Automated data acquisition has revolutionized the reliability of product design in recent years. A noteworthy example is the improvement in the design of aircrafts through field data. This research proposes a similar improvement in the reliability of process design of earthmoving operations through automated field data acquisition. The segment of earthmoving operations addressed in this research constitutes the truck-loader operation. Therefore, the applicability of this research extends to other industries involving truck-operation such as mining, agriculture and forest logging and is closely related to wheel-based earthmoving operations such as scrapers. The context of this research is defined by data collection needed to increase the validity of the results obtained by analysis tools such as simulation, performance measures and graphical representation of variance in an activity's performance, and the relation between operating conditions and the variance in an activity's performance. The automated cycle time data collection is facilitated by instrumented trucks and the collection of information on operating conditions is facilitated by image database and paper forms. The cycle time data and the information on operating conditions are linked together to form the experience database. This research developed methods to extract, quantify and understand the variation in each component of the earthmoving cycle namely, load, haul and return, and dump activities. For the load activity, the simultaneous variation in payload and load time is illustrated through the development of a PLT (PayLoad Time) Map. Among the operating conditions, material type, load area floor, space constraints and shift are investigated. A dynamic normalization process of determining the ratio of actual travel time to expected travel time is developed for the haul and return activities. The length of the haul road, sequence of gear downshifts and shift are investigated for their effect on the travel time. The discussion on the dump activity is presented in a qualitative form due to the lack of data. Each component is integrated within the framework of the experience database. The implementation aspects with respect to developing and using the experience database are also described in detail. The practical relevance of this study is highlighted using an example. / Ph. D.

Constantemente, uma variedade de novos métodos de processamento de imagens é apresentada à comunidade. Porém poucos têm provado sua utilidade na rotina clínica. A análise e comparação de diferentes abordagens por meio de uma mesma metodologia são essenciais para a qualificação do projeto de um algoritmo. Porém, é difícil comparar o desempenho e adequabilidade de diferentes algoritmos de uma mesma maneira. A principal razão deve-se à dificuldade para avaliar exaustivamente um software, ou pelo menos, testá-lo num conjunto abrangente e diversificado de casos clínicos. Muitas áreas - como o desenvolvimento de software e treinamentos em Medicina - necessitam de um conjunto diverso e abrangente de dados sobre imagens e informações associadas. Tais conjuntos podem ser utilizados para desenvolver, testar e avaliar novos softwares clínicos, utilizando dados públicos. Este trabalho propõe o desenvolvimento de um ambiente de base de imagens médicas de diferentes modalidades para uso livre em diferentes propósitos. Este ambiente - implementado como uma arquitetura de base distribuída de imagens - armazena imagens médicas com informações de aquisição, laudos, algoritmos de processamento de imagens, gold standards e imagens pós-processadas. O ambiente também possui um modelo de revisão de documentos que garante a qualidade dos conjuntos de dados. Como exemplo da facilidade e praticidade de uso, são apresentadas as avaliações de duas categorias de métodos de processamento de imagens médicas: segmentação e compressão. Em adição, a utilização do ambiente em outras atividades, como no projeto do arquivo didático digital do HC-FMUSP, demonstra a robustez da arquitetura proposta e sua aplicação em diferentes propósitos. / Constantly, a variety of new image processing methods are presented to the community. However, few of them have proved to be useful when used in clinical routine. The task of analyzing and comparing different algorithms, methods and applications through a sound testing is an essential qualification of algorithm design. However, it is usually very difficult to compare the performance and adequacy of different algorithms in the same way. The main reason is due to the difficulty to assess exhaustively the software, or at least using a comprehensive and diverse number of clinical cases for comparison. Several areas such as software development, image processing and medical training need a diverse and comprehensive dataset of images and related information. Such datasets could be used to develop, test and evaluate new medical software, using public data. This work presents the development of a free, online, multipurpose and multimodality medical image database environment. The environment, implemented such as a distributed medical image database, stores medical images, reports, image processing softwares, gold standards and post-processed images. Also, this environment implements a peer review model which assures the quality of all datasets. As an example of feasibility and easyness of use, it is shown the evaluation in two categories of medical image processing methods: segmentation and compression. In addition, the use of the set of applications proposed in this work in other activities, such as the HC-FMUSP digital teaching file, shows the robustness of the proposed architecture and its applicability on different purposes.

Este trabalho apresenta um método computacional que classifica as mamografias no padrão de densidade BI-RADS, visando auxiliar a detecção precoce do câncer de mama, seja essa realizada por análise visual ou por auxílio computadorizado. A classificação das mamografias em bancos padronizados objetiva eliminar conflitos entre laudos mamográficos de diferentes profissionais, bem como quanto à conduta médica a ser seguida. Entretanto, o estabelecimento de bancos feito visualmente e principalmente em períodos diferentes dificulta sua uniformização, proporcionando uma classificação muito subjetiva e relativamente grosseira em conseqüência a grande variação entre e inter observadores. O método desenvolvido permitiu classificar as imagens independentemente da subjetividade própria à observação visual de quem organizou o banco ou da técnica de exposição aos raios X utilizada. Os resultados foram superiores a 92% mesmo para bancos de imagens totalmente diferentes. Esses resultados foram obtidos respeitando-se as possíveis diferenças de interpretações de diversas equipes médicas. Além do estabelecimento de banco de mamografias com limiares entre as composições bem quantificadas, com esta ferramenta, tanto os estagiários poderão ser treinados para classificar as imagens no padrão de densidades do BI-RADS, respeitando as particularidades locais, quanto os resultados dos CAD poderão ser comparados. / This thesis presents a computational method that classifies the mammography into the composition of the breast tissue density patterns described in the BI-RADS protocol, intended to help in the early detection of breast cancer, either if this detection happens to be realized by visual analysis or by computerized support. The classification of the mammography in standardized database intends to eliminate issues between mammography awards of distinct professionals and the correct medical conduct to be followed. However, the determination of database only visually, especially in different periods, difficult it\'s to standardize, causing an extremely subjective classification and relatively superficial in consequence of the large inter-and intraobserver variability. The method allows classifying the images independently of the subjective quality of the visual analysis from who organized the database or from the technique of the exposition to X-ray employed. The results were superior of 92% even to database totally distinct. These results were obtained respecting eventual differences of interpretation from several medical groups. Beside the establishment of mammography database with thresholding between the well quantified categories, this methodology will consent to probationers to be trained for classify the images according to the composition of the breast tissue density patterns described in the BI-RADS, respecting its local particularity. Likewise, with this methodology, the results from CAD would be compared.

Constantemente, uma variedade de novos métodos de processamento de imagens é apresentada à comunidade. Porém poucos têm provado sua utilidade na rotina clínica. A análise e comparação de diferentes abordagens por meio de uma mesma metodologia são essenciais para a qualificação do projeto de um algoritmo. Porém, é difícil comparar o desempenho e adequabilidade de diferentes algoritmos de uma mesma maneira. A principal razão deve-se à dificuldade para avaliar exaustivamente um software, ou pelo menos, testá-lo num conjunto abrangente e diversificado de casos clínicos. Muitas áreas - como o desenvolvimento de software e treinamentos em Medicina - necessitam de um conjunto diverso e abrangente de dados sobre imagens e informações associadas. Tais conjuntos podem ser utilizados para desenvolver, testar e avaliar novos softwares clínicos, utilizando dados públicos. Este trabalho propõe o desenvolvimento de um ambiente de base de imagens médicas de diferentes modalidades para uso livre em diferentes propósitos. Este ambiente - implementado como uma arquitetura de base distribuída de imagens - armazena imagens médicas com informações de aquisição, laudos, algoritmos de processamento de imagens, gold standards e imagens pós-processadas. O ambiente também possui um modelo de revisão de documentos que garante a qualidade dos conjuntos de dados. Como exemplo da facilidade e praticidade de uso, são apresentadas as avaliações de duas categorias de métodos de processamento de imagens médicas: segmentação e compressão. Em adição, a utilização do ambiente em outras atividades, como no projeto do arquivo didático digital do HC-FMUSP, demonstra a robustez da arquitetura proposta e sua aplicação em diferentes propósitos. / Constantly, a variety of new image processing methods are presented to the community. However, few of them have proved to be useful when used in clinical routine. The task of analyzing and comparing different algorithms, methods and applications through a sound testing is an essential qualification of algorithm design. However, it is usually very difficult to compare the performance and adequacy of different algorithms in the same way. The main reason is due to the difficulty to assess exhaustively the software, or at least using a comprehensive and diverse number of clinical cases for comparison. Several areas such as software development, image processing and medical training need a diverse and comprehensive dataset of images and related information. Such datasets could be used to develop, test and evaluate new medical software, using public data. This work presents the development of a free, online, multipurpose and multimodality medical image database environment. The environment, implemented such as a distributed medical image database, stores medical images, reports, image processing softwares, gold standards and post-processed images. Also, this environment implements a peer review model which assures the quality of all datasets. As an example of feasibility and easyness of use, it is shown the evaluation in two categories of medical image processing methods: segmentation and compression. In addition, the use of the set of applications proposed in this work in other activities, such as the HC-FMUSP digital teaching file, shows the robustness of the proposed architecture and its applicability on different purposes.

Ob Standorte von Kirchen in Deutschland, Schlössern und Rittergütern in Sachsen oder Mühlen in Brandenburg, ob hausnummerngenauer Nachweis von Wohnhäusern in der Dresdner Neustadt oder der Sammlungsorte von Kunstwerken – seit Sommer 2007 können die geografischen Bezüge der Aufnahmen aus der Bilddatenbank der Deutschen Fotothek komfortabel und übersichtlich auf Karten- und Satellitenbildern dargestellt werden.

The focus of this research is the extension of topological operators with the addition of a inclusion measure. This extension is carried out in both crisp and fuzzy topological spaces. The mathematical properties of the new operators are discussed and compared with traditional operators. Ignoring small errors due to imperfections and noise in digital images is the main motivation in introducing the proposed operators. To show the effectiveness of the new operators, we demonstrate their utility in image database classification and shape classification. Each image (shape) category is modeled with a topological space and the interior of the query image is obtained with respect to different topologies. This novel way of looking at the image categories and classifying a query image shows some promising results. Moreover, the proposed interior and closure operators with inclusion degree is utilized in mathematical morphology area. The morphological operators with inclusion degree outperform traditional morphology in noise removal and edge detection in a noisy environment

The focus of this research is the extension of topological operators with the addition of a inclusion measure. This extension is carried out in both crisp and fuzzy topological spaces. The mathematical properties of the new operators are discussed and compared with traditional operators. Ignoring small errors due to imperfections and noise in digital images is the main motivation in introducing the proposed operators. To show the effectiveness of the new operators, we demonstrate their utility in image database classification and shape classification. Each image (shape) category is modeled with a topological space and the interior of the query image is obtained with respect to different topologies. This novel way of looking at the image categories and classifying a query image shows some promising results. Moreover, the proposed interior and closure operators with inclusion degree is utilized in mathematical morphology area. The morphological operators with inclusion degree outperform traditional morphology in noise removal and edge detection in a noisy environment

Este trabalho apresenta um método computacional que classifica as mamografias no padrão de densidade BI-RADS, visando auxiliar a detecção precoce do câncer de mama, seja essa realizada por análise visual ou por auxílio computadorizado. A classificação das mamografias em bancos padronizados objetiva eliminar conflitos entre laudos mamográficos de diferentes profissionais, bem como quanto à conduta médica a ser seguida. Entretanto, o estabelecimento de bancos feito visualmente e principalmente em períodos diferentes dificulta sua uniformização, proporcionando uma classificação muito subjetiva e relativamente grosseira em conseqüência a grande variação entre e inter observadores. O método desenvolvido permitiu classificar as imagens independentemente da subjetividade própria à observação visual de quem organizou o banco ou da técnica de exposição aos raios X utilizada. Os resultados foram superiores a 92% mesmo para bancos de imagens totalmente diferentes. Esses resultados foram obtidos respeitando-se as possíveis diferenças de interpretações de diversas equipes médicas. Além do estabelecimento de banco de mamografias com limiares entre as composições bem quantificadas, com esta ferramenta, tanto os estagiários poderão ser treinados para classificar as imagens no padrão de densidades do BI-RADS, respeitando as particularidades locais, quanto os resultados dos CAD poderão ser comparados. / This thesis presents a computational method that classifies the mammography into the composition of the breast tissue density patterns described in the BI-RADS protocol, intended to help in the early detection of breast cancer, either if this detection happens to be realized by visual analysis or by computerized support. The classification of the mammography in standardized database intends to eliminate issues between mammography awards of distinct professionals and the correct medical conduct to be followed. However, the determination of database only visually, especially in different periods, difficult it\'s to standardize, causing an extremely subjective classification and relatively superficial in consequence of the large inter-and intraobserver variability. The method allows classifying the images independently of the subjective quality of the visual analysis from who organized the database or from the technique of the exposition to X-ray employed. The results were superior of 92% even to database totally distinct. These results were obtained respecting eventual differences of interpretation from several medical groups. Beside the establishment of mammography database with thresholding between the well quantified categories, this methodology will consent to probationers to be trained for classify the images according to the composition of the breast tissue density patterns described in the BI-RADS, respecting its local particularity. Likewise, with this methodology, the results from CAD would be compared.

Image completion is a process of removing an area from a photograph and replacing it with suitable data. Earlier methods either search for this relevant data within the image itself, or extends the search to some form of additional data, usually some form of database. Methods that search for suitable data within the image itself has problems when no suitable data can be found in the image. Methods that extend their search has in earlier work either used some form of database with labeled images or a massive database with photos from the Internet. For the labels in a database to be useful they typically needs to be entered manually, which is a very time consuming process. Methods that uses databases with millions of images from the Internet has issues with copyrighted images, storage of the photographs and computation time. This work shows that a small database of the user’s own private, or professional, photos can be used to improve the quality of image completions. A photographer today typically take many similar photographs on similar scenes during a photo session. Therefore a smaller number of images are needed to find images that are visually and structurally similar, than when random images downloaded from the internet are used. Thus, this approach gains most of the advantages of using additional data for the image completions, while at the same time minimizing the disadvantages. It gains a better ability to find suitable data without having to process millions of irrelevant photos.

Color has been widely used in content-based image retrieval (CBIR) applications. In such applications the color properties of an image are usually characterized by the probability distribution of the colors in the image. A distance measure is then used to measure the (dis-)similarity between images based on the descriptions of their color distributions in order to quickly find relevant images. The development and investigation of statistical methods for robust representations of such distributions, the construction of distance measures between them and their applications in efficient retrieval, browsing, and structuring of very large image databases are the main contributions of the thesis. In particular we have addressed the following problems in CBIR. Firstly, different non-parametric density estimators are used to describe color information for CBIR applications. Kernel-based methods using nonorthogonal bases together with a Gram-Schmidt procedure and the application of the Fourier transform are introduced and compared to previously used histogram-based methods. Our experiments show that efficient use of kernel density estimators improves the retrieval performance of CBIR. The practical problem of how to choose an optimal smoothing parameter for such density estimators as well as the selection of the histogram bin-width for CBIR applications are also discussed. Distance measures between color distributions are then described in a differential geometry-based framework. This allows the incorporation of geometrical features of the underlying color space into the distance measure between the probability distributions. The general framework is illustrated with two examples: Normal distributions and linear representations of distributions. The linear representation of color distributions is then used to derive new compact descriptors for color-based image retrieval. These descriptors are based on the combination of two ideas: Incorporating information from the structure of the color space with information from images and application of projection methods in the space of color distribution and the space of differences between neighboring color distributions. In our experiments we used several image databases containing more than 1,300,000 images. The experiments show that the method developed in this thesis is very fast and that the retrieval performance chievedcompares favorably with existing methods. A CBIR system has been developed and is currently available at http://www.media.itn.liu.se/cse. We also describe color invariant descriptors that can be used to retrieve images of objects independent of geometrical factors and the illumination conditions under which these images were taken. Both statistics- and physics-based methods are proposed and examined. We investigated the interaction between light and material using different physical models and applied the theory of transformation groups to derive geometry color invariants. Using the proposed framework, we are able to construct all independent invariants for a given physical model. The dichromatic reflection model and the Kubelka-Munk model are used as examples for the framework. The proposed color invariant descriptors are then applied to both CBIR, color image segmentation, and color correction applications. In the last chapter of the thesis we describe an industrial application where different color correction methods are used to optimize the layout of a newspaper page. / <p>A search engine based, on the methodes discribed in this thesis, can be found at http://pub.ep.liu.se/cse/db/?. Note that the question mark must be included in the address.</p>