Demonstration Platform for Visual Quality Metrics

This thesis presents two graphical user interfaces for the project DigiQ - Fusion of Digital and Visual Print Quality, a project for computationally modeling the subjective human experience of print quality by measuring the image with certain metrics. After presenting the user interfaces, methods for reducing the computation time of several of the metrics and the image registration process required to compute the metrics, and details of their performance are given. The weighted sample method for the image registration process was able to signifigantly decrease the calculation times while resulting in some error. The random sampling method for the metrics greatly reduced calculation time while maintaining excellent accuracy, but worked with only two of the metrics.

Learning Robot Motions from Visual Sensing

Learning from demonstration becomes increasingly popular as an efficient way of robot programming. Not only a scientific interest acts as an inspiration in this case but also the possibility of producing the machines that would find application in different areas of life: robots helping with daily routine at home, high performance automata in industries or friendly toys for children. One way to teach a robot to fulfill complex tasks is to start with simple training exercises, combining them to form more difficult behavior. The objective of the Master’s thesis work was to study robot programming with visual input. Dynamic movement primitives (DMPs) were chosen as a tool for motion learning and generation. Assuming a movement to be a spring system influenced by an external force, making this system move, DMPs represent the motion as a set of non-linear differential equations. During the experiments the properties of DMP, such as temporal and spacial invariance, were examined. The effect of the DMP parameters, including spring coefficient, damping factor, temporal scaling, on the trajectory generated were studied.

Computational visual quality of digitally printed images

The problem of understanding how humans perceive the quality of a reproduced image is of interest to researchers of many fields related to vision science and engineering: optics and material physics, image processing (compression and transfer), printing and media technology, and psychology. A measure for visual quality cannot be defined without ambiguity because it is ultimately the subjective opinion of an “end-user” observing the product. The purpose of this thesis is to devise computational methods to estimate the overall visual quality of prints, i.e. a numerical value that combines all the relevant attributes of the perceived image quality. The problem is limited to consider the perceived quality of printed photographs from the viewpoint of a consumer, and moreover, the study focuses only on digital printing methods, such as inkjet and electrophotography. The main contributions of this thesis are two novel methods to estimate the overall visual quality of prints. In the first method, the quality is computed as a visible difference between the reproduced image and the original digital (reference) image, which is assumed to have an ideal quality. The second method utilises instrumental print quality measures, such as colour densities, measured from printed technical test fields, and connects the instrumental measures to the overall quality via subjective attributes, i.e. attributes that directly contribute to the perceived quality, using a Bayesian network. Both approaches were evaluated and verified with real data, and shown to predict well the subjective evaluation results.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

Verbal learning in mild cognitive impairment and alzheimer's disease : behavioural and neural approaches

The main focus of the present thesis was at verbal episodic memory processes that are particularly vulnerable to preclinical and clinical Alzheimer’s disease (AD). Here these processes were studied by a word learning paradigm, cutting across the domains of memory and language learning studies. Moreover, the differentiation between normal aging, mild cognitive impairment (MCI) and AD was studied by the cognitive screening test CERAD. In study I, the aim was to examine how patients with amnestic MCI differ from healthy controls in the different CERAD subtests. Also, the sensitivity and specificity of the CERAD screening test to MCI and AD was examined, as previous studies on the sensitivity and specificity of the CERAD have not included MCI patients. The results indicated that MCI is characterized by an encoding deficit, as shown by the overall worse performance on the CERAD Wordlist learning test compared with controls. As a screening test, CERAD was not very sensitive to MCI. In study II, verbal learning and forgetting in amnestic MCI, AD and healthy elderly controls was investigated with an experimental word learning paradigm, where names of 40 unfamiliar objects (mainly archaic tools) were trained with or without semantic support. The object names were trained during a 4-day long period and a follow-up was conducted one week, 4 weeks and 8 weeks after the training period. Manipulation of semantic support was included in the paradigm because it was hypothesized that semantic support might have some beneficial effects in the present learning task especially for the MCI group, as semantic memory is quite well preserved in MCI in contrast to episodic memory. We found that word learning was significantly impaired in MCI and AD patients, whereas forgetting patterns were similar across groups. Semantic support showed a beneficial effect on object name retrieval in the MCI group 8 weeks after training, indicating that the MCI patients’ preserved semantic memory abilities compensated for their impaired episodic memory. The MCI group performed equally well as the controls in the tasks tapping incidental learning and recognition memory, whereas the AD group showed impairment. Both the MCI and the AD group benefited less from phonological cueing than the controls. Our findings indicate that acquisition is compromised in both MCI and AD, whereas long13 term retention is not affected to the same extent. Incidental learning and recognition memory seem to be well preserved in MCI. In studies III and IV, the neural correlates of naming newly learned objects were examined in healthy elderly subjects and in amnestic MCI patients by means of positron emission tomography (PET) right after the training period. The naming of newly learned objects by healthy elderly subjects recruited a left-lateralized network, including frontotemporal regions and the cerebellum, which was more extensive than the one related to the naming of familiar objects (study III). Semantic support showed no effects on the PET results for the healthy subjects. The observed activation increases may reflect lexicalsemantic and lexical-phonological retrieval, as well as more general associative memory mechanisms. In study IV, compared to the controls, the MCI patients showed increased anterior cingulate activation when naming newly learned objects that had been learned without semantic support. This suggests a recruitment of additional executive and attentional resources in the MCI group.

Determinação do tamanho ótimo da parcela experimental pelos métodos da máxima curvatura modificado, do coeficiente de correlação intraclasse e da análise visual em testes clonais de eucalipto

O objetivo deste trabalho foi determinar o tamanho ótimo da parcela experimental em testes clonais de eucalipto, por meio dos métodos da máxima curvatura modificado, do coeficiente de correlação intraclasse e da análise visual, com base nas características de crescimento em altura, dap e volume. A partir de quatro testes clonais, dispostos no delineamento em blocos ao acaso, com quatro repetições e parcela experimental quadrada de 25 plantas (5 x 5), foram simulados diferentes tamanhos de parcela com 2, 3, 4, 5, 9, 10, 15, 20 e 25 plantas, visando determinar o tamanho ótimo da parcela pelos métodos de máxima curvatura modificado, do coeficiente de correlação intraclasse e da análise visual. Pôde-se concluir que em programas iniciais para seleção de clones parcelas de cinco a dez plantas proporcionam boa precisão experimental, sendo recomendadas, principalmente, em situação com limitações de mudas, teste de grande número de clones e avaliações de cunho preliminar e em idades precoces.

Mild Cognitive Impairment and Early Detection of Alzheimer`s Disease. A Positron Emission Tomography Study

Alzheimer`s disease (AD) is characterised neuropathologically by the presence of extracellular amyloid plaques, intraneuronal neurofibrillary tangles, and cerebral neuronal loss. The pathological changes in AD are believed to start even decades before clinical symptoms are detectable. AD gradually affects episodic memory, cognition, behaviour and the ability to perform everyday activities. Mild cognitive impairment (MCI) represents a transitional state between normal aging and dementia disorders, especially AD. The predictive accuracy of the current and commonly used MCI criteria devide this disorder into amnestic (aMCI) and non-amnestic (naMCI) MCI. It seems that many individuals with aMCI tend to convert to AD. However many MCI individuals will remain stable and some may even recover. At present, the principal drugs for the treatment of AD provide only symptomatic and palliative benefits. Safe and effective mechanism-based therapies are needed for this devastating neurodegenerative disease of later life. In conjunction with the development of new therapeutic drugs, tools for early detection of AD would be important. In future one of the challenges will be to detect at an early stage these MCI individuals who will convert to AD. Methods which can predict which MCI subjects will convert to AD will be much more important if the new drug candidates prove to have disease-arresting or even disease–slowing effects. These types of drugs are likely to have the best efficacy if administered in the early or even in the presymptomatic phase of the disease when the synaptic and neuronal loss has not become too widespread. There is no clinical method to determine with certainly which MCI individuals will progress to AD. However there are several methods which have been suggested as predictors of conversion to AD, e.g. increased [11C] PIB uptake, hippocampal atrophy in MRI, low CSF A beta 42 level, high CSF tau-protein level, apolipoprotein E (APOE) ε4 allele and impairment in episodic memory and executive functions. In the present study subjects with MCI appear to have significantly higher [¹¹C] PIB uptake vs healthy elderly in several brain areas including frontal cortex, the posterior cingulate, the parietal and lateral temporal cortices, putamen and caudate. Also results from this PET study indicate that over time, MCI subjects who display increased [¹¹C] PIB uptake appear to be significantly more likely to convert to AD than MCI subjects with negative [¹¹C] PIB retention. Also hippocampal atrophy seems to increase in MCI individuals clearly during the conversion to AD. In this study [¹¹C] PIB uptake increases early and changes relatively little during the AD process whereas there is progressive hippocampal atrophy during the disease. In addition to increased [¹¹C] PIB retention and hippocampal atrophy, the status of APOE ε4 allele might contribute to the conversion from MCI to AD.

Propriedades mecânicas de peças com dimensões estruturais de Pinus spp: correlação entre resistência à tração e classificação visual

A redução da disponibilidade de espécies de madeiras nativas e seus efeitos na economia, associada ao fortalecimento dos conceitos de preservação ambiental, criou a necessidade de desenvolvimento de alternativas viáveis para utilização racional de espécies de reflorestamento. E uma das opções é a realização de classificação visual das peças. Autores de trabalhos desenvolvidos nessa linha de pesquisa verificaram a adequação das regras de classificação visual do Southern Pine Inspection Bureau (SPIB) dos EUA à madeira de Pinus do Brasil e apresentaram proposta para normalizar o processo de classificação visual dessa madeira. Nessa classificação, os aspectos com maior influência são: presença de nós, desvio de grã em relação ao eixo da peça e densidade de anéis de crescimento. Assim, esta pesquisa apresenta um estudo experimental que consistiu na classificação visual e determinação da resistência à tração de 85 peças de Pinus spp e um estudo teórico, que propôs uma equação para determinar a resistência à tração média de peças estruturais em função da classificação visual. Com este trabalho, foi possível observar a influência dos nós e dos anéis de crescimento sobre a resistência à tração das peças analisadas.

PET and MR imaging in Parkinson’s disease patients with cognitive impairment. A study of dopaminergic dysfunction, amyloid deposition, cortical hypometabolism and brain atrophy

Parkinson’s disease (PD) is the second most common neurodegenerative disorder. It is characterized by a severe loss of substantia nigra dopaminergic neurons leading to dopamine depletion in the striatum. PD affects movement, producing motor symptoms such as rigidity, tremor and bradykinesia. Non-motor symptoms include autonomic dysfunction, neurobehavioral problems and cognitive impairment, which may lead to dementia. The pathophysiological basis of cognitive impairment and dementia in PD is unclear. The aim of this thesis was to study the pathophysiological basis of cognitive impairment and dementia in PD. We evaluated the relation between frontostriatal dopaminergic dysfunction and the cognitive symptoms in PD patients with [18F]Fdopa PET. We also combined [C]PIB and [¹⁸F]FDG PET and magnetic resonance imaging in PD patients with and without dementia. In addition, we analysed subregional striatal [¹⁸F]Fdopa PET data to find out whether a simple ratio approach would reliably separate PD patients from healthy controls. The impaired dopaminergic function of the frontostriatal regions was related to the impairment in cognitive functions, such as memory and cognitive processing in PD patients. PD patients with dementia showed an impaired glucose metabolism but not amyloid deposition in the cortical brain regions, and the hypometabolism was associated with the degree of cognitive impairment. PD patients had atrophy, both in the prefrontal cortex and in the hippocampus, and the hippocampal atrophy was related to impaired memory. A single 15-min scan 75 min after a tracer injection seemed to be sufficient for separating patients with PD from healthy controls in a clinical research environment. In conclusion, the occurrence of cognitive impairment and dementia in PD seems to be multifactorial and relates to changes, such as reduced dopaminergic activity, hypometabolism, brain atrophy and rarely to amyloid accumulation.

Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.

Alteração do campo visual em função do uso de cabinas em tratores agrícolas

Com o objetivo de avaliar a alteração do campo visual de um trator, ocasionada pela instalação de uma cabina, foram determinadas as áreas de visibilidade nula em função da presença ou não da mesma, para cada campo visual. Os procedimentos adotados basearam-se na norma ISO 5721-1981 - Agricultural tractors - Operator's field of vision. A cabina aumentou em 34,42% a área de visibilidade nula. A relação área de projeção do trator/área total sombreada foi de 0,075 para o trator sem cabina, e 0,057 para o trator com cabina, indicando as melhores condições de visibilidade do primeiro em relação ao segundo. No que se refere aos campos visuais, a maior redução ocorreu no campo visual dos olhos e no obtido com o movimento da cabeça, em função dos suportes da cabina e da estrutura de proteção contra o capotamento. A cabina diminui o campo de visão do operador, e adequações no projeto da estrutura avaliada são necessárias para melhorar as condições de visibilidade.

Genetically Determined Hypometabolism in Alzheimer’s Disease and Midlife Risk Factors for Cognitive Impairment

The role of genetic factors in the pathogenesis of Alzheimer’s disease (AD) is not completely understood. In order to improve this understanding, the cerebral glucose metabolism of seven monozygotic and nine dizygotic twin pairs discordant for AD was compared to that of 13 unrelated controls using positron emission tomography (PET). Traditional region of interest analysis revealed no differences between the non-demented dizygotic co-twins and controls. In contrast, in voxel-level and automated region of interest analyses, the non-demented monozygotic co-twins displayed a lower metabolic rate in temporal and parietal cortices as well as in subcortical grey matter structures when compared to controls. Again, no reductions were seen in the non-demented dizygotic co-twins. The reductions seen in the non-demented monozygotic co-twins may indicate a higher genetically mediated risk of AD or genetically mediated hypometabolism possibly rendering them more vulnerable to AD pathogenesis. With no disease modifying treatment available for AD, prevention of dementia is of the utmost importance. A total of 2 165 at least 65 years old twins of the Finnish Twin Cohort with questionnaire data from 1981 participated in a validated telephone interview assessing cognitive function between 1999 and 2007. Those subjects reporting heavy alcohol drinking in 1981 had an elevated cognitive impairment risk over 20 years later compared to light drinkers. In addition, binge drinking was associated with an increased risk even when total alcohol consumption was controlled for, suggesting that binge drinking is an independent risk factor for cognitive impairment. When compared to light drinkers, also non-drinkers had an increased risk of cognitive impairment. Midlife hypertension, obesity and low leisure time physical activity but not hypercholesterolemia were significant risk factors for cognitive impairment. The accumulation of risk factors increased cognitive impairment risk in an additive manner. A previously postulated dementia risk score based on midlife demographic and cardiovascular factors was validated. The risk score was found to well predict cognitive impairment risk, and cognitive impairment risk increased significantly as the score became higher. However, the risk score is not accurate enough for use in the clinic without further testing.