Made available in DSpace on 2014-12-17T14:56:07Z (GMT). No. of bitstreams: 1 JesseHNB_DISSERT.pdf: 2206144 bytes, checksum: 191ca3ce00f97e4019b5bdb2bc9ab914 (MD5) Previous issue date: 2012-10-18 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / The vision is one of the five senses of the human body and, in children is responsible for up to 80% of the perception of world around. Studies show that 50% of children with multiple disabilities have some visual impairment, and 4% of all children are diagnosed with strabismus. The strabismus is an eye disability associated with handling capacity of the eye, defined as any deviation from perfect ocular alignment. Besides of aesthetic aspect, the child may report blurred or double vision . Ophthalmological cases not diagnosed correctly are reasons for many school abandonments. The Ministry of Education of Brazil points to the visually impaired as a challenge to the educators of children, particularly in literacy process. The traditional eye examination for diagnosis of strabismus can be accomplished by inducing the eye movements through the doctor s instructions to the patient. This procedure can be played through the computer aided analysis of images captured on video. This paper presents a proposal for distributed system to assist health professionals in remote diagnosis of visual impairment associated with motor abilities of the eye, such as strabismus. It is hoped through this proposal to contribute improving the rates of school learning for children, allowing better diagnosis and, consequently, the student accompaniment / A vis?o ? um dos cinco sentidos do corpo humano e, em crian?as, ? respons?vel por at? 80% da percep??o do mundo ao redor. Estudos revelam que 50% das crian?as com m?ltiplas defici?ncias possuem alguma defici?ncia visual, sendo que 4% de todas as crian?as s?o diagnosticadas com estrabismo. O estrabismo ? uma defici?ncia ocular associada ? capacidade de movimenta??o dos olhos, caracterizada por qualquer desvio no alinhamento ocular perfeito. Al?m do aspecto est?tico, a crian?a pode relatar vista emba?ada ou dupla . Problemas oftalmol?gicos n?o diagnosticados corretamente s?o motivos de muitos abandonos da escola. O Minist?rio da Educa??o do Brasil aponta as defici?ncias visuais como um grande desafio aos educadores de crian?as, principalmente no processo de alfabetiza??o. O exame oftalmol?gico tradicional para diagn?stico do estrabismo pode ser realizado induzindo os movimentos oculares atrav?s de instru??es do m?dico ao paciente. Esse procedimento pode ser reproduzido com aux?lio computacional atrav?s da an?lise de imagens capturadas em v?deo. Este trabalho apresenta uma proposta de sistema de teleoftalmologia para auxiliar profissionais da sa?de no diagn?stico a dist?ncia de defici?ncias visuais associadas ? capacidade motora dos olhos, como o estrabismo. Espera-se atrav?s deste trabalho contribuir diretamente para a melhoria dos ?ndices do aprendizado escolar infantil, permitindo melhores condi??es de diagn?stico e, consequentemente, acompanhamento do aluno

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

本研究嘗試不全以負面假設來看待配戴眼鏡對人臉辨識的影響。吾人將以邊緣偵測圖為基礎，以邊點強度的分析來建立一套定位眼鏡的偵測系統。同時用偵測出的鏡框位置，以邊緣點的強度、密度比較的方式，定位眼睛的位置；並以前述兩套偵測演算，採擷其過程的資訊，進一步地定位鼻子與嘴巴的位置。這些演算形成一個簡易的人臉特徵定位系統，其將可處理配戴眼鏡的人臉；吾人也將進一步地經由其處理過程與結果，分析眼鏡對區域人臉辨識的影響，進而引導出非自然物件可能對人臉辨識的阻礙或輔助。 論文也將以全域比對法中的PCA與ICA演算法作一連串的實驗，剖析眼鏡對於全域辨識的影響；此外，亦用相同的方法來測試非自然物(眼鏡)、光源亮度與人臉角度對於人臉辨識阻礙的程度，以探究是否系統值得花費更大的代價，來移除眼鏡這個被一致認定的人臉辨識障礙，並得以在辨識演算法上獲得更高的效能。 / The objective of this thesis is to investigate the efficacy of face recognition systems when the subjects are wearing glasses. We do not presume that non-facial features such as glasses are nuisances. Instead, we will study whether the inclusion of glasses will have a positive impact on the face detection procedure and how it affects the feature extraction process. We will demonstrate how to use techniques based on local feature analysis to reduce the uncertainties in the matching result due to interferences around the eyes and nose caused by optical glasses. We have also conducted extensive experiments to analyze the effect of glasses on face recognition systems based on global matching strategy. Specifically, we perform both principal component analysis (PCA) and independent component analysis (ICA) on face databases with different percentage of subjects wearing eye glasses. It is concluded that external objects such as glasses will have a negative impact on face recognition using global analysis approaches. However, the adverse influences of illumination and pose are more conspicuous during the recognition process. Therefore, one should take caution when attempting to adapt the global matching scheme to handle the difficulties caused by glasses.

It is well understood that multiple video cameras and computer vision (CV) technology can be used in sport for match officiating, statistics and player performance analysis. A review of the literature reveals a number of existing solutions, both commercial and theoretical, within this domain. However, these solutions are expensive and often complex in their installation. The hypothesis for this research states that by considering only changes in ball motion, automatic event classification is achievable with low-cost monocular video recording devices, without the need for 3-dimensional (3D) positional ball data and representation. The focus of this research is a rigorous empirical study of low cost single consumer-grade video camera solutions applied to table tennis, confirming that monocular CV based detected ball location data contains sufficient information to enable key match-play events to be recognised and measured. In total a library of 276 event-based video sequences, using a range of recording hardware, were produced for this research. The research has four key considerations: i) an investigation into an effective recording environment with minimum configuration and calibration, ii) the selection and optimisation of a CV algorithm to detect the ball from the resulting single source video data, iii) validation of the accuracy of the 2-dimensional (2D) CV data for motion change detection, and iv) the data requirements and processing techniques necessary to automatically detect changes in ball motion and match those to match-play events. Throughout the thesis, table tennis has been chosen as the example sport for observational and experimental analysis since it offers a number of specific CV challenges due to the relatively high ball speed (in excess of 100kph) and small ball size (40mm in diameter). Furthermore, the inherent rules of table tennis show potential for a monocular based event classification vision system. As the initial stage, a proposed optimum location and configuration of the single camera is defined. Next, the selection of a CV algorithm is critical in obtaining usable ball motion data. It is shown in this research that segmentation processes vary in their ball detection capabilities and location out-puts, which ultimately affects the ability of automated event detection and decision making solutions. Therefore, a comparison of CV algorithms is necessary to establish confidence in the accuracy of the derived location of the ball. As part of the research, a CV software environment has been developed to allow robust, repeatable and direct comparisons between different CV algorithms. An event based method of evaluating the success of a CV algorithm is proposed. Comparison of CV algorithms is made against the novel Efficacy Metric Set (EMS), producing a measurable Relative Efficacy Index (REI). Within the context of this low cost, single camera ball trajectory and event investigation, experimental results provided show that the Horn-Schunck Optical Flow algorithm, with a REI of 163.5 is the most successful method when compared to a discrete selection of CV detection and extraction techniques gathered from the literature review. Furthermore, evidence based data from the REI also suggests switching to the Canny edge detector (a REI of 186.4) for segmentation of the ball when in close proximity to the net. In addition to and in support of the data generated from the CV software environment, a novel method is presented for producing simultaneous data from 3D marker based recordings, reduced to 2D and compared directly to the CV output to establish comparative time-resolved data for the ball location. It is proposed here that a continuous scale factor, based on the known dimensions of the ball, is incorporated at every frame. Using this method, comparison results show a mean accuracy of 3.01mm when applied to a selection of nineteen video sequences and events. This tolerance is within 10% of the diameter of the ball and accountable by the limits of image resolution. Further experimental results demonstrate the ability to identify a number of match-play events from a monocular image sequence using a combination of the suggested optimum algorithm and ball motion analysis methods. The results show a promising application of 2D based CV processing to match-play event classification with an overall success rate of 95.9%. The majority of failures occur when the ball, during returns and services, is partially occluded by either the player or racket, due to the inherent problem of using a monocular recording device. Finally, the thesis proposes further research and extensions for developing and implementing monocular based CV processing of motion based event analysis and classification in a wider range of applications.

Notre laboratoire travaille sur la conception et le développement de Modules de Contrôle et d'Interface pour la Téléopération (MCIT). Le but de MCIT est de fournir à l'opérateur une aide pour la perception et pour la commande du site téléopéré. L'aide visuelle consiste en la mise à jour et la superposition de la BD3D sur l'image vidéo. Afin d'automatiser cette aide, un système de reconnaissance de polyèdres à partir d'une image de luminance a été développé et intégré à MCIT dans le cadre de cette thèse. Ce système est constitué d'un module de traitement d'images et d'un module d'appariement 2D/3D. Le 1er module est basé sur la modélisation orientée objet. La transformée de Hough, dont une amélioration est apportée, est utilisée pour extraire les segments de droite de l'image. L'organisation perceptive est appliquée pour trouver un modèle 2D de l'image. Le 2nd module est constitué de deux étapes. La 1ère étape concerne la prédiction d'hypothèses, elle utilise 2 méthodes d'appariement : la méthode des graphes qui donne un nombre d'hypothèses très réduit grâce à l'utilisation des invariants topologiques et projectifs mais, elle échoue en présence de défauts du traitement d'images. Dans ce cas, nous appliquons la méthode du hachage géométrique qui donne toujours une solution. Deux méthodes d'extraction de graphes d'aspects applicables aux polyèdres ont été également développées. La première est destinée à l'appariement par graphes, la seconde est utilisée par le hachage géométrique. La 2nde étape concerne la vérification de l'appariement, nous avons mis en oeuvre des méthodes existantes de recalage et avons développé une méthode hybride qui donne une meilleure précision. Le développement de la calibration automatique de la caméra à l'aide d'un robot a permis également d'augmenter la précision et l'autonomie du système.

This dissertation deals with customised image analysis tools in cancer research. In the field of biomedical sciences, mathematical imaging has become crucial in order to account for advancements in technical equipment and data storage by sound mathematical methods that can process and analyse imaging data in an automated way. This thesis contributes to the development of such mathematically sound imaging models in four ways: (i) automated cell segmentation and tracking. In cancer drug development, time-lapse light microscopy experiments are conducted for performance validation. The aim is to monitor behaviour of cells in cultures that have previously been treated with chemotherapy drugs, since atypical duration and outcome of mitosis, the process of cell division, can be an indicator of successfully working drugs. As an imaging modality we focus on phase contrast microscopy, hence avoiding phototoxicity and influence on cell behaviour. As a drawback, the common halo- and shade-off effect impede image analysis. We present a novel workflow uniting both automated mitotic cell detection with the Hough transform and subsequent cell tracking by a tailor-made level-set method in order to obtain statistics on length of mitosis and cell fates. The proposed image analysis pipeline is deployed in a MATLAB software package called MitosisAnalyser. For the detection of mitotic cells we use the circular Hough transform. This concept is investigated further in the framework of image regularisation in the general context of imaging inverse problems, in which circular objects should be enhanced, (ii) exploiting sparsity of first-order derivatives in combination with the linear circular Hough transform operation. Furthermore, (iii) we present a new unified higher-order derivative-type regularisation functional enforcing sparsity of a vector field related to an image to be reconstructed using curl, divergence and shear operators. The model is able to interpolate between well-known regularisers such as total generalised variation and infimal convolution total variation. Finally, (iv) we demonstrate how we can learn sparsity promoting parametrised regularisers via quotient minimisation, which can be motivated by generalised Eigenproblems. Learning approaches have recently become very popular in the field of inverse problems. However, the majority aims at fitting models to favourable training data, whereas we incorporate knowledge about both fit and misfit data. We present results resembling behaviour of well-established derivative-based sparse regularisers, introduce novel families of non-derivative-based regularisers and extend this framework to classification problems.

Variational methods and Partial Differential Equations (PDEs) have been extensively employed for the mathematical formulation of a myriad of problems describing physical phenomena such as heat propagation, thermodynamic transformations and many more. In imaging, PDEs following variational principles are often considered. In their general form these models combine a regularisation and a data fitting term, balancing one against the other appropriately. Total variation (TV) regularisation is often used due to its edgepreserving and smoothing properties. In this thesis, we focus on the design of TV-based models for several different applications. We start considering PDE models encoding higher-order derivatives to overcome wellknown TV reconstruction drawbacks. Due to their high differential order and nonlinear nature, the computation of the numerical solution of these equations is often challenging. In this thesis, we propose directional splitting techniques and use Newton-type methods that despite these numerical hurdles render reliable and efficient computational schemes. Next, we discuss the problem of choosing the appropriate data fitting term in the case when multiple noise statistics in the data are present due, for instance, to different acquisition and transmission problems. We propose a novel variational model which encodes appropriately and consistently the different noise distributions in this case. Balancing the effect of the regularisation against the data fitting is also crucial. For this sake, we consider a learning approach which estimates the optimal ratio between the two by using training sets of examples via bilevel optimisation. Numerically, we use a combination of SemiSmooth (SSN) and quasi-Newton methods to solve the problem efficiently. Finally, we consider TV-based models in the framework of graphs for image segmentation problems. Here, spectral properties combined with matrix completion techniques are needed to overcome the computational limitations due to the large amount of image data. Further, a semi-supervised technique for the measurement of the segmented region by means of the Hough transform is proposed.

Purpose of this thesis is the quality check of correct button text display on photographed monitors. These photographs contain a variety of image distortions which complicates the following image graphic element recognition. This paper outlines several possibilities to detect buttons on forms and further elaborates on the implemented detection based on contour shapes description. After buttons are found, their defects are detected subsequently. Additionally, this thesis describes an automatic identification of picture with the highest quality for documentation purposes.

From an overview of most commonly used kinematic conceptions of robotic manipulators, the conception of Cartesian robot was identified as the most suitable for the given task of colony picking. A control system consisting of two modular parts has been designed for the colony picking robot. ColonyCounter module is a set of image processing libraries for identification of microbial colonies in image data and precise localization of individual colonies. This has been achieved by combination of multiple methods, most importantly connected components labelling and Hough circular transform. The second module – ColonyPicker – utilizes output of ColonyCounter module to plan the picking and placing of colonies. Subsequently it controls the transfer process itself using an innovative task planning and executing system.

The biometric techniques are well known and widespread nowadays. In this context biometry means automated person recognition using anatomic features. This work uses the iris as the anatomic feature. Iris recognition is taken as the most promising technique of all because of its non-invasiveness and low error rate. The inventor of iris recognition is John G. Daugman. His work underlies almost all current public works of this technology. This final thesis is concerned with biometry based on iris images. The principles of biometric methods based on iris images are described in the first part. The first practical part of this work is aimed at the proposal and realization of two methods which localize the iris inner boundary. The third part presents the proposal and realization of iris image processing in order to classifying persons. The last chapter is focus on evaluation of experimental results and there are also compared our results with several well-known methods.