroid (aggregation of ~ 750 cells) is important with respect to its growth performance in presence of angiogenic stimulators. Apparently, tubules formed on malformed spheroids lack homogeneity in terms of density and length. This requires segregation of well formed spheroids from malformed ones to obtain better performance metrics. We aim to develop and validate an automated imaging software analysis tool, as a part of a High-content High throughput screening (HC-HTS) assay platform, to exploit 3D-ECSA as a differential HTS assay. We present a solution using Circular Hough Transform to detect a nearly perfect spheroid as per its circular shape in a 2D image. This successfully enables us to differentiate and separate good spheroids from the malformed ones using automated test bench.
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Princen, John. "Hough transform methods for curve detection and parameter estimation." Thesis, University of Surrey, 1990. http://epubs.surrey.ac.uk/817/.
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Patterson, Colleen (Stella Colleen) Carleton University Dissertation Engineering Systems and Computer. "Feature extraction from digital imagery using the Hough Transform." Ottawa, 1999.
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Gendy, Shokri. "Automatic Car Registration Plate Recognition Using the Hough Transform." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 1998. https://ro.ecu.edu.au/theses/1429.
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The development of automatic car registration plate recognition systems will provide greater efficiency for vehicle monitoring in automatic access control, and will avoid the need to equip vehicles with special RF tags for identification since all vehicles possess a unique registration plate. Thus this study is an attempt to introduce an automatic car registration plate recognition system based on identifying the plate characters by using the Hough transform. However, the proposed recognition system can be used in conjunction with a tag system for higher security access control. The automatic registration plate recognition could also have considerable potential in a wide range of applications especially in the identification of vehicle-based offences and with law enforcement. Recent advances in computer vision technology and the falling price of the related devices has contributed in making it practical to build an automatic, registration plate recognition systems. There have been a number of Optical Character Recognition (OCR) techniques, which have been used in the recognition of car registration plate characters. These systems include the character details matching process (Lotufo, et al. 1990), BAM (Bi-directional Associative Memories) neural network (Fahmy 1994) neural network (Tindall, 1995) and cross correlation pattern matching character matching techniques (Cornelli, et al. 1995). All of these systems recognized the characters by matching the full image of every character with a character's template database which requires considerable processing time and large memory for the database. The purpose of this study is to explore the potential for using Hough transform (Hough 1962) in vehicle registration plate recognition. The OCR technique used in this project is unlike the other systems where the character recognition was based on matching the character's full image; However the OCR technique in this system used Hough transform to identify the characters, where the recognition of a character is based on matching its identification array to the database. To validate the research, a car registration plate recognition system was developed to locate the registration plate from the full image of a vehicle and then extrar.t the plate characters by using image processing techniques. A Hough transform algorithm was applied to every character within the registration plate image to produce an identification array for these characters, and the plate characters were recognized by matching their identification array to the database. The system has been applied to a number of video recorded car images to recognize their registration plates. The rate of correctly recognized characters was 82.7% of the extracted characters, but improvement can be granted by using a faster digital camera and taking some precautions in the registration plate frames. However, the research indicated that the optical character recognition technique used in the study is an efficient and simple algorithm to identify characters, without requiring a relatively large processing memory.
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Alexiadis, Evangelos. "Implementation of a real time Hough transform using FPGA technology." Thesis, University of Kent, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.544083.
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Cao, X. "Hough transform techniques for recognition and inspection of industrial objects." Thesis, Swansea University, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.636204.
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It is well known that the lack of robustness, reliability and fast processing of computer vision algorithms is a major barrier affecting the wide use of machine vision systems in industrial automation. To this end, the thesis evaluates many Hough transform related techniques and proposes several efficient algorithms suitable for object identification and inspection in industrial scenes. To detect multiple circular objects in a noisy image accurately, two schemes are proposed. The first scheme combines a labelling technique with the adaptive Hough transform for circle detection to resolve the ambiguities in locating peaks in the parameter space. In the second scheme an alternative transform equation is used to generate the parameter space and, for locating a cluster of three points on a circle, a set of rules is developed. Using this approach, the parameter space generated by the transform is more compact that that generated using conventional methods, and hence fast processing can be achieved. To validate the proposed approaches, several experiments are conducted to detect multiple circular objects in both synthetic and real images. The experiments show that the labelling adaptive Hough transform can produce good results when used to detect circular objects in good-contrast images, and the algorithm using an alternative transform equation performs very well, even in images contaminated by noise, with objects touching and/or overlapping each other. An improved technique is also presented for the detection of arbitrarily-shaped objects by incorporating a model-size-reduction scheme into an optimized, generalized Hough transform. For further speed-up of the algorithms developed in the thesis, their parallel implementation on transputer-based networks is investigated.
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Latt, Khine. "Sonar-based localization of mobile robots using the Hough transform." Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/8981.
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Approved for public release; distribution is unlimitedFor an autonomous mobile robot to navigate in an unknown environment, it is essential to know the location of the robot on a real-time basis. Finding position and orientation of a mobile robot in a world coordinate system is a problem in localization. Dead-reckoning is commonly used for localization, but position and orientation errors from dead-reckoning tend to accumulate over time. The objective of this thesis is to develop a feature-based localization method that allows a mobile robot to re-calibrate its position and orientation by automatically selecting wall-like features in the environment. In this thesis, the selection of features is accomplished by applying the Hough transform to sonar data. The Hough transform makes it possible to select the optimal feature (the longest wall, in this case) without finding all possible line segments from the sonar data. A least-square line fitting method is then employed to construct a model of the line segment that represents the feature selected by the Hough transform. The algorithm developed was tested using synthetic and real sonar data. Experimental results demonstrated the effectiveness of the proposed localization methods
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Ramesh, Naren. "A Hardware Implementation of Hough Transform Based on Parabolic Duality." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1396530960.
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Gifford, Eric Allan 1965. "Hough transform extraction of cartographic fiducial marks from aerial photography." Thesis, The University of Arizona, 1991. http://hdl.handle.net/10150/277903.
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Cartographic compilation requires precision mensuration. The calibration of mensuration processes is based on specific fiducials. External fiducials, around the exterior frame of the image, must be precisely measured to establish the overall physical geometry. Internal fiducials are provided within the image by placement of cloth panels on the ground at locations whose position is precisely known. Both types of fiducials must be known within the pixel space of a digitized image in order for the feature extraction process to be accurate with respect to delineated features. Precise mensuration of these fiducials requires that a cartographer view the image on a display and use pointing devices, such as a mouse, to pick the exact point. For accurate fiducial location, the required manual operations can be an added time-consuming task in the feature extraction process. Interactive tools which eliminate the precise pointing action for the operator are described in this thesis. The operator is required only to "box-in" the fiducial, using a simple drawing tool, select the fiducial function, and the software of the tool returns the precise location of the fiducial.
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Flint, Anthony David. "The development of predictive maintenance systems based on the Hough transform." Thesis, University of Huddersfield, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.307836.
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Inrawong, Prajuab. "Application of PCA and Hough Transform to classify features in optical images." Thesis, University of Nottingham, 2012. http://eprints.nottingham.ac.uk/12520/.
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Viewing fine features of object with optical instruments have become increasingly difficult as the dimensions of many features of interest have become smaller than the traditional optical resolution limit. Examples of these features can be found in semiconductor components and biological tissues. This has caused a move to non-optical methods such as scanning electron and atomic force microscopy techniques, or optical methods combined with signal processing techniques to provide clearer images of samples. This thesis presents a method to increase the resolution of an optical system. This is achieved by using principal component analysis (PCA). Once the PCA measured the object image parameters, the new clearer image can be reconstructed based on these parameters. This process works extremely well. Various aspects of samples measured by the PCA have been investigated, such as the shift of sample, the sample with different sizes, the orientation of sample and the impact of noise. These studies show that the technique is extremely robust, and has huge potential for general usage. The thesis also contains the detail of the Hough Transform technique which was used to provide the initial parameters to the PCA. From the analysis of the technique, it is concluded that the accurate measurement of the technique can be achieved by providing adequate templates of the object image for the system.
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Gharachlou, Albert Purbenyamin. "Automatic recognition of three dimensional planar objects by Hough transform type operations." Thesis, City University London, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.281844.
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Salmanpour, Rahmdel Payam. "A parallel windowing approach to the Hough transform for line segment detection." Thesis, Middlesex University, 2013. http://eprints.mdx.ac.uk/12629/.
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In the wide range of image processing and computer vision problems, line segment detection has always been among the most critical headlines. Detection of primitives such as linear features and straight edges has diverse applications in many image understanding and perception tasks. The research presented in this dissertation is a contribution to the detection of straight-line segments by identifying the location of their endpoints within a two-dimensional digital image. The proposed method is based on a unique domain-crossing approach that takes both image and parameter domain information into consideration. First, the straight-line parameters, i.e. location and orientation, have been identified using an advanced Fourier-based Hough transform. As well as producing more accurate and robust detection of straight-lines, this method has been proven to have better efficiency in terms of computational time in comparison with the standard Hough transform. Second, for each straight-line a window-of-interest is designed in the image domain and the disturbance caused by the other neighbouring segments is removed to capture the Hough transform buttery of the target segment. In this way, for each straight-line a separate buttery is constructed. The boundary of the buttery wings are further smoothed and approximated by a curve fitting approach. Finally, segments endpoints were identified using buttery boundary points and the Hough transform peak. Experimental results on synthetic and real images have shown that the proposed method enjoys a superior performance compared with the existing similar representative works.
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Seshadri, M. D. "Image reconstruction, recognition, using image processing, pattern recognition and the Hough transform /." The Ohio State University, 1992. http://rave.ohiolink.edu/etdc/view?acc_num=osu1258488573.
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Silva, Ernany Paranaguá da. "Aplicação da Transformada de Hough em inspeção visual automática." Universidade de São Paulo, 1996. http://www.teses.usp.br/teses/disponiveis/18/18133/tde-23012018-141411/.
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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.
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Thakkar, Chintan. "Ventricle slice detection in MRI images using Hough Transform and Object Matching techniques." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001815.
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Janga, Satyanarayana Reddy. "A Fast and Robust Image-Based Method for tracking Robot-assisted Needle Placement in Real-time MR Images." Digital WPI, 2014. https://digitalcommons.wpi.edu/etd-theses/106.
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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.
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Nash, Jason Mark. "Evidence gathering for dynamic feature extraction." Thesis, University of Southampton, 1999. https://eprints.soton.ac.uk/253031/.
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Tu, Chunling. "Améliorations de la Transformée de Hough en traitement d'images." Thesis, Paris Est, 2014. http://www.theses.fr/2014PEST1103/document.
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Les travaux effectués dans le cadre de la présente thèse concernent l'analyse et les améliorations apportées à la transformée de Hough Standard (SHT), utilisée en traitement d'image comme simple outil de détection de segments de lignes droites. La transformée de Hough a reçu, depuis sa proposition en 1962, une attention particulière de la part de la communauté. La HT est considérée comme une méthode robuste, dont le principe repose sur la transformation le problème initial de détection de segments de lignes droites en un problème de section de sommets dans l'espace des paramètres, appelé aussi espace HT ou espace de Hough. Les points candidats dans l'espace image sont mis en correspondance points dans l'espace de Hough, en utilisant Le principe avancé par la transformée de Hough est qu'il existe un nombre infini de lignes qui passent par un point, dont la seule différence est l'orientation (l'angle). La transformée de Hough permet de déterminer lesquelles de ces lignes passent au plus près du domaine d'intérêt. Les cellules dans l'espace de Hough échantillonné obtiennent des votes des points candidats. Les maxima locaux, correspondant aux sommets sont construit lorsque les cellules considérées obtiennent plus de votes que les cellules voisines. Les sommets détectés alors dans l'espace des paramètres sont transformée dans l'espace image pour validation. Malheureusement, les opérations les opérations de transformation directe, de l'espace image vers l'espace des paramètres, et inverse engendrent des opérations d'approximation, ce qui est la source de plusieurs problèmes de la transformée de Hough, qui affectent les aspects de robustesse, précision et résolution. On se propose de résoudre ces problèmes dans le cadre des travaux engagés dans le cadre de la thèse. Les contributions, détaillées ci-dessous, ont pu être proposées. A) Pour adresser le problème de limitation en termes de résolution de la SHT, les points concernent la sélection d'une bonne résolution, l'extension de la résolution de la SHT et l'utilisation des techniques de super-résolution pour la HT ont été couverts et de nouvelles propositions ont été faites et qui sont d'une utilité certaine pour les applications de traitement d'image.- la relation entre la performance de la HT et la résolution est proposée, ce qui permet de garantir le bon choix.- Une technique de super-résolution ets proposée en s'appuyant sur le principe de la HT- Une auto-similarité dans les échantillons HT a été découverte et a été utilisée pour obtenir une résolution supérieure de la HT avec un grande fidélité. B) Pour adresser le problème de la précision de la SHT, les erreurs de la HT ont été analysées, lorsque l'on fait subir des transformations géométriques à l'image source. Les erreurs ainsi détectées ont été utilisées pour compenser le manque de précision de la SHT, aboutissant ainsi à une HT plus précise. Afin de permettre l'évaluation de performance des approches proposées dan sel cadre de la thèse, une transformée de Hough idéale est proposée comme référenceThe thesis addresses the improvements of the Standard Hough Transform (SHT) for image processing applications. As a common tool for straight line segment detection, the Hough Transform (HT) has received extensive attention since its proposal in 1962. HT is robust since it converts the straight line detection problem to a peak seeking problem in the parameter space (also called HT space or Hough space). Feature points in the image space are mapped to the parameter space, according to the normal formulation of the possible straight lines crossing them. The cells in the digitalised parameter space obtain votes from the feature points. The local maxima, corresponding to peaks are built when corresponding cells obtain more votes than the ones around them. The peaks detected in the parameter space are then mapped back to the image space for validation. Unfortunately, when mapping feature points in the image space to the parameter space in conjunction with the voting process, rounding operations are employed, which leads to several problems of HT. The robustness, accuracy and resolution are all affected. This thesis aims to solve these problems, and the following contributions were made towards this goal : A) Because of the resolution limitation of SHT, the topics of how to select a “good” resolution, how to extend the resolutions of SHT and how to employ the super-resolution technique in HT are covered. In the research of these topics, several outputs are obtained, which are helpful to image processing applications. These include:- The map of HT performance versus resolutions is drawn, according to which “good” choices of resolutions can be found.- HT resolutions are extended by geometrical analysis of the HT butterflies.- Super resolution HT is proposed with consideration to the features of HT.- Self-similarity of the HT butterflies is discovered and employed to obtain high resolution HT with high reliability. B) For the accuracy defect of SHT, the error system of HT is studied when the image is shifted in the image space. The detection errors are employed to compensate for the defect, and an accurate HT is proposed. In order to evaluate existing HT varieties, an ideal HT is proposed as a standard
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O'Regan, Katherine. "Investigation into the use of the Microsoft Kinect and the Hough transform for mobile robotics." Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/13202.
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Includes bibliographical references.The Microsoft Kinect sensor is a low cost RGB-D sensor. In this dissertation, its calibration is fully investigated and then these parameters are compared to the parameters given by Microsoft and OpenNI. The parameters found were found to be different to those given by Microsoft and OpenNI therefore, every Kinect should be fully calibrated. The transformation from the raw data to a point cloud is also investigated. Then, the Hough transform is presented in its 2-dimensional form. The Hough transform is a line extraction algorithm which uses a voting system. It is then compared to the Split-and-Merge algorithm using laser range _nder data. The Hough transform is found to compare well to the Split-and-Merge in 2 dimensions. Finally, the Hough transform is extended into 3-dimensions for use with the Kinect sensor. It was found that pre-processing of the Kinect data was necessary to reduce the number of points input into the Hough transform. Three edge detectors are used - the LoG, Canny and Sobel edge detectors. These were compared, and the Sobel detector was found to be the best. The _nal process was then used in multiple ways - _rst to determine its speed. Its accuracy was then investigated. It was found that the planes extracted were very inaccurate, and therefore not suitable for obstacle avoidance in mobile robotics. The suitability of the process for SLAM was also investigated. It was found to be unsuitable, as planar environments did not have distinct features which could be tracked, whilst the complex environment was not planar, and therefore the Hough transform would not work.
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ROMANENGO, CHIARA. "Recognition and representation of curve and surface primitives in digital models via the Hough transform." Doctoral thesis, Università degli studi di Genova, 2023. https://hdl.handle.net/11567/1103813.
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Curve and surface primitives have an important role in conveying an object shape and their recognition finds significant applications in manufacturing, art, design and medical applications. When 3D models are acquired by scanning real objects, the resulting geometry does not explicitly encode these curves and surfaces, especially in the presence of noise or missing data. Then, the knowledge of the parts that compose a 3D model allows the reconstruction of the model itself. The problem of recognising curves and surfaces and providing a mathematical representation of them can be addressed using the Hough transform technique (HT), which in literature is mainly used to recognise curves in the plane and planes in space. Only in the last few years, it has been explored for the fitting of space curves and extended to different families of surfaces. Such a technique is robust to noise, does not suffer from missing parts and benefits from the flexibility of the template curve or surface.
For these reasons, our approach is inspired by a generalisation of the Hough transform defined for algebraic curves.
In this thesis, we present the methods we implemented and the results we obtained about the recognition, extraction, and representation of feature parts that compose a 3D model (both meshes and point clouds). Specifically, we first study the recognition of plane curves, simple and compound, expressed both in implicit and parametric form, with a focus on the application of cultural heritage and geometric motifs. Then, we analyse the extension of the method to space curves, concentrating on the improvement of the model through the insertion of the recognised curves directly on its surface.
To overcome the limitation of knowing in advance the family of curves to be used with the HT,
we introduce a piece-wise curve approximation using specific parametric, low-degree polynomial curves.
Finally, we analyse how to recognise simple and complex geometric surface primitives on both pre-segmented and entire point clouds, and we show a comparison with state-of-the-art approaches on two benchmarks specifically created to evaluate existing and our methods.
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Glennon, Jonathan Scott. "Feature-based localization in sonar-equipped autonomous mobile robots through hough transform and unsupervised learning network." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA350382.
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Lin, Hong Yi, and 林泓毅. "Hough transform on reconfigurable meshes." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/37254054416629524200.
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HUANG, HUAN-CHAO, and 黃煥超. "Inexact matching by hough transform." Thesis, 1987. http://ndltd.ncl.edu.tw/handle/65843867451588489048.
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Wu, Chujen, and 吳巨仁. "Hough Transform In Geometry Detection." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/57534300515392133704.
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碩士義守大學
資訊工程學系
100
For image detection, shape recognition and analysis are important. In geometric images, straight lines and circles are detected most commonly, and edge information is important in shape recognition. There are many edge detection methods. Due to noise interference, information may produce broken or discontinuous features after the edge detection operations. These missing parts may be important information needed for studies. The missing parts can be compensated by Hough Transform. In image processing, Hough Transform is one of the methods to recognize geometric shapes. It’s an algorithm which would not be affected by image rotation and zooming, easy to transform images fast, and can link breakage or non-contiguous line segments together. Hough Transform finds the parameters from the split points in the image, and maps the split points from Euclidean space to parameter space by one-to-many. We find the image parameters with characteristics of the collinear by accumulating the number of all parameter positions using accumulator. The edge information would affect the accuracy at the final selection if the texture of the edge information is too complex. This work focuses on the strengthening and improvement of the straight lines. We increase the accuracy of the straight lines by regional sampling the results which were produced using Hough Transform in straight line detection.
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Murmu, Rabindra Kumar, and Meena Jhaniya. "Image Segmentation Using Hough Transform." Thesis, 2009. http://ethesis.nitrkl.ac.in/356/1/IMAGE_SEGMENTATION_USING_HOUGH_TRASFORM.PDF.
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Image segmentation, a way of extracting and representing information from an image is to group pixels together into regions of similarity. We would group pixels together according to the rate of change of their intensity over a region or the rate of change of depth in the image, corresponding to pixels lying on the same surface such as a plane, cylinder, sphere etc.
Hough has proposed an interesting and computationally efficient procedure for detecting lines in pictures. In this paper we point out that the use of angle- radius rather than s lope-intercept parameters simplifies the computation further. We also show how the method can be used for circle detection.
The objective of this application is the recognition of different shapes in an image. This task can be subdivided into following procedures. First, an image is converted into gray scale. For detecting lines in images, we used histogram for the intensity related information and threshold. Then, an edge recognition procedure is implemented. We use the first-derivative Sobel detector to determine the edges and edge directions. Then, a Hough transform is accomplished on the threshold edge map for linking the edges. This is the procedure to detect straight line. For circle detection we wrote a function called “houghcircle”.
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Zheng, Sheng-Qing, and 鄭聖慶. "A study of generalized hough transform." Thesis, 1991. http://ndltd.ncl.edu.tw/handle/81256483854283137703.
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JHENG, YU-SIN, and 鄭羽馨. "Lane Departure Detection based on Hough Transform." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/02391936861603554694.
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碩士義守大學
資訊工程學系
104
Automatic land detection plays an important role in utopilot systems, but it is often interfered with the non-lane area on the screen so that it is easy to make some noise to produce false positives in the detection process. This hesis is mainly to propose novel strategies based on Hough transform. First of all, design an adaptive region of interest, and narrow down the detected range to the front of vehicle. The second step is the timeline estimation to correct the detected lane, which is used to exclude exceptions; for instance, the disappearance of the lane can be corrected by using the previous frames. In order to strengthen the stability of detection, make use of the characteristics, both sides of the lane edge paralleling to each other, to propose the land-based detection instead of the line-based detection for removing the interference of other warning marks on the road. This research is focused on the domestic highway, and its objective is to develop lane departure warning systems with real time, anti-interference and high accuracy such that the system can be initiative to remind drivers to maintain traffic safety.
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lo, Rong-Chin, and 駱榮欽. "Extensions of Hough Transform And Their Applications." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/35361745848954655767.
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博士國立交通大學
資訊科學學系
84
Several approaches based on new extensions of the Hough transform (HT) and their applications are proposed for overcoming several problems about processing analyzing gray-scale, color, and perspective images encountered in the use of the conventional Hough transform (CHT) and the generalized Hough transform (GHT). First, a gray-scale Hough transform (GSHT) for thick line detection in gray-scale images is proposed. Second, a method for thick circle detection by an extended HT (EHT) is studied. Third, a modified GHT (MGHT) is proposed for color image detection and matching. Fourth, a perspective transformation invariant generalized Hough transform (PTIGHT) is proposed for perspective planar shape detection and matching. Finally, a new approach to position and orientation tracking using the PTIGHT for virtual reality applications is presented. Usually, the use of the CHT requires the preprocessing steps of thresholding and edge detection (or thinning) before the transform can be performed to detect thick lines (called linear bands) in a gray-scale image. This causes loss of useful gray and position relationship existing among the pixels of a linear band, and requires certain postprocessing step to recover the band in the original image. The proposed GSHT with a gray-scale image as the direct input removes this shortcoming, reqiring neither preprocessing nor postprocessing step in detecting the bands in the image. The MGHT is proposed to remove this weakness. First, lighting changes in an input color image are removed using normalized color values. Next, certain critical pixels of the input image whose neighborhoods have larger variances of color values. For each critical pixel, a feature vector, which includes the normalized color values of the pixel as well as of the pixel''s neighbors, is then constructed. A modified voting rule for the GHT is proposed accordingly, which is based on a
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Wang, Shih-Yuan, and 王世源. "Application of Hough Transform on Lane Detection System." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/03485798484121592326.
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碩士遠東科技大學
機械工程研究所
104
In this paper, we proposed the lane detection method from the image captured by the CCD of the road to locate the lane position. First, we develop a road marking detection system, which uses a line model to identify the position of the lane marks. The Hough transform, and image processing technology would be used to achieve the goal of detecting road markings. In the paper, we use the OpenCV library to achieve all the image process works. The OpenCV library is mainly developed for image manipulating and processing, which image processing functions to provide the user fast and simple way to achieve the image processing process. We develop the lane detection system, mainly used Hough Transform and Canny Edge Filter to provide the capability of stably detect lane position. The first of the detection process is to covert the color road image to gray level image. The procedure is to facilitate the subsequent image processing. Next, the noises of non-road marking in the grayscale images will be filtered by the prosed process. Then the image will be performed the edge detection sequence. Finally, Apply the linear Hough Transform to detect possible lane line on the image segment. As the number of straight line segments after Hough Transform is lot, we proposed a methods to remove inappropriate linear blocks. Then, the two endpoints of each appropriate segment to be connected in order to mark the position of the lane
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Liaw, Joen-Woei, and 廖振偉. "Roof Reconstruction From Digital Images Using Hough Transform." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/15622681211020817942.
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碩士國立交通大學
土木工程系
88
With the progress of the computer technology, digital map is becoming popular and demanded by many disciplines such as Urban Planning, Telecommunication, Architecture Design and Environmental Engineering. They can take use of virtual reality to enhance the traditional operations with digital information. However, these 3D information are acquired by human, the expense is high both in time and human resource. With the automated reconstruction of man-made building, spatial information can be applied widely in many fields. During the process of 3D man-made building reconstruction, linear features extracted with feature-based extraction algorithms only stand for the places of abrupt grayscale change, not necessarily the true edge of building. Building information mixed with others not only increases storage and computation burden, but also degrades the reconstruction. It is necessary to remove redundant information during feature extraction. This research uses the property that the building is higher than the terrain surface to remove the ground pixels. A scheme for reconstruction of man-made building with Hough Transform is proposed in this study. In order to test the proposed scheme, two subscences are extracted from ISPRS’s Suburb Dataset as test images. The experiment shows that only the partial 3D building boundary can be extracted due to insufficient information.
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游俊德. "Hough Transform Neural Networks for Seismic Pattern Analysis." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/96442415973759790909.
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碩士國立交通大學
資訊科學系所
93
A neural network model for Hough transform is proposed. This model can be applied to seismic signal processing and recognition of directed wave (line) and reflected wave (hyperbola) on seismic signal. For seismic signal analysis and processing, the detection of directed wave (line) and reflected wave (hyperbola) are very important. Our method provides convenience to the seismic signal processing.
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Yang, Yu-Chi, and 楊祐齊. "An Improved Hough Transform-based Clock Skew Measurement." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/43671580091238795330.
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碩士國立臺灣科技大學
資訊工程系
103
Precise measurement is one of the critical requirement in the field of clock skew based device identification. Oka et al. recently developed a Hough transform-based clock skew measurement method. This method is able to reach a ppm level precision estimation of clock skew with only few minutes of measurement, and it is robust in communications with lower outliers, which happens when the delay jitters are large. The existing approaches like piecewise minimum algorithm and linear programming algorithm, on the other hand, are severely affected by lower outliers. This research modifies Oka’s method further to pursue more stable estimation and possibly faster measurement. In this research, we use sliding window to find the densest quadrilateral region in the scatter diagram of offset set, replacing the offset voting function of Oka’s method. Since the results of the new method are guaranteed to be optimal, we may derive the clock skew directly. In contrast, Oka’s method needs a linear regression post-processing to stabilize the estimation values. We compared our method with the origin one. Under the classical delay network connections, the experiment results show that the maximum difference reduces from 1.1ppm to 0.4ppm. Under high delay jitter connections, the maximum difference reduces from 1.8ppm to 0.5ppm. The proposed method also provides stable estimation for only 1000 packets, and reduces computation time from 8.3 second to less than 1 second.