Minimum Mean Square Error Approach in Images Processing for Full-field Displacements and Deformation Measurements

A vision system is applied to full-field displacements and deformation measurements in solid mechanics. A speckle like pattern is preliminary formed on the surface under investigation. To determine displacements field of one speckle image with respect to a reference speckle image, sub-images, referred to Zones Of Interest (ZOI) are considered. The field is obtained by matching a ZOI in the reference image with the respective ZOI in the moved image. Two image processing techniques are used for implementing the matching procedure: – cross correlation function and minimum mean square error (MMSE) of the ZOI intensity distribution. The two algorithms are compared and the influence of the ZOI size on the accuracy of measurements is studied.

An automatic correction method for the heel effect in digitized mammography images

The most significant radiation field nonuniformity is the well-known Heel effect. This nonuniform beam effect has a negative influence on the results of computer-aided diagnosis of mammograms, which is frequently used for early cancer detection. This paper presents a method to correct all pixels in the mammography image according to the excess or lack on radiation to which these have been submitted as a result of the this effect. The current simulation method calculates the intensities at all points of the image plane. In the simulated image, the percentage of radiation received by all the points takes the center of the field as reference. In the digitized mammography, the percentages of the optical density of all the pixels of the analyzed image are also calculated. The Heel effect causes a Gaussian distribution around the anode-cathode axis and a logarithmic distribution parallel to this axis. Those characteristic distributions are used to determine the center of the radiation field as well as the cathode-anode axis, allowing for the automatic determination of the correlation between these two sets of data. The measurements obtained with our proposed method differs on average by 2.49 mm in the direction perpendicular to the anode-cathode axis and 2.02 mm parallel to the anode-cathode axis of commercial equipment. The method eliminates around 94% of the Heel effect in the radiological image and the objects will reflect their x-ray absorption. To evaluate this method, experimental data was taken from known objects, but could also be done with clinical and digital images.

Extraction of subjective properties in image processing

Most of the present digital images processing methods are related with objective characterization of external properties as shape, form or colour. This information concerns objective characteristics of different bodies and is applied to extract details to perform several different tasks. But in some occasions, some other type of information is needed. This is the case when the image processing system is going to be applied to some operation related with living bodies. In this case, some other type of object information may be useful. As a matter of fact, it may give additional knowledge about its subjective properties. Some of these properties are object symmetry, parallelism between lines and the feeling of size. These types of properties concerns more to internal sensations of living beings when they are related with their environment than to the objective information obtained by artificial systems. This paper presents an elemental system able to detect some of the above-mentioned parameters. A first mathematical model to analyze these situations is reported. This theoretical model will give the possibility to implement a simple working system. The basis of this system is the use of optical logic cells, previously employed in optical computing.

Hough Transform Approach to Identification of Flare Stars in Multi-exposure Plate Images

ACM Computing Classification System (1998): I.2.8 , I.2.10, I.5.1, J.2.

O âmbito de aplicação material da legislação de proteção de dados pessoais e o tratamento de imagem por pessoa singular

Images have gained a never before seen importance. Technological changes have given the Information Society extraordinary means to capture, treat and transmit images, wheter your own or those of others, with or without a commercial purpose, with no boundaries of time or country, without “any kind of eraser”. From the several different ways natural persons may engage in image processing with no commercial purpose, the cases of sharing pictures through social networks and video surveillance assume particular relevance. Consequently there are growing legitimate concerns with the protection of one's image, since its processing may sometimes generate situations of privacy invasion or put at risk other fundamental rights. With this in mind, the present thesis arises from the question: what are the existent legal instruments in Portuguese Law that enable citizens to protect themselves from the abusive usage of their own pictures, whether because that image have been captured by a smartphone or some video surveillance camera, whether because it was massively shared through a blog or some social network? There is no question the one's right to not having his or her image used in an abusive way is protected by the Portuguese constitution, through the article 26th CRP, as well as personally right, under the article 79th of the Civil Code, and finally through criminal law, articles 192nd and 193rd of the Criminal Code. The question arises in the personal data protection context, considering that one's picture, given certain conditions, is personal data. Both the Directive 95/46/CE dated from 1995 as well as the LPD from 1998 are applicable to the processing of personal data, but both exclude situations of natural persons doing so in the pursuit of activities strictly personal or family-related. These laws demand complex procedures to natural persons, such as the preemptive formal authorisation request to the Data Protection National Commission. Failing to do so a natural person may result in the application of fines as high as €2.500,00 or even criminal charges. Consequently, the present thesis aims to study if the image processing with no commercial purposes by a natural person in the context of social networks or through video surveillance belongs to the domain of the existent personal data protection law. To that effect, it was made general considerations regarding the concept of video surveillance, what is its regimen, in a way that it may be distinguishable from Steve Mann's definition of sousveillance, and what are the associated obligations in order to better understand the concept's essence. The application of the existent laws on personal data protection to images processing by natural persons has been analysed taking into account the Directive 95/46/CE, the LPD and the General Regulation. From this analysis it is concluded that the regimen from 1995 to 1998 is out of touch with reality creating an absence of legal shielding in the personal data protection law, a flaw that doesn't exist because compensated by the right to image as a right to personality, that anyway reveals the inability of the Portuguese legislator to face the new technological challenges. It is urgent to legislate. A contrary interpretation will evidence the unconstitutionality of several rules on the LPD due to the obligations natural persons are bound to that violate the right to the freedom of speech and information, which would be inadequate and disproportionate. Considering the recently approved General Regulation and in the case it becomes the final version, the use for natural person of video surveillance of private spaces, Google Glass (in public and private places) and other similar gadgets used to recreational purposes, as well as social networks are subject to its regulation only if the images are shared without limits or existing commercial purposes. Video surveillance of public spaces in all situations is subject to General Regulation provisions.

MACHINE VISION FOR AUTOMATICVISUAL INSPECTION OF WOODENRAILWAY SLEEPERS USING UNSUPERVISED NEURAL NETWORKS

The motivation for this thesis work is the need for improving reliability of equipment and quality of service to railway passengers as well as a requirement for cost-effective and efficient condition maintenance management for rail transportation. This thesis work develops a fusion of various machine vision analysis methods to achieve high performance in automation of wooden rail track inspection.The condition monitoring in rail transport is done manually by a human operator where people rely on inference systems and assumptions to develop conclusions. The use of conditional monitoring allows maintenance to be scheduled, or other actions to be taken to avoid the consequences of failure, before the failure occurs. Manual or automated condition monitoring of materials in fields of public transportation like railway, aerial navigation, traffic safety, etc, where safety is of prior importance needs non-destructive testing (NDT).In general, wooden railway sleeper inspection is done manually by a human operator, by moving along the rail sleeper and gathering information by visual and sound analysis for examining the presence of cracks. Human inspectors working on lines visually inspect wooden rails to judge the quality of rail sleeper. In this project work the machine vision system is developed based on the manual visual analysis system, which uses digital cameras and image processing software to perform similar manual inspections. As the manual inspection requires much effort and is expected to be error prone sometimes and also appears difficult to discriminate even for a human operator by the frequent changes in inspected material. The machine vision system developed classifies the condition of material by examining individual pixels of images, processing them and attempting to develop conclusions with the assistance of knowledge bases and features.A pattern recognition approach is developed based on the methodological knowledge from manual procedure. The pattern recognition approach for this thesis work was developed and achieved by a non destructive testing method to identify the flaws in manually done condition monitoring of sleepers.In this method, a test vehicle is designed to capture sleeper images similar to visual inspection by human operator and the raw data for pattern recognition approach is provided from the captured images of the wooden sleepers. The data from the NDT method were further processed and appropriate features were extracted.The collection of data by the NDT method is to achieve high accuracy in reliable classification results. A key idea is to use the non supervised classifier based on the features extracted from the method to discriminate the condition of wooden sleepers in to either good or bad. Self organising map is used as classifier for the wooden sleeper classification.In order to achieve greater integration, the data collected by the machine vision system was made to interface with one another by a strategy called fusion. Data fusion was looked in at two different levels namely sensor-level fusion, feature- level fusion. As the goal was to reduce the accuracy of the human error on the rail sleeper classification as good or bad the results obtained by the feature-level fusion compared to that of the results of actual classification were satisfactory.

Dinâmica da paisagem no litoral oriental do Rio Grande do Norte: geocartografia e padrões espaciais dos campos de dunas móveis

This study shows the results of a research developed in the coastal regions of the Maxaranguape and Touros municipalities, more specific in the mobile dune fields of the Rio Grande do Norte's eastern coast. Although the coastal zones, represent a small percentage of the earth's surface it concentrates a great part of the world's population. The Rio Grande do Norte's state coastal landscape mosaic composed by the dune fields suggest a dynamic scene of changes in the spatial and temporal arranges, with significant changes in the geometry of the sedimentary cover. Following this perspective this research has the objective to map the emerged coastal zone of the Rio Grande do Norte's eastern coast under the perspective of the time-space evolution of the mobile dune fields using geoprocessing techniques, which includes remote sensing, digital images processing and geographic information system (GIS). The results imply the issue of thematic maps: Geologic map; multitemporal evolution map of the mobile dune fields; quantification of the mobile dune fields differences map; temporal evolution of the mobile dune fields surrounds map. The El Niño episodes have directly affected the atmospheric circulation, what have enhanced the sedimentary input in the sand dune, what can justify the relative area growth between the years of 1993 and 2001. The dynamic of the landscape transition were higher than the stability of the spatial pattern of the dune and it's surrounds, as a result the Rio Grande do Norte eastern coast dune fields, specially the mobile dunes from Touros, Zumbi and Maracajau have shown a decrease on the sedimentary cover without vegetation area from 1970 to 2007. Therefore, the data acquired and the techniques used, can be, eventually applied to the mobile dune fields monitoring in order to preserve the dune ecosystems in the Rio Grande do Norte coast

Implementação em FPGA de um sistema para processamento de imagens digitais para aplicações diversificadas

Pós-graduação em Ciência da Computação - IBILCE

Avaliação de parâmetros farmacêuticos em comprimidos matriciais empregando a técnica de Biosusceptometria AC

Oral administration is widely accepted route for drug delivery and solid dosage forms are commonly employed. The variation of absorption profiles along the human gastrointestinal tract (GIT) and the ability to target drugs by adequate dosage forms to distinct sites is the challenge in the pharmaceutical development of solid dosage forms. AC Biosusceptometry (ACB) is a technique that deserves consideration due to its features, accuracy of results and versatility. The purpose of this work was to evaluate, by employing the AC Biosusceptometer, the rate of swelling of systems matrices consisting of hydrophilic polymer (hydroxypropyl methyl cellulose) and magnetic material. Matrices tablets were evaluated in vitro to a more detailed analysis of kinetics of swelling, in addition to the study and application of mathematical models to correlate the magnetic area variation and the water uptake. All the procedures for qualitative and quantitative analysis of digital signals as well as the magnetic images processing were performed in MatLab® (Mathworks Inc.). ACB technique proved to be useful towards estimating the swelling properties of hydrophilic matrices in vitro, showing a promising capacity for further analyses involving dissolution test and in vivo studies, supporting their innovative potential pharmaceutical applications

Utilização de técnicas de geoprocessamento para monitoramento de atividades de mineração ao longo de dutos: poliduto Rio de Janeiro/Minas Gerais

The transportation of oil through polyducts implies a concern related to safety and environmental impacts they may cause, especially when exposed to risks that affect their integrity. Among the various anthropogenic activities included in this scenario, mining can aggravate, increase the risks and degrade the environment. Since these polyducts go through significant extensions, remote sensing has great applicability as a tool for data acquisition. For this, change detection techniques were used to monitor mining activities in a defined study area in the state of Rio de Janeiro, along the duct ORBEL. The characterization of the study area and the mining activities were developed through bibliographical data. The satellite images processing and the application of change detection technique were performed in two scenes for the years 2002 and 2010. The growth in the mining area was about 6.67 times and it was possible to identify types of extraction involved which can represent direct risks to the pipeline

Determinação de cenários futuros de uso e cobertura do solo e sua influência na vulnerabilidade ambiental : o caso do município de Formosa – GO

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, Programa de Pós-Graduação em Tecnologia Ambiental e Recursos Hídricos, 2015.

Processamento de imagem digital para o controlo de qualidade do queijo regional de Évora

A utilização generalizada do computador para a automatização das mais diversas tarefas, tem conduzido ao desenvolvimento de aplicações que possibilitam a realização de actividades que até então poderiam não só ser demoradas, como estar sujeitas a erros inerentes à actividade humana. A investigação desenvolvida no âmbito desta tese, tem como objectivo o desenvolvimento de um software e algoritmos que permitam a avaliação e classificação de queijos produzidos na região de Évora, através do processamento de imagens digitais. No decurso desta investigação, foram desenvolvidos algoritmos e metodologias que permitem a identificação dos olhos e dimensões do queijo, a presença de textura na parte exterior do queijo, assim como características relativas à cor do mesmo, permitindo que com base nestes parâmetros possa ser efectuada uma classificação e avaliação do queijo. A aplicação de software, resultou num produto de simples utilização. As fotografias devem respeitar algumas regras simples, sobre as quais se efectuará o processamento e classificação do queijo. ABSTRACT: The widespread use of computers for the automation of repetitive tasks, has resulted in developing applications that allow a range of activities, that until now could not only be time consuming and also subject to errors inherent to human activity, to be performed without or with little human intervention. The research carried out within this thesis, aims to develop a software application and algorithms that enable the assessment and classification of cheeses produced in the region of Évora, by digital images processing. Throughout this research, algorithms and methodologies have been developed that allow the identification of the cheese eyes, the dimensions of the cheese, the presence of texture on the outside of cheese, as well as an analysis of the color, so that, based on these parameters, a classification and evaluation of the cheese can be conducted. The developed software application, is product simple to use, requiring no special computer knowledge. Requires only the acquisition of the photographs following a simple set of rules, based on which it will do the processing and classification of cheese.

Análise da paisagem e das alterações de uso/ocupação do solo no Lubango e arredores

A cartografia temática surge como um aliado indispensável ao estudo e conhecimento do estado da paisagem e dos ecossistemas terrestres. Angola é um país com uma enorme lacuna em termos de informação cartográfica para suporte a diversas actividades desenvolvidas em várias áreas. É por isso necessária informação sobre a superfície terrestre que registe as alterações temporais ocorridas nos ecossistemas e identifique os factores que estão na sua origem de forma a implementar medidas que permitam uma gestão mais sustentável do seu enorme território. O presente estudo foi realizado no sector Sudoeste de Angola, abrangendo os municípios do Lubango, Humpata e Chibia, com uma área aproximada de 9600 km2. Os objectivos foram: a) cartografar o coberto do solo e monitorizar as alterações ocorridas na área de estudo no período 1990-2010, b) analisar e interpretar as alterações da estrutura da paisagem nos últimos 20 anos usando cartografia de ocupação do solo, produzida recorrendo a imagens de satélite, e métricas da paisagem, e c) quantificar e examinar a relação entre a fragmentação da paisagem e os factores geradores. A metodologia utilizada no estudo é composta por duas partes, sendo a primeira dedicada às operações de processamento e interpretação de imagens de satélite Landsat e, a segunda dedicada à produção de novas métricas de fragmentação da paisagem com recurso à ferramenta SIG utilizando operações de álgebra de mapas. O comportamento da fragmentação é analisado, à luz do efeito dos fatores ambientais e socioeconómicas ao nível da região. Os resultados obtidos, através da aplicação de técnicas de deteção remota e usando imagens Landsat TM e ETM+, permitiram a elaboração de mapas de coberto do solo, onde se distinguiram 8 classes temáticas e espectralmente diferentes. Verificou-se em termos globais que aproximadamente 38% da área sofreu algum tipo de alteração no período estudado, sendo as classes de miombo e áreas cultivadas as que mais alterações sofreram. A fragmentação da paisagem foi avaliada através da implementação de novas métricas, mostrando os resultados, que no período 1990-2000, a fragmentação foi superior à que se verificou entre 2000-2010. A nível espacial, a dinâmica de fragmentação foi mais acentuada, entre 1990-2000, na Humpata e, entre 2000-2010, no Lubango; ANALYSIS OF LANDSCAPE AND LAND USE LAND COVER CHANGE IN LUBANGO AND SURROUNDINGS ABSTRACT: Thematic cartography shows up as an essential ally in the study and knowledge of the state of landscapes and terrestrial ecosystems. Angola is a country with an enormous lack of cartographic information to support the several activities carried out in a variety of areas. This is the reason information on the earth’s surface is necessary, registering alterations which occur over time in ecosystems and identifying the associated factors in its origin, so as to implement metrics that allow a more sustainable management of its enormous territory. This study was carried out in the Southeast of Angola in the Lubango, Humpata and Chibia Municipalities, with an area of approximately 9600 km2. Our objectives were the following: a) land cover mapping and land cover changes monitoring over the period 1990 to 2010 using Landsat images, b) to analyze and interpret landscape structures changes using land cover maps, and landscapes metrics, and c) to quantify and to examine the relationship between landscape fragmentation and its drivers. The methodology developed in the study has two parts, the first includes Landsat satellite images processing and interpretation and, the second the production of new landscape fragmentation metrics with support to a GIS tool and algebraic mapping operations. The fragmentation behavior is analyzed, taking into account the effect of environmental and socioeconomic factors at a regional level. The results allowed obtaining land cover maps, in which 8 spectrally different thematic classes were distinguished. It was observed that 38% of the area suffered some type of alteration in the studied period, with higher changes observed in the classes of miombo and agriculture. Landscapes fragmentation results, evaluated through the implementation of new metrics, show that, values are greater in the period 1990-2000 than in 2000-2010. At municipality level, fragmentation dynamics were more accentuated in Humpata between 1990 -2000 and in Lubango between 2000 -2010.

Digital processing of diffusion-tensor images of avascular tissues

Diffusion is the process that leads to the mixing of substances as a result of spontaneous and random thermal motion of individual atoms and molecules. It was first detected by the English botanist Robert Brown in 1827, and the phenomenon became known as ‘Brownian motion’. More specifically, the motion observed by Brown was translational diffusion – thermal motion resulting in random variations of the position of a molecule. This type of motion was given a correct theoretical interpretation in 1905 by Albert Einstein, who derived the relationship between temperature, the viscosity of the medium, the size of the diffusing molecule, and its diffusion coefficient. It is translational diffusion that is indirectly observed in MR diffusion-tensor imaging (DTI). The relationship obtained by Einstein provides the physical basis for using translational diffusion to probe the microscopic environment surrounding the molecule.

Learning Nonlinear Visual Processing from Natural Images

The paradigm of computational vision hypothesizes that any visual function -- such as the recognition of your grandparent -- can be replicated by computational processing of the visual input. What are these computations that the brain performs? What should or could they be? Working on the latter question, this dissertation takes the statistical approach, where the suitable computations are attempted to be learned from the natural visual data itself. In particular, we empirically study the computational processing that emerges from the statistical properties of the visual world and the constraints and objectives specified for the learning process. This thesis consists of an introduction and 7 peer-reviewed publications, where the purpose of the introduction is to illustrate the area of study to a reader who is not familiar with computational vision research. In the scope of the introduction, we will briefly overview the primary challenges to visual processing, as well as recall some of the current opinions on visual processing in the early visual systems of animals. Next, we describe the methodology we have used in our research, and discuss the presented results. We have included some additional remarks, speculations and conclusions to this discussion that were not featured in the original publications. We present the following results in the publications of this thesis. First, we empirically demonstrate that luminance and contrast are strongly dependent in natural images, contradicting previous theories suggesting that luminance and contrast were processed separately in natural systems due to their independence in the visual data. Second, we show that simple cell -like receptive fields of the primary visual cortex can be learned in the nonlinear contrast domain by maximization of independence. Further, we provide first-time reports of the emergence of conjunctive (corner-detecting) and subtractive (opponent orientation) processing due to nonlinear projection pursuit with simple objective functions related to sparseness and response energy optimization. Then, we show that attempting to extract independent components of nonlinear histogram statistics of a biologically plausible representation leads to projection directions that appear to differentiate between visual contexts. Such processing might be applicable for priming, \ie the selection and tuning of later visual processing. We continue by showing that a different kind of thresholded low-frequency priming can be learned and used to make object detection faster with little loss in accuracy. Finally, we show that in a computational object detection setting, nonlinearly gain-controlled visual features of medium complexity can be acquired sequentially as images are encountered and discarded. We present two online algorithms to perform this feature selection, and propose the idea that for artificial systems, some processing mechanisms could be selectable from the environment without optimizing the mechanisms themselves. In summary, this thesis explores learning visual processing on several levels. The learning can be understood as interplay of input data, model structures, learning objectives, and estimation algorithms. The presented work adds to the growing body of evidence showing that statistical methods can be used to acquire intuitively meaningful visual processing mechanisms. The work also presents some predictions and ideas regarding biological visual processing.