Dissertations / Theses on the topic 'Recognition'
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1
Chen, Qian. "Scanning probe recognition microscopy recognition strategies /." Diss., Connect to online resource - MSU authorized users, 2007.
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Thesis (Ph. D.)--Michigan State University. Dept. of Electrical & Computer Engineering, 2007.Title from PDF t.p. (viewed on Apr. 21, 2009) Includes bibliographical references (p. 123-129). Also issued in print.
2
An, Kyung Hee. "Concurrent Pattern Recognition and Optical Character Recognition." Thesis, University of North Texas, 1991. https://digital.library.unt.edu/ark:/67531/metadc332598/.
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The problem of interest as indicated is to develop a general purpose technique that is a combination of the structural approach, and an extension of the Finite Inductive Sequence (FI) technique. FI technology is pre-algebra, and deals with patterns for which an alphabet can be formulated.
3
Goure, Devin Russell. "Contesting Recognition: A Critique of Hegelian Theories of Recognitive Freedom." Oberlin College Honors Theses / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1274107371.
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Tran, Thao, and Nathalie Tkauc. "Face recognition and speech recognition for access control." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-39776.
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This project is a collaboration with the company JayWay in Halmstad. In order to enter theoffice today, a tag-key is needed for the employees and a doorbell for the guests. If someonerings the doorbell, someone on the inside has to open the door manually which is consideredas a disturbance during work time. The purpose with the project is to minimize thedisturbances in the office. The goal with the project is to develop a system that uses facerecognition and speech-to-text to control the lock system for the entrance door. The components used for the project are two Raspberry Pi’s, a 7 inch LCD-touch display, aRaspberry Pi Camera Module V2, a external sound card, a microphone and speaker. Thewhole project was written in Python and the platform used was Amazon Web Services (AWS)for storage and the face recognition while speech-to-text was provided by Google.The system is divided in three functions for employees, guests and deliveries. The employeefunction has two authentication steps, the face recognition and a random generated code that needs to be confirmed to avoid biometric spoofing. The guest function includes the speech-to-text service to state an employee's name that the guest wants to meet and the employee is then notified. The delivery function informs the specific persons in the office that are responsiblefor the deliveries by sending a notification.The test proves that the system will always match with the right person when using the facerecognition. It also shows what the threshold for the face recognition can be set to, to makesure that only authorized people enters the office.Using the two steps authentication, the face recognition and the code makes the system secureand protects the system against spoofing. One downside is that it is an extra step that takestime. The speech-to-text is set to swedish and works quite well for swedish-speaking persons.However, for a multicultural company it can be hard to use the speech-to-text service. It canalso be hard for the service to listen and translate if there is a lot of background noise or ifseveral people speak at the same time.
5
Dimitrov, Emanuil. "Fingerprints recognition." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-5522.
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Nowadays biometric identification is used in a variety of applications-administration, business and even home. Although there are a lot of biometric identifiers, fingerprints are the most widely spread due to their acceptance from the people and the cheap price of the hardware equipment. Fingerprint recognition is a complex image recognition problem and includes algorithms and procedures for image enhancement and binarization, extracting and matching features and sometimes classification. In this work the main approaches in the research area are discussed, demonstrated and tested in a sample application. The demonstration software application is developed by using Verifinger SDK and Microsoft Visual Studio platform. The fingerprint sensor for testing the application is AuthenTec AES2501.
6
Cooke, Jason W. B. "Chirality recognition." Thesis, University of Oxford, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306575.
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Davis, James W. "Gesture recognition." Honors in the Major Thesis, University of Central Florida, 1994. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/126.
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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf.edu/Systems/DigitalInitiatives/DigitalCollections/InternetDistributionConsentAgreementForm.pdf You may also contact the project coordinator, Kerri Bottorff, at kerri.bottorff@ucf.edu for more information.Bachelors
Arts and Sciences
Computer Science
8
OLIVEIRA, MARCELO LUNA GONCALVES DE. "HANDWRITING RECOGNITION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1995. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8738@1.
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICONeste trabalho é proposta uma metodologia de processamento da imagem associada a uma rede neural de perceptrons multicamadas, que é capaz de segmentar e reconhecer caracteres manuscritos cursivos. Esta técnica é robusta quanto à mudança na escala e translação dos caracteres, ligeiras variações na forma do caracter e ruído provocado pro tremores na mão do escritor. Pode ainda tornar-se robusta quanto à rotação, dependendo da escolha dos Descritores de Fourier. O método aproveita a existência de características geométricas e topológicas ou padrões de linhas. Estes componentes são fundamentais na construção da letra. São descritos pré-processamentos, que produzem os esqueletos dos caracteres, tais como algoritmos de afinamento e alisamento heurístico, filtragem zonal para atenuação de retas horizontais e verticais, detecção de contornos, extração heurística de características e a computação dos Descritores de Fourier representantes dos padrões de linha formadores dos caracteres. Após sua extração, as características são combinadas à entrada da rede neural de modo que cada combinação é reconhecida como pertencente a um determinado caracter. Para completar, os resultados do reconhecimento são combinados de modo a eliminar a interseção de classes proveniente das combinações comuns a vários caracteres. Esta metodologia procura a segmentação e o reconhecimento da forma de caracteres manuscritos, sem utilizar qualquer análise de contexto, o que naturalmente pode aumentar sua eficiência.
This work introduces an image processing methodology that, associated with a multi-level neural network of perceptrons, is able to isolate and recognize cursive handwritten characters. The character isolation technique makes use of fundamental geometric and topological aspectos of the characters. The work describe procedures to extract the characters skeletons, such as thinning and smoothing heuristic algorithms, zoned filtering to attenuate horizontal and vertical lines, contour detection, heuristic extraction of characteristics and the computation of Fourier Descriptors representing the line patterns, that compose the characters. After character extraction, its combined characteristics are presented to a neural network in order to allow recognition (identification). Finally, the results of the character identification are combined to avoid classification intersections, due to common aspects in a number of characters. The introduced methodology concerns only with the segmentation and form identification of the characters. It does not adress any context analysis.
9
Childers, Jason C. "Peripheral Recognition." ScholarWorks@UNO, 2014. http://scholarworks.uno.edu/td/1853.
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Perception greatly affects the way we experience and understand the world. Using self-reflective research processes and data collection, I explore how art can subjectively re-present data and what this means for research and knowledge. The artworks through which I discuss these notions are Self Checkout 2013, Bibliography of Virtual Consciousness: Uniform Resource Locator Volumes 1-12 (BOVC:URL 1-12), and Observation Box. Self Checkout 2013 is composed of all of my receipts from 2013. They not only record my transactions, but also re-present data from which one can make inferences regarding my life—my consumer identity, my needs, my desires, etc. BOVC:URL 1-12 re-presents my web history and suggests a reflection on the relationships between physical realities, virtual realities, and the consciousness that mediates experience between them. These forms of data are analyzed by me and through audience participation in Observation Box in an attempt to construct multi-perspectival knowledges from art.
10
Chuchilina, L. M., and I. E. Yeskov. "Speech recognition." Thesis, Видавництво СумДУ, 2008. http://essuir.sumdu.edu.ua/handle/123456789/15995.
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Diefenderfer, Graig T. "Fingerprint recognition." Thesis, Monterey California. Naval Postgraduate School, 2006. http://hdl.handle.net/10945/2761.
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The use of biometrics is an evolving component in today's society. Fingerprint recognition continues to be one of the most widely used biometric systems. This thesis explores the various steps present in a fingerprint recognition system. The study develops a working algorithm to extract fingerprint minutiae from an input fingerprint image. This stage incorporates a variety of image pre-processing steps necessary for accurate minutiae extraction and includes two different methods of ridge thinning. Next, it implements a procedure for matching sets of minutiae data. This process goes through all possible alignments of the datasets and returns the matching score for the best possible alignment. Finally, it conducts a series of matching experiments to compare the performance of the two different thinning methods considered. Results show that thinning by the central line method produces better False Non-match Rates and False Match Rates than those obtained through thinning by the block filter method.US Navy (USN) author.
12
Freeman, Michelle S. "Revenue Recognition." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etsu-works/5777.
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GUALTIERI, MARTINA MARIA MACARENA. "Non Recognition." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2019. http://hdl.handle.net/10281/241155.
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Il non riconoscimento nel diritto internazionale il non riconoscimento presenta diverse questioni che devono essere risolte sia alla luce della sua natura, sia del suo contenuto sia dei suoi effetti. La prassi internazionali offre diversi esempi di non riconoscimento. Il presente lavoro cerca di dare ordine a questa varietà di casi cercando di capire come un’analisi di caso in caso sia l’approccio migliore per riaffermare l’importanza del non riconoscimento. Il fatto che esso presenti un contenuto diverso in base alla situazione non determina la sua non importanza. Esso anzi è uno strumento imprescindibile per garantire la tenuta dell’ordine internazionale.Non-recognition in international law presents several questions that need to be resolved both in the light of its nature, its content and its effects. International practice offers several examples of non-recognition. The present work tries to give order to this variety of cases trying to understand how a case by case analysis is the best approach to reaffirm the importance of non-recognition. The fact that it presents a different content according to the situation which is the object of non-recognition does not determine its irrelevance. In fact, it turns out to be an indispensable tool to guarantee the preservation of the international order.
14
Ou, Chung-Pei. "Protein array for small molecules recognition using pattern recognition." Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.420941.
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Laird, Esther. "Voice recognition and auditory-visual integration in person recognition." Thesis, University of Sussex, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.487906.
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The human ability to recognise a voice is important for social interaction and speech comprehension. In everyday recognitions, the voice can be encountered alone (e.g. over a telephone) or with a face, and ~e person being recognised can be familiar or unfamiliar (such as a witness choosing a perpetrator from a lineup). This thesis - presents 7 studies cov~ring each of these situations. The first paper presents 3 studies on recognition of unfamiliar voices when there is a change in emotional tone between learning and test phases. A tone change reduces recognition accuracy when there is no specific encoding strategy at the learning phase. Familiaris.ation at the learning phase reduces the tone change effect but concentrating on word content at the learning phase does not. The second paper presents 3 studies investigating the limitations of the face overshadowing effect (voice recognition is worse when the voice is learned with a face than if it is learned alone). Blurring faces made face recognition more qifficult but did not affect voice recognition. In experiment 2, participants learned a sentence repeated 3 times, either with the face changing on each repetition or staying the same. Face recognition accuracy was lower when there were 3 faces, but this did not affect voice recognition. In experiment 3, inverting faces' made face recognition more difficult but did not affect voice recognition. The third paper reports that episodic memory for a celebrity is improved when a face and voice are given compared to just a face. A model of person recognition is presented that builds on existing models (e.g. Burton, Bruce & Johnston, 1990; Belin, 2004). It accounts for unfamiliar and familiar voice recognition and the benefits and costs of auditory-visual integration.
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ALVARENGA, EDUARDO PIMENTEL DE. "OPTICAL CHARACTER RECOGNITION FOR AUTOMATED LICENSE PLATE RECOGNITION SYSTEMS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2014. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=28690@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIROCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
Sistemas de reconhecimento automático de placas (ALPR na sigla em inglês) são geralmente utilizados em aplicações como controle de tráfego, estacionamento, monitoração de faixas exclusivas entre outras aplicações. A estrutura básica de um sistema ALPR pode ser dividida em quatro etapas principais: aquisição da imagem, localização da placa em uma foto ou frame de vídeo; segmentação dos caracteres que compõe a placa; e reconhecimento destes caracteres. Neste trabalho focamos somente na etapa de reconhecimento. Para esta tarefa, utilizamos um Perceptron multiclasse, aprimorado pela técnica de geração de atributos baseada em entropia. Mostramos que é possível atingir resultados comparáveis com o estado da arte, com uma arquitetura leve e que permite aprendizado contínuo mesmo em equipamentos com baixo poder de processamento, tais como dispositivos móveis.
ALPR systems are commonly used in applications such as traffic control, parking ticketing, exclusive lane monitoring and others. The basic structure of an ALPR system can be divided in four major steps: image acquisition, license plate localization in a picture or movie frame; character segmentation; and character recognition. In this work we ll focus solely on the recognition step. For this task, we used a multiclass Perceptron, enhanced by an entropy guided feature generation technique. We ll show that it s possible to achieve results on par with the state of the art solution, with a lightweight architecture that allows continuous learning, even on low processing power machines, such as mobile devices.
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Muller, Neil Leonard. "Image recognition using the Eigenpicture Technique (with specific applications in face recognition and optical character recognition)." Master's thesis, University of Cape Town, 1998. http://hdl.handle.net/11427/14381.
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Includes bibliographical references.In the first part of this dissertation, we present a detailed description of the eigenface technique first proposed by Sirovich and Kirby and subsequently developed by several groups, most notably the Media Lab at MIT. Other significant contributions have been made by Rockefeller University, whose ideas have culminated in a commercial system known as Faceit. For a different techniques (i.e. not eigenfaces) and a detailed comparison of some other techniques, the reader is referred to [5]. Although we followed ideas in the open literature (we believe there that there is a large body of advanced proprietary knowledge, which remains inaccessible), the implementation is our own. In addition, we believe that the method for updating the eigenfaces to deal with badly represented images presented in section 2. 7 is our own. The next stage in this section would be to develop an experimental system that can be extensively tested. At this point however, another, nonscientific difficulty arises, that of developing an adequately large data base. The basic problem is that one needs a training set representative of all faces to be encountered in future. Note that this does not mean that one can only deal with faces in the database, the whole idea is to be able to work with any facial image. However, a data base is only representative if it contains images similar to anything that can be encountered in future. For this reason a representative database may be very large and is not easy to build. In addition for testing purposes one needs multiple images of a large number of people, acquired over a period of time under different physical conditions representing the typical variations encountered in practice. Obviously this is a very slow process. Potentially the variation between the faces in the database can be large suggesting that the representation of all these different images in terms of eigenfaces may not be particularly efficient. One idea is to separate all the facial images into different, more or less homogeneous classes. Again this can only be done with access to a sufficiently large database, probably consisting of several thousand faces.
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Scott, Emily A. "Recognition of aerospace acoustic sources using advanced pattern recognition techniques." Thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-03022010-020131/.
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Zhou, Shaohua. "Unconstrained face recognition." College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/1800.
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Thesis (Ph. D.) -- University of Maryland, College Park, 2004.Thesis research directed by: Electrical Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Eriksson, Mattias. "Speech recognition availability." Thesis, Linköping University, Department of Computer and Information Science, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2651.
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This project investigates the importance of availability in the scope of dictation programs. Using speech recognition technology for dictating has not reached the public, and that may very well be a result of poor availability in today’s technical solutions.
I have constructed a persona character, Johanna, who personalizes the target user. I have also developed a solution that streams audio into a speech recognition server and sends back interpreted text. Johanna affirmed that the solution was successful in theory.
I then incorporated test users that tried out the solution in practice. Half of them do indeed claim that their usage has been and will continue to be increased thanks to the new level of availability.
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Xiu, Pingping. "Whole-book recognition." LEHIGH UNIVERSITY, 2011. http://pqdtopen.proquest.com/#viewpdf?dispub=3439862.
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Ustun, Bulend. "3d Face Recognition." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12609075/index.pdf.
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In this thesis, the effect of registration process is evaluated as well as several methods proposed for 3D face recognition. Input faces are in point cloud form and have noises due to the nature of scanner technologies. These inputs are noise filtered and smoothed before registration step. In order to register the faces an average face model is obtained from all the images in the database. All the faces are registered to the average model and stored to the database. Registration is performed by using a rigid registration technique called ICP (Iterative Closest Point), probably the most popular technique for registering two 3D shapes. Furthermore some variants of ICP are implemented and they are evaluated in terms of accuracy, time and number of iterations needed for convergence. At the recognition step, several recognition methods, namely Eigenface, Fisherface, NMF (Nonnegative Matrix Factorization) and ICA (Independent Component Analysis) are tested on registered and non-registered faces and the performances are evaluated.
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Aydin, Ufuk Suat. "Traffic Sign Recognition." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610590/index.pdf.
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Designing smarter vehicles, aiming to minimize the number of driverbased wrong decisions or accidents, which can be faced with during the drive, is one of hot topics of today&rsquos automotive technology. In the design of smarter vehicles, several research issues can be addressed
one of which is Traffic Sign Recognition (TSR). In TSR systems, the aim is to remind or warn drivers about the restrictions, dangers or other information imparted by traffic signs, beforehand. Since the existing signs are designed to draw drivers&rsquo
attention by their colors and shapes, processing of these features is one of the crucial parts in these systems. In this thesis, a Traffic Sign Recognition System, having ability of detection and identification of traffic signs even with bad visual artifacts those originate from some weather conditions or other circumstances, is developed. The developed algorithm in this thesis, segments the required color influenced by the illumination of the environment, then reconstructs the shape of partially occluded traffic sign by its remaining segments and finally, identifies it. These three stages are called as &ldquo
Segmentation&rdquo
, &ldquo
Reconstruction&rdquo
and &ldquo
Identification&rdquo
respectively, within this thesis. Due to the difficulty of analyzing partial segments to construct the main frame (a whole sign), the main complexity of the algorithm takes place in the &ldquo
Reconstruction&rdquo
stage.
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Erdem, Erem. "Digital Modulation Recognition." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12611281/index.pdf.
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In this thesis work, automatic recognition algorithms for digital modulated signals are surveyed.
Feature extraction and classification algorithm stages are the main parts of a modulation recognition system. Performance of the modulation recognition system mainly depends on the prior knowledge of some of the signal parameters, selection of the key features and classification algorithm selection.
Unfortunately, most of the features require some of the signal parameters such as carrier frequency, pulse shape, time of arrival, initial phase, symbol rate, signal to noise ratio, to be known or to be extracted. Thus, in this thesis, features which do not require prior knowledge of the signal parameters, such as the number of the peaks in the envelope histogram and the locations of these peaks, the number of peaks in the frequency histogram, higher order moments of the signal are considered. Particularly, symbol rate and signal to noise ratio estimation methods are surveyed. A method based on the cyclostationarity analysis is used for symbol rate estimation and a method based on the eigenvector decomposition is used for the estimation of signal to noise ratio. Also, estimated signal to noise ratio is used to improve the performance of the classification algorithm.
Two methods are proposed for modulation recognition:
1) Decision tree based method
2) Bayesian based classification method
A method to estimate the symbol rate and carrier frequency offset of minimum-shift keying (MSK) signal is also investigated.
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Songke, Li, and Chen Yixian. "License plate recognition." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-9442.
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This paper presents a method for license plate recognition through analysis of vehicle images. Accurate location of license plate and extracting characters of plate are implemented. In the plate location module, the paper puts forward arithmetic of plate edge recognition by morphology algorithms. Meanwhile, Radon transform is used to adjust different angles between viewer and license plate. At last, characters extraction is done by histogram. And the extraction characters are matched with the templates. Experimental results show that this approach can recognize license plates more effectively and establish a good technical base for the future advanced license plate recognition.
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Li, Daqing. "Road sign recognition." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ39486.pdf.
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Mulder, Frank Willem. "Tactical plan recognition." [Maastricht : Maastricht : Universiteit Maasticht] ; University Library, Maastricht University [Host], 2005. http://arno.unimaas.nl/show.cgi?fid=8682.
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Yao, Xiaoqiang. "Pattern-recognition scheduling." Ohio : Ohio University, 1996. http://www.ohiolink.edu/etd/view.cgi?ohiou1177698616.
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Helmer, Scott. "Embodied object recognition." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/42481.
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The ability to localize and categorize objects via imagery is central to many potential applications, including autonomous vehicles, mobile robotics, and surveillance. In this thesis we employ a probabilistic approach to show how utilizing multiple images of the same scene can improve detection. We cast the task of object detection as finding the set of objects that maximize the posterior probability given a model of the categories and a prior for their spatial arrangements.
We first present an approach to detection that leverages depth data from binocular stereo by factoring classification into two terms: an independent appearance-based object classifier, and a term for the 3D shape. We overcome the missing data and the limited fidelity of stereo by focusing on the size of the object and the presence of discontinuities. We go on to demonstrate that even with off-the-shelf stereo algorithms we can significantly improve detection on two household objects, mugs and shoes, in the presence of significant background clutter and textural variation.
We also present a novel method for object detection, both in 2D and in 3D, from multiple images with known extrinsic camera parameters. We show that by also inferring the 3D position of the objects we can improve object detection by incorporating size priors and reasoning about the 3D geometry of a scene. We also show that integrating information across multiple viewpoints allows us to boost weak classification responses, overcome occlusion, and reduce false positives. We demonstrate the efficacy of our approach, over single viewpoint detection, on a dataset containing mugs, bottles, bowls, and shoes in a variety of challenging scenarios.
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Yar, Majid. "Community and recognition." Thesis, Lancaster University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322864.
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Fitzpatrick, Kevin. "Organometallic chirality recognition." Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359451.
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Cheng, You-Chi. "Robust gesture recognition." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53492.
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It is a challenging problem to make a general hand gesture recognition system work in a practical operation environment. In this study, it is mainly focused on recognizing English letters and digits performed near the steering wheel of a car and captured by a video camera. Like most human computer interaction (HCI) scenarios, the in-car gesture recognition suffers from various robustness issues, including multiple human factors and highly varying lighting conditions. It therefore brings up quite a few research issues to be addressed. First, multiple gesturing alternatives may share the same meaning, which is not typical in most previous systems. Next, gestures may not be the same as expected because users cannot see what exactly has been written, which increases the gesture diversity significantly.In addition, varying illumination conditions will make hand detection trivial and thus result in noisy hand gestures. And most severely, users will tend to perform letters at a fast pace, which may result in lack of frames for well-describing gestures. Since users are allowed to perform gestures in free-style, multiple alternatives and variations should be considered while modeling gestures. The main contribution of this work is to analyze and address these challenging issues step-by-step such that eventually the robustness of the whole system can be effectively improved. By choosing color-space representation and performing the compensation techniques for varying recording conditions, the hand detection performance for multiple illumination conditions is first enhanced. Furthermore, the issues of low frame rate and different gesturing tempo will be separately resolved via the cubic B-spline interpolation and i-vector method for feature extraction. Finally, remaining issues will be handled by other modeling techniques such as sub-letter stroke modeling. According to experimental results based on the above strategies, the proposed framework clearly improved the system robustness and thus encouraged the future research direction on exploring more discriminative features and modeling techniques.
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Petheram, R. J. "Automatic pattern recognition." Thesis, University of Nottingham, 1989. http://eprints.nottingham.ac.uk/28974/.
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In this thesis the author presents a new method for the location, extraction and normalisation of discrete objects found in digital images. The extraction is by means of sub-pixcel contour following around the object. The normalisation obtains and removes the information concerning size, orientation and location of the object within an image. Analyses of the results are carried out to determine the confidence in recognition of patterns, and methods of cross correlation of object descriptions using Fourier transforms are demonstrated.
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Datta, Ankur. "Gait Based Recognition." Honors in the Major Thesis, University of Central Florida, 2004. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/436.
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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucfBachelors
Engineering and Computer Science
Computer Science
35
Chatzaras, Anargyros, and Georgios Savvidis. "Seamless speaker recognition." Thesis, KTH, Radio Systems Laboratory (RS Lab), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-159021.
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In a technologically advanced society, the average person manages dozens of accounts for e-mail, social networks, e-banking, and other electronic services. As the number of these accounts increases, the need for automatic user identification becomes more essential. Biometrics have long been used to identify people and are the most common (if not the only) method to achieve this task. Over the past few years, smartphones have become frequently used gadgets. These devices have built-in microphones and are commonly used by a single user or a small set of users, such as a couple or a family. This thesis uses a smartphone’s microphone to capture user’s speech and identify him/her. Existing speaker recognition systems typically prompt the user to provide long voice samples in order to provide accurate results. This results in a poor user experience and discourages users who do not have the patience to go through such a process. The main idea behind the speaker recognition approach presented in this thesis is to provide a seamless user experience where the recording of the user’s voice takes place in the background. An Android application is developed which silently collects voices samples and performs speaker recognition without requiring extensive user interaction. Two variants of the proposed tool have been developed and are described in depth in this thesis. The open source framework Recognito is used to perform the speaker recognition task. The analysis of Recognito showed that it is not capable of achieving high accuracy especially when the voice samples contain background noise. Finally, the comparison between the two architectures showed that they do not differ significantly in terms of performance.I ett teknologiskt avancerat samhälle så hanterar den genomsnittliga personen dussintals konton för e-post, sociala nätverk, internetbanker, och andra elektroniska tjänster. Allt eftersom antalet konton ökar, blir behovet av automatisk identifiering av användaren mer väsentlig. Biometri har länge använts för att identifiera personer och är den vanligaste (om inte den enda) metoden för att utföra denna uppgift. Smartphones har under de senaste åren blivit allt mer vanligt förekommande, de ger användaren tillgång till de flesta av sina konton och, i viss mån, även personifiering av enheterna baserat på deras profiler på sociala nätverk. Dessa enheter har inbyggda mikrofoner och används ofta av en enskild användare eller en liten grupp av användare, till exempel ett par eller en familj. Denna avhandling använder mikrofonen i en smartphone för att spela in användarens tal och identifiera honom/henne. Befintliga lösningar för talarigenkänning ber vanligtvis användaren om att ge långa röstprover för att kunna ge korrekta resultat. Detta resulterar i en dålig användarupplevelse och avskräcker användare som inte har tålamod att gå igenom en sådan process. Huvudtanken bakom den strategi för talarigenkänningen som presenteras i denna avhandling är att ge en sömlös användarupplevelse där inspelningen av användarens röst sker i bakgrunden. En Android-applikation har utvecklats som, utan att märkas, samlar in röstprover och utför talarigenkänning på dessa utan att kräva omfattande interaktion av användaren. Två varianter av verktyget har utvecklats och dessa beskrivs ingående i denna avhandling. Öpen source-ramverket Recognito används för att utföra talarigenkänningen. Analysen av Recognito visade att det inte klarar av att uppnå tillräckligt hög noggrannhet, speciellt när röstproverna innehåller bakgrundsbrus. Dessutom visade jämförelsen mellan de två arkitekturerna att de inte skiljer sig nämnvärt i fråga om prestanda.
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Mahmood, A. "Automatic drawing recognition." Thesis, University of Nottingham, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.381072.
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Choakjarernwanit, Naruetep. "Statistical pattern recognition." Thesis, University of Surrey, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306586.
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Akra, Mohamad A. (Mohamad Ahmad). "Automated text recognition." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/11109.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.Includes bibliographical references (leaves 92-96).
by Mohamad A. Akra.
Ph.D.
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Wells, William Mercer. "Statistical object recognition." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12606.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.Includes bibliographical references (p. 169-177).
by William Mercer Wells, III.
Ph.D.
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Salamin, Hugues Eric. "Automatic role recognition." Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/4367/.
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The computing community is making significant efforts towards the development of automatic approaches for the analysis of social interactions. The way people interact depends on the context, but there is one aspect that all social interactions seem to have in common: humans behave according to roles. Therefore, recognizing the roles of participants is an essential step towards understanding social interactions and the construction of socially aware computer. This thesis addresses the problem of automatically recognizing roles of participants in multi-party recordings. The objective is to assign to each participant a role. All the proposed approaches use a similar strategy. They all start by segmenting the audio into turns. Those turns are used as basic analysis units. The next step is to extract features accounting for the organization of turns. The more sophisticated approaches extend the features extracted with features from either the prosody or the semantic. Finally, the mapping of people or turns to roles is done using statistical models. The goal of this thesis is to gain a better understanding of role recognition and we will investigate three aspects that can influence the performance of the system: We investigate the impact of modelling the dependency between the roles. We investigate the contribution of different modalities for the effectiveness of role recognition approach. We investigate the effectiveness of the approach for different scenarios. Three models are proposed and tested on three different corpora totalizing more than 90 hours of audio. The first contribution of this thesis is to investigate the combination of turn-taking features and semantic information for role recognition, improving the accuracy of role recognition from a baseline of 46.4% to 67.9% on the AMI meeting corpus. The second contribution is to use features extracted from the prosody to assign roles. The performance of this model is 89.7% on broadcast news and 87.0% on talk-shows. Finally, the third contribution is the development of a model robust to change in the social setting. This model achieved an accuracy of 86.7% on a database composed of a mixture of broadcast news and talk-shows.
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Al, Rifaee Mustafa Moh'd Husien. "Unconstrained iris recognition." Thesis, De Montfort University, 2014. http://hdl.handle.net/2086/10949.
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This research focuses on iris recognition, the most accurate form of biometric identification. The robustness of iris recognition comes from the unique characteristics of the human, and the permanency of the iris texture as it is stable over human life, and the environmental effects cannot easily alter its shape. In most iris recognition systems, ideal image acquisition conditions are assumed. These conditions include a near infrared (NIR) light source to reveal the clear iris texture as well as look and stare constraints and close distance from the capturing device. However, the recognition accuracy of the-state-of-the-art systems decreases significantly when these constraints are relaxed. Recent advances have proposed different methods to process iris images captured in unconstrained environments. While these methods improve the accuracy of the original iris recognition system, they still have segmentation and feature selection problems, which results in high FRR (False Rejection Rate) and FAR (False Acceptance Rate) or in recognition failure. In the first part of this thesis, a novel segmentation algorithm for detecting the limbus and pupillary boundaries of human iris images with a quality assessment process is proposed. The algorithm first searches over the HSV colour space to detect the local maxima sclera region as it is the most easily distinguishable part of the human eye. The parameters from this stage are then used for eye area detection, upper/lower eyelid isolation and for rotation angle correction. The second step is the iris image quality assessment process, as the iris images captured under unconstrained conditions have heterogeneous characteristics. In addition, the probability of getting a mis-segmented sclera portion around the outer ring of the iris is very high, especially in the presence of reflection caused by a visible wavelength light source. Therefore, quality assessment procedures are applied for the classification of images from the first step into seven different categories based on the average of their RGB colour intensity. An appropriate filter is applied based on the detected quality. In the third step, a binarization process is applied to the detected eye portion from the first step for detecting the iris outer ring based on a threshold value defined on the basis of image quality from the second step. Finally, for the pupil area segmentation, the method searches over the HSV colour space for local minima pixels, as the pupil contains the darkest pixels in the human eye. In the second part, a novel discriminating feature extraction and selection based on the Curvelet transform are introduced. Most of the state-of-the-art iris recognition systems use the textural features extracted from the iris images. While these fine tiny features are very robust when extracted from high resolution clear images captured at very close distances, they show major weaknesses when extracted from degraded images captured over long distances. The use of the Curvelet transform to extract 2D geometrical features (curves and edges) from the degraded iris images addresses the weakness of 1D texture features extracted by the classical methods based on textural analysis wavelet transform. Our experiments show significant improvements in the segmentation and recognition accuracy when compared to the-state-of-the-art results.
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Placide, Eustache. "Hybrid pattern recognition." DigitalCommons@Robert W. Woodruff Library, Atlanta University Center, 1987. http://digitalcommons.auctr.edu/dissertations/3018.
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There are two basic approaches to pattern recognition: decision-theoretic and syntactic. However, in actual applications, a combination of both may be needed. One such hybrid technique consists of syntactic method coupled with stochasticity in its grammar. Randomness in the syntactic case is caused due to noise and insufficient information about characteristics of pattern classes. To absorb the effect of this randomness, the grammar must be generalized to include the probabilities of production rules.
In this paper, a preliminary discussion of issues involved with hybrid techniques, in general, and stochastic grammars, in particular, is provided. An efficient algorithm for an automatic learning of production probabilities is devised. Concepts are illustrated via examples.
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McMahon, Stephen Andrew. "Protein-carbohydrate recognition." Thesis, University of St Andrews, 1999. http://hdl.handle.net/10023/14045.
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Protein-carbohydrate recognition is an important target for inhibitor development. Improved inhibitor design requires a fundamental molecular basis of these interactions. This thesis describes the preliminary structural studies on three carbohydrate processing enzymes, UDP-galactopyranose mutase, alpha-D-glucose-1-phosphate thymidylyltransferase and TDP-glucose 4,6-dehydratase. These enzymes are found in important human pathogens such as Mycobacterium tuberculosis and Salmonella typhimurium. The major focus of the thesis has been on UDP-galactopyranose mutase, the enzyme responsible for catalysing synthesis of the thermodynamically unfavourable 5 membered ring form of galactose, UDP-galactofuranose from the thermodynamically favoured 6 membered ring form, UDP-galactopyranose. UDP-galactofuranose plays a key role in mycobacterial cell walls. This thesis also describes work with concanavalin A. This legume lectin is an invaluable model for the study of protein-carbohydrate interactions. Two concanavalin A complexes are discussed. Both structures clear up misunderstandings in the literature and provide an insight into designing enzyme inhibitors.
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Dobler, Michael. "Rethinking revenue recognition." Inderscience Publishers, 2008. https://tud.qucosa.de/id/qucosa%3A36452.
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Revenue recognition is one of the most crucial issues in financial reporting and the prevalent source for recent accounting scandals. International financial reporting standard setters are conducting a major project rethinking revenue recognition. Tentative proposals of the project Revenue Recognition feature an asset-liability approach relying on measurement at fair values or at allocated customer consideration amounts. This paper chooses construction contracts to illustrate and to evaluate the far-reaching changes implied by the proposals in a multi-period context. Main results suggest that the proposals are ambivalent in terms of relevance but critical in terms of reliability compared to the recent treatment under IAS 11. Particularly, a pure fair value approach yields irritating patterns of revenue recognition found inappropriate for stewardship purposes. While its adoption for revenue recognition under IFRSs is unlikely due to regulatory incompatibilities, measuring performance obligations at allocated consideration amount partly mitigates the concerns.
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chiluka, srikanthreddy. "Traffic Sign Recognition." Thesis, Blekinge Tekniska Högskola, Institutionen för matematik och naturvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-21343.
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Smart vehicles with capabilities of autonomous driving are a big revolution in automobile industry. The vehicles can sense their environment and react based on it. It replaces the manual driver. Recognition of traffic sign is an important enabler for autonomous driving. Camera installed in the vehicle captures the traffic sign on the road and they must be recognized accurately for triggering the suitable action. In this thesis both image processing and Euclidean distance matching are used to pre-process and classify the traffic signs and thresholding and thinning are applied on image for feature extraction. In this work, a simple, efficient traffic sign recognition system with low computational time and to achieve good accuracy is proposed. Time to classify the traffic sign is achieved in milliseconds and accuracy is maintained using the proposed system. Keywords: Autonomous Driving, Image processing, Thresholding, Thinning, Euclidean distance matching.
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Paripati, Praveen Kumar. "Polyhedra:representation and recognition." Thesis, Virginia Tech, 1989. http://hdl.handle.net/10919/43105.
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Computer Aided Design systems intended for three dimensional solid modelling
have traditionally used geometric representations incompatible with established representations
in computer vision. The utilization of object models built using these
systems require a representation conversion before they can be used in automatic
sensing systems. Considerable advantages follow from building a combined CAD
and sensing system based on a common geometric model. For example, a library
of objects can be built up and its models used in vision and touch sensing system
integrated into an automated assembly line to 'discriminate between objects and determine-
orientation and distance. This thesis studies a representation scheme, the
dual spherical representation, useful in geometric modelling and machine recognition.
We prove that the representation uniquely represents genus 0 polyhedra. We
show by,example that our representation is not a strict dual of the vertex connectivity graph, and hence is not necessarily ambiguous. However, we have not been able to prove that the representation is unambiguous. An augmented dual spherical
representation which is unique for general polyhedra is presented. This graph theoretic
approach to polyhedra also results in an elegant method for decomposition of polyhedra into combinatorially convex parts. An algorithm implementation details and experimental results for recognition of polyhedra using a large field tactile
sensor are given. A theorem relating the edges in the dual spherical representation and the edge under perspective projection is proved. Sensor fusion using visual and tactile sensory inputs is proposed to improve recognition rates.Master of Science
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Shah, Jaimin Nitesh. "Underwater Document Recognition." University of Dayton / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1619452066101887.
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Kaâniche, Mohamed Bécha. "Human gesture recognition." Nice, 2009. http://www.theses.fr/2009NICE4032.
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Dans cette thèse, nous voulons reconnaître les gestes (par ex. Lever la main) et plus généralement les actions brèves (par ex. Tomber, se baisser) effectués par un individu. De nombreux travaux ont été proposés afin de reconnaître des gestes dans un contexte précis (par ex. En laboratoire) à l’aide d’une multiplicité de capteurs (par ex. Réseaux de cameras ou individu observé muni de marqueurs). Malgré ces hypothèses simplificatrices, la reconnaissance de gestes reste souvent ambiguë en fonction de la position de l’individu par rapport aux caméras. Nous proposons de réduire ces hypothèses afin de concevoir un algorithme général permettant de reconnaître des gestes d’un individu évoluant dans un environnement quelconque et observé `a l’aide d’un nombre réduit de caméras. Il s’agit d’estimer la vraisemblance de la reconnaissance des gestes en fonction des conditions d’observation. Notre méthode consiste `a classifier un ensemble de gestes `a partir de l’apprentissage de descripteurs de mouvement. Les descripteurs de mouvement sont des signatures locales du mouvement de points d’intérêt associés aux descriptions locales de la texture du voisinage des points considérés. L’approche a été validée sur une base de données de gestes publique KTH et des résultats encourageants ont été obtenusIn this thesis, we aim to recognize gestures (e. G. Hand raising) and more generally short actions (e. G. Fall, bending) accomplished by an individual. Many techniques have already been proposed for gesture recognition in specific environment (e. G. Laboratory) using the cooperation of several sensors (e. G. Camera network, individual equipped with markers). Despite these strong hypotheses, gesture recognition is still brittle and often depends on the position of the individual relatively to the cameras. We propose to reduce these hypotheses in order to conceive general algorithm enabling the recognition of the gesture of an individual involving in an unconstrained environment and observed through limited number of cameras. The goal is to estimate the likelihood of gesture recognition in function of the observation conditions. Our method consists of classifying a set of gestures by learning motion descriptors. These motion descriptors are local signatures of the motion of corner points which are associated with their local textural description. We demonstrate the effectiveness of our motion descriptors by recognizing the actions of the public KTH database
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Robinson, Anthony David. "Ship target recognition." Master's thesis, University of Cape Town, 1996. http://hdl.handle.net/11427/9229.
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Includes bibliographical references.In this report the classification of ship targets using a low resolution radar system is investigated. The thesis can be divided into two major parts. The first part summarizes research into the applications of neural networks to the low resolution non-cooperative ship target recognition problem. Three very different neural architectures are investigated and compared, namely; the Feedforward Network with Back-propagation, Kohonen's Supervised Learning Vector Quantization Network, and Simpson's Fuzzy Min-Max neural network. In all cases, pre-processing in the form of the Fourier-Modified Discrete Mellin Transform is used as a means of extracting feature vectors which are insensitive to the aspect angle of the radar. Classification tests are based on both simulated and real data. Classification accuracies of up to 93 are reported. The second part is of a purely investigative nature, and summarizes a body of research aimed at exploring new ground. The crux of this work is centered on the proposal to use synthetic range profiling in order to achieve a much higher range resolution (and hence better classification accuracies). Included in this work is a comprehensive investigation into the use of super-resolution and noise reducing eigendecomposition techniques. Algorithms investigated include the Principal Eigenvector Method, the Total Least Squares Method, and the MUSIC method. A final proposal for future research and development concerns the use of time domain averaging to improve the classification performance of the radar system. The use of an iterative correlation algorithm is investigated.
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Wong, Vincent. "Human face recognition /." Online version of thesis, 1994. http://hdl.handle.net/1850/11882.
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