Three different topics associated with their respective applications are proposed in this thesis. The first application is the implementation of a PC-Based Vision Inspecting Machine. The Second topic is to carry out a advanced Auot-focusing technology. And the third topic is focused on the implementation of a Depth-from-Focus Technology.

Throughout the decades, different techniques have been proposed to improve the depth-of-focus in optical microscopy. Common techniques like optical sectioning microscopy and scanning confocal microscopy have innate problems. By simply modifying the pupil function in microscope imaging system, we can also extend the depth-of-focus. The scanning system with a thin annular pupil has a high depth-of-focus and can scan the whole object, but the output light is too dim to be detected well by a photodetector. In this thesis, we propose a scanning technique employing an optical heterodyne scanning system using a difference-of-Gaussians (DoG) pupil. The object is illuminated by the combined beam which consists of two Gaussian beams with different waists, frequencies, and amplitudes. This system does not block most light like the annular pupil system and can obtain high depth-of-focus. The main objective of the thesis is to extend the depth-of-focus using the proposed system. The depth-of-focus characteristics of the DoG pupil function are examined and compared with those of well-known functions such as the circular, annular, and Gaussian pupils. / Master of Science

La majorité des dispositifs de métrologie basés vision sont équipés de systèmes optiques stéréo ou de systèmes de mesure externes dits actifs. Les méthodes de reconstruction tridimensionnelle (Structure-from-Motion, Shape-from-Shading) applicables à la vision monoculaire souffrent généralement de l’ambiguïté d’échelle. Cette dernière est inhérente au processus d’acquisition d’images qui implique la perte de l’information de profondeur de la scène. La relation entre la taille des objets et la distance de la prise de vue est équivoque.Cette étude a pour objet l’estimation de l’échelle absolue d’une scène par vision passive monofocale. Elle vise à apporter une solution à l’ambiguïté d’échelle uniquement basée vision, pour un système optique monoculaire dont les paramètres internes sont fixes. Elle se destine plus particulièrement à la mesure des lésions en coloscopie. Cette procédure endoscopique (du grec endom : intérieur et scopie : vision) permet l’exploration et l’intervention au sein du côlon à l’aide d’un dispositif flexible (coloscope) embarquant généralement un système optique monofocal. Dans ce contexte, la taille des néoplasies (excroissances anormales de tissu) constitue un critère diagnostic essentiel. Cette dernière est cependant difficile à évaluer et les erreurs d’estimations visuelles peuvent conduire à la définition d’intervalles de temps de surveillance inappropriés. La nécessité de concevoir un système d’estimation de la taille des lésions coloniques constitue la motivation majeure de cette étude. Nous dressons dans la première partie de ce manuscrit un état de l’art synoptique des différents systèmes de mesure basés vision afin de positionner notre étude dans ce contexte. Nous présentons ensuite le modèle de caméra monofocal ainsi que le modèle de formation d’image qui lui a été associé. Ce dernier est la base essentielle des travaux menés dans le cadre de cette thèse. La seconde partie du manuscrit présente la contribution majeure de notre étude. Nous dressons tout d’abord un état de l’art détaillé des méthodes de reconstruction 3D basées sur l’analyse de l’information de flou optique (DfD (Depth-from-Defocus) et DfF (Depth-from-Defocus)). Ces dernières sont des approches passives permettant, sous certaines contraintes d’asservissement de la caméra, de résoudre l’ambiguïté d’échelle. Elles ont directement inspiré le système de mesure par extraction du point de rupture de netteté présenté dans le chapitre suivant. Nous considérons une vidéo correspondant à un mouvement d’approche du système optique face à une région d’intérêt dont on souhaite estimer les dimensions. Notre système de mesure permet d’extraire le point de rupture nette/flou au sein de cette vidéo. Nous démontrons que, dans le cas d’un système optique monofocale, ce point unique correspond à une profondeur de référence pouvant être calibrée. Notre système est composé de deux modules. Le module BET (Blur EstimatingTracking) permet le suivi et l’estimation conjointe de l’information de mise au point d’une région d’intérêt au sein d’une vidéo. Le module BMF (Blur Model Fitting) permet d’extraire de façon robuste le point de rupture de netteté grâce à l’ajustement d’un modèle de flou optique. Une évaluation de notre système appliqué à l’estimation de la taille des lésions coloniques démontre sa faisabilité. Le dernier chapitre de ce manuscrit est consacré à une perspective d’extension de notre approche par une méthode générative. Nous présentons, sous la forme d’une étude théorique préliminaire, une méthode NRSfM (Non-Rigid Structure-from-Motion) permettant la reconstruction à l’échelle de surfaces déformables. Cette dernière permet l’estimation conjointe de cartes de profondeurs denses ainsi que de l’image de la surface aplanie entièrement mise au point. (...) / Vision-based metrology devices generally embed stereoscopic sensors or active measurement systems. Most of the passive 3D reconstruction techniques (Structure-from-Motion, Shape from-Shading) adapted to monocular vision suffer from scale ambiguity. Because the processing of image acquisition implies the loss of the depth information, there is an ambiguous relationship between the depth of a scene and the size of an imaged object. This study deals with the estimation of the absolute scale of a scene using passive monofocal vision. Monofocal vision describes monocular system for which optical parameters are fixed. Such optical systems are notably embedded within endoscopic systems used in colonoscopy. This minimally invasive technique allows endoscopists to explore the colon cavity and remove neoplasias (abnormal growths of tissue). Their size is an essential diagnostic criterion for estimating their rate of malignancy. However, it is difficult to estimate and erroneous visual estimations lead to neoplasias surveillance intervals being inappropriately assigned. The need to design a neoplasia measurement system is the core motivation for our study. In the first part of this manuscript, we review state-of-the-art vision-based metrology devices to provide context for our system. We then introduce monofocal optical systems and the specific image formation model used in our study. The second part deals with the main contribution of our work. We first review in detail state of the art DfD (Depth-from-Defocus) and DfF (Depth-from-Defocus) approaches. They are passive computer vision techniques that enable us to resolve scale ambiguity. Our core contribution is introduced in the following chapter. We define the Infocus-Breakpoint (IB) that allows us to resolve scale from a regular video. The IB is the lower limit of the optical system’s depth of field. Our system relies on two novel technical modules: Blur-Estimating Tracking (BET) and Blur-Model Fitting (BMF). BET allows us to simultaneously track an area of interest and estimate the optical blur information. BMF allows us to robustly extract the IB by fitting an optical blur model to the blur measurement estimated by the BET module. For the optical system is monofocal, the IB corresponds to a reference depth that can be calibrated. In the last chapter, we evaluate our method and propose a neoplasia measurement system adapted to the constraints in colonoscopy examination. The last part of this manuscript is dedicated to a prospect of extension of our method by a generative approach. We present, as a preliminary study, a new NRSfM (Non-Rigid Structure-from-Motion) method allowing the scaled Euclidean 3D reconstruction of deformable surfaces. This approach is based on the simultaneous estimation of dense depth maps corresponding to a set of deformations as well as the in-focus color map of the flattened surface. We first review state-of-the-art methods for 3D reconstruction of deformable surfaces. We then introduce our new generative model as well as an alternation method allowing us to infer it.

Indiana University-Purdue University Indianapolis (IUPUI) / Depth estimation is increasingly becoming more important in computer vision. The requirement for autonomous systems to gauge their surroundings is of the utmost importance in order to avoid obstacles, preventing damage to itself and/or other systems or people. Depth measuring/estimation systems that use multiple cameras from multiple views can be expensive and extremely complex. And as these autonomous systems decrease in size and available power, the supporting sensors required to estimate depth must also shrink in size and power consumption. This research will concentrate on a single passive method known as Depth from Defocus (DfD), which uses an in-focus and out-of-focus image to infer the depth of objects in a scene. The major contribution of this research is the introduction of a new Deep Learning (DL) architecture to process the the in-focus and out-of-focus images to produce a depth map for the scene improving both speed and performance over a range of lighting conditions. Compared to the previous state-of-the-art multi-label graph cuts algorithms applied to the synthetically blurred dataset the DfD-Net produced a 34.30% improvement in the average Normalized Root Mean Square Error (NRMSE). Similarly the DfD-Net architecture produced a 76.69% improvement in the average Normalized Mean Absolute Error (NMAE). Only the Structural Similarity Index (SSIM) had a small average decrease of 2.68% when compared to the graph cuts algorithm. This slight reduction in the SSIM value is a result of the SSIM metric penalizing images that appear to be noisy. In some instances the DfD-Net output is mottled, which is interpreted as noise by the SSIM metric. This research introduces two methods of deep learning architecture optimization. The first method employs the use of a variant of the Particle Swarm Optimization (PSO) algorithm to improve the performance of the DfD-Net architecture. The PSO algorithm was able to find a combination of the number of convolutional filters, the size of the filters, the activation layers used, the use of a batch normalization layer between filters and the size of the input image used during training to produce a network architecture that resulted in an average NRMSE that was approximately 6.25% better than the baseline DfD-Net average NRMSE. This optimized architecture also resulted in an average NMAE that was 5.25% better than the baseline DfD-Net average NMAE. Only the SSIM metric did not see a gain in performance, dropping by 0.26% when compared to the baseline DfD-Net average SSIM value. The second method illustrates the use of a Self Organizing Map clustering method to reduce the number convolutional filters in the DfD-Net to reduce the overall run time of the architecture while still retaining the network performance exhibited prior to the reduction. This method produces a reduced DfD-Net architecture that has a run time decrease of between 14.91% and 44.85% depending on the hardware architecture that is running the network. The final reduced DfD-Net resulted in a network architecture that had an overall decrease in the average NRMSE value of approximately 3.4% when compared to the baseline, unaltered DfD-Net, mean NRMSE value. The NMAE and the SSIM results for the reduced architecture were 0.65% and 0.13% below the baseline results respectively. This illustrates that reducing the network architecture complexity does not necessarily reduce the reduction in performance. Finally, this research introduced a new, real world dataset that was captured using a camera and a voltage controlled microfluidic lens to capture the visual data and a 2-D scanning LIDAR to capture the ground truth data. The visual data consists of images captured at seven different exposure times and 17 discrete voltage steps per exposure time. The objects in this dataset were divided into four repeating scene patterns in which the same surfaces were used. These scenes were located between 1.5 and 2.5 meters from the camera and LIDAR. This was done so any of the deep learning algorithms tested would see the same texture at multiple depths and multiple blurs. The DfD-Net architecture was employed in two separate tests using the real world dataset. The first test was the synthetic blurring of the real world dataset and assessing the performance of the DfD-Net trained on the Middlebury dataset. The results of the real world dataset for the scenes that were between 1.5 and 2.2 meters from the camera the DfD-Net trained on the Middlebury dataset produced an average NRMSE, NMAE and SSIM value that exceeded the test results of the DfD-Net tested on the Middlebury test set. The second test conducted was the training and testing solely on the real world dataset. Analysis of the camera and lens behavior led to an optimal lens voltage step configuration of 141 and 129. Using this configuration, training the DfD-Net resulted in an average NRMSE, NMAE and SSIM of 0.0660, 0.0517 and 0.8028 with a standard deviation of 0.0173, 0.0186 and 0.0641 respectively.

Yes / Background: A range of myopia management (MM) contact lenses are becoming available to practitioners. These lenses are designed to slow myopia progression and axial elongation. This study explored the initial experience of participants wearing daily disposable MM contact lenses to investigate established factors previously associated with successful lens wear. Methods: This was a prospective, double-masked, crossover study. Twenty participants aged 18–30 years old were assigned to wear two daily disposable MM lenses in a randomised order. Visual acuity, contrast sensitivity, and amplitude/lag of accommodation were assessed at baseline, post-insertion, and after 2 and 6 h of lens wear. Self-reported lens comfort and vision quality were recorded at the same timepoints, and at 10 h post-insertion. Pairwise comparisons were performed between the two lenses at each timepoint, as well as assessing changes throughout wear. The relationship of the measured parameters to overall lens satisfaction was also assessed. Results: There were no significant differences between the two MM lenses at any timepoint for any of the participant-reported parameters, including overall satisfaction. A small difference in visual acuity was noted at 6 h post-insertion, although this is unlikely to be clinically significant. Comfort decreased throughout the day, most notably at 10 h post-insertion. A moderate positive correlation was observed between participant-reported visual quality and overall satisfaction. A similar pattern was seen for comfort and overall satisfaction. Self-reported vision quality and measured visual acuity were poorly correlated, highlighting the benefit of subjectively assessing the quality of vision with these lenses. Conclusions: The participants demonstrated comparable measures across a range of measures between the two MM lenses. Notably, half of the participants demonstrated a clear lens preference, although the preferred lens varied between individuals. Candidates for MM may benefit from trialling more than one MM lens design, to maximise initial wearing satisfaction. / This project was supported by the British Contact Lens Association Summer Research Scholarship.

Yes / Background: Soft contact lenses have been developed and licensed for reducing myopia progression. These lenses have different designs, such as extended depth of focus (EDOF) and dual focus (DF). In this prospective, doublemasked, cross-over study, different lens designs were investigated to see whether these had impact on accommodative microfluctuations and eye movements during reading. Methods: Participants were fitted with three lenses in a randomised order; a single vision (SV) design (Omafilcon A2; Proclear), a DF design (Omafilcon A2; MiSight), and an EDOF lens design (Etafilcon A; NaturalVue),. Accommodative microfluctuations were measured at 25 cm for at least 60s in each lens, using a Shin-Nippon SRW-5000 autorefractor adapted to continuously record accommodation at 22Hz. Eye movement data was collected with the Thomson Clinical Eye Tracker incorporating a Tobii Eye bar. Eye movements include fixations per row, fixations per minute, mean regressions per row, total number of regressions, and total rightward saccades. Accommodation data was analysed using power spectrum analysis. Differences between the lenses were compared using a related sample two-way Friedman test. Results: Twenty-three participants (18–29 years) were recruited to take part. The average mean spherical error was − 2.65D ± 1.42DS, with an average age of 23.4 ± 3.5 years. No significant difference for accommodative microfluctuations was found. Significant differences were found for fixations per row (P = 0.03), fixations per minute (P = 0.008), mean regressions per row (P = 0.002), and total number of regressions (P = 0.002), but not total rightward saccades (P = 0.10). Post-hoc analysis indicated the EDOF lens results were significantly different from the other lenses, with more regressive eye movements observed. Conclusions: Regressive saccades appear to increase when wearing EDOF lens designs, which may impact visual comfort. Further studies in children, over a longer period of adaptation are necessary to assess the potential impact of this finding on daily reading activities in children. / This project was supported by the British Contact Lens Association Summer Studentship Award (recipient Muskaan Hussain).

Accommodation is the change in the dioptric power of the eye altering the focus from distance to near. Presbyopia is the loss of accommodative function that occurs with age. There are many techniques used to measure accommodation, however, there is little consensus as to how clinical data should be collected and analysed. The overarching theme of this thesis is the in vivo examination of accommodation and how lifestyle can affect the onset of presbyopia. An open-field autorefractor with badal adaption was used to examine accommodative dynamic profiles under varying demands of vergence. From this data a new metric for assessing the time for accommodative change was derived. Furthermore this thesis describes a bespoke automated accommodative facility instrument that was developed to provide further assessment of accommodative speeds. Defocus curves are used for assessing accommodation and depth-of-focus; the work presented explores the use of non-linear regression models to define the most appropriate method of assessing defocus curves in phakic subjects, and pseudophakic subjects implanted with an extended depth-of-focus intraocular lens. Using an absolute cut-off criteria of +0.30logMAR improved the repeatability and reliability of the depth-of-focus metrics over a cut-off criteria relative to the best corrected visual acuity. A swept-source anterior segment optical coherence tomographer (AS-OCT) was used to image the morphology of the ciliary muscle during accommodation. The accuracy of ciliary muscle measurements was improved when using reference points on the sclera to align the AS-OCT scan. The use of a ciliary muscle area metric demonstrated poor repeatability and reliability when compared to the traditional assessment of muscle morphology via thickness measurements. Physiological ageing in the crystalline lens occurs in line with ageing in other structures in the body. The methods for assessing accommodative function examined in previous chapters, were used to examine whether lifestyle factors which affect the rate of systemic ageing, such as smoking, also affect accommodative function. Although being a current smoker and having greater central adiposity was associated with a slower time for accommodative change, further research is required before these findings can be applied to the target population.

The study of microstructures in brightfield microscopy using unbiased stereology plays a large and growing role in bioscience research. Stereology enables objective quantitative analysis of biological structures within a tissue sample. A first step in the stereology process is to calculate the thickness of a tissue sample by locating the top and bottom surfaces of the sample. The aim of this project is to fully automate this location process by using the relative optical focus measure as an indicator of tissue surface boundary. The current method for identification of focus bounding planes requires a trained user to manually select the top and bottom of the tissue at each sample position examined. To automate finding the correct focal planes, i.e. the "just out of focus" planes at the top and bottom surfaces of the tissue sections, a novel approach was developed. Several gray scale focusing functions were analyzed, but while the traditional emphasis of microscopy focus functions is to find global maximums on the focus curve, in this project the aim was to find the sharp "knees" on the focus curve. Starting with a low focus measure value when the focal plane of the objective lens is out of focus above the tissue sample, the objective focal plane is moved downward through the tissue. The ideal focus measure should increase sharply as the upper surface of the tissue passes into the depth of field of the objective lens. As the focal plane is moved through the tissue, the focus measure value rises and falls as objects within the tissue come in and out of focus. As the bottom tissue surface passes into the depth of field the ideal focus measure should reflect some level of focus, dropping precipitously as the surface passes out of the depth of field into the unfocused region below the tissue.

Today, medical imaging is playing an important role in medicine as it provides the techniques and processes used to create images of the human body or parts thereof for clinical purposes (medical procedures seeking to reveal, diagnose or examine disease) or medical science (including the study of normal anatomy and function). Modalities are developing over time to achieve the highest possible resolution, speed of image acquisition, sensitivity, and specificity. In the past decade, advances in optics, fiber, as well as laser technology have enabled the development of noninvasive optical biomedical imaging technology that can also be applied to endoscopy to reach deeper locations in the human body. The purpose of this dissertation is to investigate a full system design and optimization of an optical coherence tomography (OCT) system to achieve high axial and lateral resolution together with an extended depth of focus for endoscopic in vivo imaging. In this research aimed at advancing endoscopic OCT imaging, two high axial resolution optical coherence tomography systems were developed: (1) a spectrometer-based frequency-domain (FD) OCT achieving an axial resolution of ~2.5 µm using a Ti:Sa femtosecond laser with a 120nm bandwidth centered at 800nm and (2) a swept-source based FD OCT employing a high speed Fourier domain mode locked (FDML) laser that achieves real time in vivo imaging with ~8 µm axial resolution at an acquisition speed of 90,000 A-scans/sec. A critical prior limitation of FD OCT systems is the presence of mirror images in the image reconstruction algorithm that could only be eliminated at the expense of depth and speed of imaging. A key contribution of this research is the development of a novel FD OCT imager that enables full range depth imaging without a loss in acquisition speed. Furthermore, towards the need for better axial resolution, we developed a mathematical model of the OCT signal that includes the effect on phase modulation of phase delay, group delay, and dispersion. From the mathematical model we saw that a Fourier domain optical delay line (FD ODL) incorporated into the reference arm of the OCT system represented a path to higher performance. Here we then present a method to compensate for overall system dispersion with a FDODL that maintains the axial resolution at the limit determined solely by the coherence length of a broadband source. In the development of OCT for endoscopic applications, the need for long depth of focus imaging is critical to accommodate the placement of the catheter anywhere within a vessel. A potential solution to this challenge is Bessel-beam imaging. In a first step, a Bessel-beam based confocal scanning optical microscopy (BCSOM) using an axicon and single mode fiber was investigated with a mathematical model and simulation. The BCSOM approach was then implemented in a FD OCT system that delivered high lateral resolution over a long depth of focus. We reported on the imaging in biological samples for the first time with a double-pass microoptics axicon that demonstrated clearly invariant SNR and 8 um lateral resolution images across a 4 mm depth of focus. Finally, we describe the design and fabrication of a catheter incorporated in the FD OCT. The design, conceived for a 5 mm outer diameter catheter, allows 360 degree scanning with a lateral resolution of about 5 um across a depth of focus of about 1.6 mm. The dissertation concludes with comments for related future work.

This thesis deals with optical distance measurement and 3D scene measurement using focusing techniques with focus on confocal microscopy, depth from focus and depth from defocus. Theoretical part of the thesis is about different approaches to depth map generation and also about micro image defocusing technique for measuring refractive index of transparent materials. Then the camera calibration for focused techniques is described. In the next part of the thesis is described experimentally verification of depth from focus and depth from defocus techniques. For the first technique are shown results of depth map generation and for the second technique is shown comparison between measured distance values and real distance values. Finally, the discussed techniques are compared and evaluated.