Image processing technologies are broadly applied on modern machine vision and industrial inspection , but there is usually a trade-off between accuracy and speed of inspection . We plan to solve the plight by two steps : 1.We will develop many major image processing methods such as image boundary¡Bto remove the noise¡Bpattern match , and so on . 2.We will focus on sub-pixel algorithm and boundary research to improve the image accuracy and processing time by software under limited hardware . As we know , pixel is the most basic element of an image , but we can divide one pixel into several smaller parts by mathematics ; in the meanwhile , the pixel accuracy can be improved . We will use algorithm to realize the goal in continuous way , and research on the flow of image recognition to find out a best flow for any specific image properties .

The CCD sensors have the advantage for small size clear image and low prices, It is the image capture unit of computer-vision system which developed fast in the past years, especially in the 2-D image capture CCD sensors are better then another sensors, so in the industry it be used on products detection . There are two different sections on using CCD sensors to detect products,the first section is about the detection of what kind of objects amount of objects and position of objects, the second section is about looking for lines ¡Bcircles ¡Bareas of objects¡Bdiameter¡Bcircularity and the angles between two lines The research purpose is finding a high accuracy algorithmic with low complicacy and high accuracy conditions; the accuracy can reach the sub-pixel accuracy with low price facilities and high speed .

One of the basic problems in computer vision is motion detection and analysis in a given scene. This work focuses on detecting small changes in the image by using the moiré phenomenon. The main goal of this thesis is to detect different types of dislocations with algorithms used in computer vision. In this work synthetically created pictures are analysed, which were created with the mathematical model of a pinhole camera.

É apresentado o desenvolvimento de um modelo computacional que visa relacionar imagens digitais obtidas em diferentes escalas e resoluções com aplicação de Wavelets. Seu desenvolvimento encontra-se no contexto multidisciplinar e situa-se na intersecção das linhas de pesquisa de áreas da Física, da Matemática e da Computação. Desta forma, optou-se na implementação por uma abordagem computacional dos estudos, com aplicação em imagens digitais provenientes da reconstrução de dados de tomografia computadorizada de Raios-X. Resultados indicam que a implementação do modelo computacional desenvolvido tem sua funcionalidade comprovada, uma vez que os atributos vetoriais dos objetos considerados para análise (poros) foram mantidos estáveis em diferentes resoluções estudadas. O modelo foi implementado em linguagem de programação C++ com uso de orientação a objetos e organizado em classes. Adicionalmente, sua aplicação é viabilizada para diversas plataformas computacionais no que tange a sistemas operacionais e processadores. Do ponto de vista científico, o sistema resultante, além de ser uma ferramenta importante no estudo de meios porosos através de imagens de tomografia computadorizada por Raios-X, contribui com métodos inovadores que fazem uso de Wavelets e são aplicados na suavização de bordas por técnica sub-pixel, na otimização de desempenho e no processamento de dados para interpolação / This work consists of the development of a computational model aimed at relating digital images obtained on different scales and resolutions to the application of Wavelets. The development of this model lies within a multidisciplinary context, at the intersection of the research lines of areas of Physics, Mathematics and Computation. The choice of these studies therefore fel1 on a computational approach, with the application of digital images originating from the reconstruction of computerized tomographic X-ray data. The results of the implementation of the computational model developed here confirm the model\'s functionality, since the vectorial attributes of the objects utilized for our analysis (pores) remained stable under different resolutions. The model was implemented in the C++ programming language using object orientation, and the model\'s methods were organized into classes based on their application on different computational platforms, from the standpoint of operational systems and processors. In the scientific point of view, the resulting system is an important tool in the porous means researches using computerized tomography by X-rays and it has exclusive methods. These methods use Wavelets and they have application in edge smoothing processes by sub-pixel technique, in optimizing processing time and in data processing for interpolation

É apresentado o desenvolvimento de um modelo computacional que visa relacionar imagens digitais obtidas em diferentes escalas e resoluções com aplicação de Wavelets. Seu desenvolvimento encontra-se no contexto multidisciplinar e situa-se na intersecção das linhas de pesquisa de áreas da Física, da Matemática e da Computação. Desta forma, optou-se na implementação por uma abordagem computacional dos estudos, com aplicação em imagens digitais provenientes da reconstrução de dados de tomografia computadorizada de Raios-X. Resultados indicam que a implementação do modelo computacional desenvolvido tem sua funcionalidade comprovada, uma vez que os atributos vetoriais dos objetos considerados para análise (poros) foram mantidos estáveis em diferentes resoluções estudadas. O modelo foi implementado em linguagem de programação C++ com uso de orientação a objetos e organizado em classes. Adicionalmente, sua aplicação é viabilizada para diversas plataformas computacionais no que tange a sistemas operacionais e processadores. Do ponto de vista científico, o sistema resultante, além de ser uma ferramenta importante no estudo de meios porosos através de imagens de tomografia computadorizada por Raios-X, contribui com métodos inovadores que fazem uso de Wavelets e são aplicados na suavização de bordas por técnica sub-pixel, na otimização de desempenho e no processamento de dados para interpolação / This work consists of the development of a computational model aimed at relating digital images obtained on different scales and resolutions to the application of Wavelets. The development of this model lies within a multidisciplinary context, at the intersection of the research lines of areas of Physics, Mathematics and Computation. The choice of these studies therefore fel1 on a computational approach, with the application of digital images originating from the reconstruction of computerized tomographic X-ray data. The results of the implementation of the computational model developed here confirm the model\'s functionality, since the vectorial attributes of the objects utilized for our analysis (pores) remained stable under different resolutions. The model was implemented in the C++ programming language using object orientation, and the model\'s methods were organized into classes based on their application on different computational platforms, from the standpoint of operational systems and processors. In the scientific point of view, the resulting system is an important tool in the porous means researches using computerized tomography by X-rays and it has exclusive methods. These methods use Wavelets and they have application in edge smoothing processes by sub-pixel technique, in optimizing processing time and in data processing for interpolation

In this effort a new measurement technique for the lateral Goos-Hanchen shift is developed, analyzed, and demonstrated. The new technique uses classical image formation methods fused with modern detection and analysis methods to achieve higher levels of sensitivity than obtained with prior practice. Central to the effort is a new mathematical model of the dispersion seen at a step shadow when the Goos-Hanchen effect occurs near critical angle for total internal reflection. Image processing techniques are applied to measure the intensity distribution transfer function of a new divergence model of the Goos-Hanchen phenomena providing verification of the model. This effort includes mathematical modeling techniques, analytical derivations of governing equations, numerical verification of models and sensitivities, optical design of apparatus, image processing

The performance of a dedicated A/D converter located beneath each pixel is explored in this thesis. Specifically, a voltage to frequency converter coupled with a direct injection amplifier designed for use with an IR focal plane array is analyzed. This versatile implementation of a Readout Integrated Circuit can be found applicable to a wide variety of imaging technologies. Noise performance of the conversion system is theoretically calculated, and is supported by SPICE simulations using valid CMOS SPICE models. It is shown that a 10 transistor sub-pixel voltage to frequency analog to digital converter will produce noise that is less than the input shot noise. Design considerations will be addressed to ensure continued performance as the scale of the imagers increase to large format arrays.

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2006. / Submitted by Rosane Cossich Furtado (rosanecossich@gmail.com) on 2010-01-04T17:28:57Z No. of bitstreams: 1 Dissertacao Rafael Esteves 091.pdf: 4853118 bytes, checksum: a451b3bbd996a0991f9b20fad61bf3b1 (MD5) / Approved for entry into archive by Carolina Campos(carolinacamposmaia@gmail.com) on 2010-01-05T17:53:53Z (GMT) No. of bitstreams: 1 Dissertacao Rafael Esteves 091.pdf: 4853118 bytes, checksum: a451b3bbd996a0991f9b20fad61bf3b1 (MD5) / Made available in DSpace on 2010-01-05T17:53:53Z (GMT). No. of bitstreams: 1 Dissertacao Rafael Esteves 091.pdf: 4853118 bytes, checksum: a451b3bbd996a0991f9b20fad61bf3b1 (MD5) Previous issue date: 2006-02-02 / O crescimento descontrolado das superfícies impermeáveis em áreas urbanas tem conseqüências diretas na quantidade e qualidade do escoamento pluvial. O conhecimento da impermeabilidade do solo das bacias hidrográficas possibilita sua utilização como indicador da qualidade das águas urbanas e como instrumento de planejamento e regulação no sistema de gerenciamento dos recursos hídricos urbanos. Além disso, os estudos hidrológicos necessitam de parâmetros, dentre os quais a porcentagem de área impermeável talvez seja um dos mais importantes. A difusão das técnicas de Sensoriamento Remoto e seu grande potencial motivaram a realização dessa pesquisa, a fim de buscar métodos mais eficientes de estimação da impermeabilidade do solo de bacias hidrográficas. Foram utilizados três diferentes algoritmos de classificação de imagens de satélite para calcular a impermeabilidade de áreas de controle localizadas no Plano Piloto de Brasília- DF. Os algoritmos foram o Modelo Linear de Mistura, já disponível no software SPRING versão 4.1, o classificador Fuzzy com função de pertinência baseada na distância de Mahalanobis e o classificador tradicional MaxVer. Estes dois últimos foram implementados computacionalmente em linguagem JAVA no software Image J. Os algoritmos foram avaliados com imagens digitais de diferentes resoluções espaciais: IKONOS, SPOT, CBERS e LANDSAT. Para efeito de comparação, as áreas impermeáveis foram digitalizadas manualmente na imagem IKONOS e validadas com visitas a campo. Os valores de impermeabilidade assim estimados foram considerados a verdade de campo. Os resultados mostraram que os melhores desempenhos foram obtidos pelo Modelo de Mistura e pelo classificador Fuzzy, que obtiveram erros médios de 21,2% e 23,7%, respectivamente. O classificador MaxVer obteve um erro médio maior, de 31,8%. O Modelo de Mistura apresentou algumas deficiências, como a superestimação das áreas da classe sombra, tendência de subestimar as áreas impermeáveis e tempo de processamento computacional muito alto. A influência da resolução espacial das imagens foi importante apenas para o classificador Maxver. _______________________________________________________________________________ ABSTRACT / Impervious surface coverage growth has direct consequences in quantity and quality of stormwater runoff, such as floods and nonpoint source pollution. The quantification of basins’ imperviousness makes possible to use it as a water quality indicator for urban areas and as an important planning and managing instrument in the urban water resources management system. Furthermore, hydrologic studies need parameters, among which impervious surface percentage may be one of the most important. The diffusion of Remote Sensing techniques and their great potential motivated this research, in order to find more efficient methods for estimating impervious surface coverage in basins. Three different algorithms were used to classify satellite images and to calculate imperviousness in control areas located in the city of Brasilia-DF, Brazil. The algorithms used were the Linear Mixture Model, available in software SPRING version 4.1, the Fuzzy classifier with membership function based on Mahalanobis distance, and the traditional Maximum Likelihood classifier (MaxVer). The last two were implemented in JAVA software language as a plugin for the software Image J. The three algorithms were tested with different spatial resolution digital imageries: IKONOS, with 1 meter; SPOT, with 10 meters; CBERS, with 20 meters, and LANDSAT, with 30 meters. To compare with the reality, impervious surfaces were manually digitized over IKONOS imagery and validated with field visits, so that the imperviousness obtained was considered the ground truth. Results showed that best performances were obtained by Linear Mixture Model and by Fuzzy classifier, which had mean errors of 21,2% and 23,7%, respectively. MaxVer classifier obtained greater mean error of 31,8%. Linear Mixture Model, however, showed some deficiencies, such as high values for shadow classes, tendency to underestimate impervious surfaces, and very high computer processing times. The influence of spatial resolution was important only to the MaxVer classifier.

In computational imaging, data acquired by sampling the same scene or object at different times or from different orientations result in images in different coordinate systems. Registration is a crucial step in order to be able to compare, integrate and fuse the data obtained from different measurements. Tomography is the method of imaging a single plane or slice of an object. A Computed Tomography (CT) scan, also known as a CAT scan (Computed Axial Tomography scan), is a Helical Tomography, which traditionally produces a 2D image of the structures in a thin section of the body. It uses X-ray, which is ionizing radiation. Although the actual dose is typically low, repeated scans should be limited. In dentistry, implant dentistry in specific, there is a need for 3D visualization of internal anatomy. The internal visualization is mainly based on CT scanning technologies. The most important technological advancement which dramatically enhanced the clinician's ability to diagnose, treat, and plan dental implants has been the CT scan. Advanced 3D modeling and visualization techniques permit highly refined and accurate assessment of the CT scan data. However, in addition to imperfections of the instrument and the imaging process, it is not uncommon to encounter other unwanted artifacts in the form of bright regions, flares and erroneous pixels due to dental bridges, metal braces, etc. Currently, removing and cleaning up the data from acquisition backscattering imperfections and unwanted artifacts is performed manually, which is as good as the experience level of the technician. On the other hand the process is error prone, since the editing process needs to be performed image by image. We address some of these issues by proposing novel registration methods and using stonecast models of patient's dental imprint as reference ground truth data. Stone-cast models were originally used by dentists to make complete or partial dentures. The CT scan of such stone-cast models can be used to automatically guide the cleaning of patients' CT scans from defects or unwanted artifacts, and also as an automatic segmentation system for the outliers of the CT scan data without use of stone-cast models. Segmented data is subsequently used to clean the data from artifacts using a new proposed 3D inpainting approach.

This case study used Zhongwei City in northwest China to quantify the urbanization and revegetation processes (1990-2011) through a unified sub-pixel measure of vegetation cover. Research strategies included: (1) Conduct sub-pixel vegetation mapping (1990, 1996, 2004, and 2011) with Random Forest (RF) algorithm by integrating high (OrbView-3) and medium spatial resolution (Landsat TM) data; (2) Examine simple Dark Object Subtraction (DOS) atmospheric correction method to support temporal generalization of sub-pixel mapping algorithm; (3) And characterize patterns of vegetation cover dynamics based on change detection analysis. We found the RF algorithm, combined with simple DOS, showed good generalization capability for sub-pixel vegetation mapping. Predicted sub-pixel vegetation proportions were consistent for "pseudo-invariant" pixels. Vegetation change analysis suggested persistent urban development within the city boundary, accompanied by a continuous expansion of revegetated area at the city fringe. Urban development occurred at both the suburban and urban core areas, and was mainly shaped by transportation networks. A transition in revegetation practices was documented: the large-scale governmental revegetation programs were replaced by the commercial afforestation conducted by industries. This study showed a slight increase in vegetation cover over the time period, balanced by losses to urban expansion, and a likely severe degradation of vegetation cover due to conversion of arable land to desert vegetation. The loss of arable land and the growth of artificial desert vegetation have yielded a dynamic equilibrium in terms of overall vegetation cover during 1990 to 2011, but in the long run vegetation quality is certainly reduced. / Master of Science