Syftet: Syftet med föreliggande studie var att undersöka färgstabiliteten hos manuellt infärgad hög-translucent zirkonia efter åldring i drycker med lågt pH-värde (vin och Coca Cola) och vatten. Material och metod: I studien användes 30 provkroppar i hög-translucent zirkonia. Provkropparna frästes fram i runda diskar med måtten 6 mm i diameter och 3 mm i tjocklek och färgades in manuellt med infiltreringsvätska genom doppteknik och därefter skedde sintring. Provkropparna förvarades i rött vin, Coca Cola eller destillerat vatten i 12 dagar. Färgkoordinaterna L*a*b* mättes genom spektrofotometer före (kontrollgrupp) och efter förvaring i respektive vätska. Medelvärdet av L*a*b* registrerades och färgskillnaderna (ΔEab, NBS) beräknades. Resultatet analyserades med Fisher՚s exact test samt One-way ANOVA, Tukey’s test med signifikansnivån α=0,05. Resultat: I jämförelse mellan grupperna hade gruppen som vinförvarats högst medelvärde i färgskillnad följt av vatten och Coca Cola. Färgskillnaden för gruppen som vinförvarats var kliniskt icke-acceptabel och visade en statistiskt signifikant skillnad jämfört med vatten och Coca Cola. Ingen statistisk signifikant skillnad observerades mellan de resterande grupperna vatten och Coca Cola. Signifikanta skillnader för färgskillnaden, ΔEab, observerades mellan kontrollgruppen mot övriga grupper för samtliga parametrar L* a* b* med p-värde<0,001 efter åldring i de olika dryckerna. Slutsats: Färgstabilitet hos manuellt infärgad hög-translucent zirkonia påverkas av åldring i drycker med lågt pH-värde såsom vin och Coca Cola, där vin påverkar mer än Coca Cola och vatten. Hög-translucent zirkonia som förvarats i vin uppvisar en rödare ton medan förvaring i Coca Cola uppvisar en gulare ton. / Purpose: This study investigated the color stability of manually infiltrated high translucent zirconia after immersion in beverages with low pH-value (wine and Coca Cola) and water.  Material and method: 30 specimens of high translucent zirconia were prepared. The specimens were milled into round discs and colored manually with infiltration liquid before sintering and were stored in red wine, Coca Cola, or distilled water for 12 days. The color coordinates L*a*b* were measured by spectrophotometer before and after storage in the specific beverage. The mean value of L*a*b* was recorded and the color differences (ΔEab, NBS) were calculated. The results were analyzed with Fisher's exact test and One-way ANOVA, Tukey's test with the significance level α=0.05. Results: In comparison between the groups, the wine group had the highest mean value in color difference followed by water and Coca Cola. Results from wine storage showed a statistically significant difference compared to water and Coca Cola which was clinically non-acceptable. No statistical significant difference was observed between the remaining groups.  Conclusion: Color stability of manually colored high translucent zirconia is affected by aging in beverages with a low pH-value such as wine and Coca Cola, where wine affected more as compared to Coca Cola and water. High translucent zirconia stored in wine exhibited a redder tone, while storage in Coca Cola exhibited a yellower tone.

The thesis deals with colors - their representation in digital devices and how to provide the best color preservation accross different devices. In the first part of the work, the knowledge of colors and human vision is briefly summarized. Then color models and color spaces are elaborated, mainly those device independent. Spectrum of colors viewable or printable on a device - the gamut - is different for every device and there's a need of precise reproduction or record of color. That's why the system of color management is described further and especially the gamut mapping approaches and algorithms are mentioned. In the second part of the work, the implementation of how two algorithms of color gamut mapping (HPMINDE, SCLIP) can be implemented in MATLAB is described. In the third and last part of the work, the results of implemented algorithms are presented and discussed. These results are compared to results of commonly used color gamut mapping technique (Adobe Photoshop).

A school of fiction known as local color emerged following the Civil War. It reached its peak of productivity during the 1880's, and faded at the turn of the century. The purpose of this study is to illuminate the Southern authors of this school, giving major emphasis to their genre in relation to their significance for Southern history. The main sources for this study come from the novels and short stories of the authors themselves. Also found valuable to this study were the numerous books, articles and criticisms of the authors by their contemporary critics. The Southern local color school, although it did not produce any major literary figures, contained many bright minor writers. As a group they reflected and shaped much of the thinking of their age. They also provide a connecting link between pre-war romanticism and the realism of the twentieth century.

Este trabalho foi desenvolvido com o intuito de se estabelecer uma metodologia para a classificação das cores de imagens digitais em cores perceptuais para se gerar um vetor de características que permita recuperar imagens através de seu conteúdo em uma base de dados. Em trabalhos e estudos correlatos analisados, as metodologias de agrupamento das diversas cores possíveis de uma imagem não permitem uma associação entre a cor digitalizada e a cor percebida por seres humanos. Estudos mostram que a maioria das culturas humanas associam às cores apenas onze termos: vermelho, amarelo, violeta, azul, verde, rosa, marrom, preto, branco, laranja e cinza. Este trabalho propõe, portanto, uma metodologia baseada em regras da lógica fuzzy, que permite associar a todas as possíveis cores de imagens digitais uma das onze cores culturais definidas, criando assim um histograma perceptual de cores. Isso permitiu a geração de um vetor de características para a recuperação de imagens baseada em conteúdo em uma base de dados. / This work aims at establishing a digital image classification methodology based on perceptual colors, by generating a feature vector that allows retrieving images from a database by their content. In related works the methodologies of grouping the diverse possible colors of an image do not allow associate digitized colors and those colors perceived by human beings. Studies show that the majority of human being culture associates only eleven terms to all the possible colors: red, yellow, blue, green, pink, brown, black, white, purple, orange and gray. This work purpose a methodology based on fuzzy logic that allows to associate the eleven cultural color terms with all of digitized colors by a perceptual color histogram. The image color quantization generates a feature vector used for content-based image retrieval. The results show that it is possible to use the perceptual color histogram for CBIR and in the semantic gap reduction.

Úlceras de pele são causadas devido à deficiência na circulação sanguínea. O diagnóstico é feito pela análise visual das regiões afetadas. A quantificação da distribuição de cores da lesão, por meio de técnicas de processamento de imagens pode auxiliar na caracterização e análise da dinâmica do processo patológico e resposta ao tratamento. O processamento de imagens de úlceras dermatológicas envolve etapas relacionadas a segmentação, caracterização e indexação. Esta análise é importante para classificação, recuperação de imagens similares e acompanhamento da evolução de uma lesão. Este trabalho apresenta um estudo sobre técnicas de segmentação e caracterização de imagens coloridas de úlceras de pele, baseadas nos modelos de cores RGB, HSV, L*a*b* e L*u*v*, utilizando suas componentes na extração de informações de textura e cor. Foram utilizadas técnicas de Aprendizado de Máquina e algoritmos matemáticos para a segmentação e extração de atributos, utilizando uma base de dados com 172 imagens. Nos testes de recuperação, foram utilizadas diferentes métricas de distância para avaliação do desempenho e técnicas de seleção de atributos. Os resultados obtidos evidenciam bom potencial para apoio ao diagnóstico e acompanhamento da evolução do tratamento com valores de até 75% de precisão para as técnicas de recuperação, 0,9 de área embaixo da curva receiver-operating-characteristic na classificação e 0,04 de erro médio quadrático entre a composição de cores da imagem segmentada automaticamente e a segmentada manualmente. Nos testes utilizando seleção de atributos, foi observado uma redução nos valores de precisão de recuperação (60%) e valores similares nos tetes de classificação (0,85). / Skin ulcers are caused due to deficiency in the bloodstream. The diagnosis is made by a visual analysis of the affected area. Quantification of color distribution of the lesion by image processing techniques can aid in the characterization and response to treatment. The image processing steps involves skin ulcers related to segmentation, characterization and indexing. This analysis is important for classification, image retrieval and similar tracking the evolution of an injury. This project presents a study of segmentation techniques and characterization of color images of dermatological skin ulcers, based on the color models RGB, HSV, L*a*b* and L*u*v*, using their components in the extraction of texture and color information. Were used Machine Learning techniques, mathematical algorithms for segmentation and extraction of attributes, using a database containing 172 images in two versions. In recovery tests were used different distance metrics for performance evaluation and techniques of features selection. The results show good potential to support the diagnosis and monitoring of treatment progress with values up to 75% precision in recovery techniques, 0.9 area under the curve receiver-operating-characteristic) in classification, and 0.04 mean square error between the color composition of the automatically segmented image and the manually segmented image. In tests utilizing feature selection was observed a decrease in precision values of image retrieval (60%) and similar values in the classification\'s tests (0.85).

Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-06-11T14:07:57Z No. of bitstreams: 1 HANNA FRANÇA MENEZES - DISSERTAÇÃO PPGDesign 2018..pdf: 84986995 bytes, checksum: 37d7333f46e5b8fc742a7f9ec888ef3c (MD5) / Made available in DSpace on 2018-06-11T14:07:57Z (GMT). No. of bitstreams: 1 HANNA FRANÇA MENEZES - DISSERTAÇÃO PPGDesign 2018..pdf: 84986995 bytes, checksum: 37d7333f46e5b8fc742a7f9ec888ef3c (MD5) Previous issue date: 2018-02 / Infography has been characterized as a new representaíion of form the contemporary informative journalism genre, that synthesizes the information from the resources the graphic visual language, aiming quick and efficient reading the news. Among the visual language elements that characterize its configuration, the color becomes an important feature the infographics, can contribute to emphasize and organize complex visual information, for clarity, visual balance, and harmony. However, it can also have negative effects, if used improperly, making information difficult to understand. Within this context, the present study investigates the indicative, perceptive and representative functions of color in the journalism infographics, aiming to propose recommendations for its use in the design of infographics. Therefore, this research presents an exploratory, mixedmethod (qualitative and quantitative) approach, to be carried out in four stages: (i) characterization of color functions; (ii) analysis of a set of infographics; (iii) processing and interpretation of data; and (iv) recommendations for the use of color in the project of journalism infographics. Comparing the three categories was observed that perceptive and indicative function categories were the most recurrent, being the functions harmonize, organize, hierarchize and measure the most ones. However, these same categories were also those ones that presented a higher number of probiems in the use of color, with the functions maintaining readability and visibility and maintaining consistency the most problematic ones. Such analysis identified successful uses and highlighted some shortcomings, moreover contributing recommendations for directing the proper application of color in journalism infographics.

Este trabalho foi desenvolvido com o intuito de se estabelecer uma metodologia para a classificação das cores de imagens digitais em cores perceptuais para se gerar um vetor de características que permita recuperar imagens através de seu conteúdo em uma base de dados. Em trabalhos e estudos correlatos analisados, as metodologias de agrupamento das diversas cores possíveis de uma imagem não permitem uma associação entre a cor digitalizada e a cor percebida por seres humanos. Estudos mostram que a maioria das culturas humanas associam às cores apenas onze termos: vermelho, amarelo, violeta, azul, verde, rosa, marrom, preto, branco, laranja e cinza. Este trabalho propõe, portanto, uma metodologia baseada em regras da lógica fuzzy, que permite associar a todas as possíveis cores de imagens digitais uma das onze cores culturais definidas, criando assim um histograma perceptual de cores. Isso permitiu a geração de um vetor de características para a recuperação de imagens baseada em conteúdo em uma base de dados. / This work aims at establishing a digital image classification methodology based on perceptual colors, by generating a feature vector that allows retrieving images from a database by their content. In related works the methodologies of grouping the diverse possible colors of an image do not allow associate digitized colors and those colors perceived by human beings. Studies show that the majority of human being culture associates only eleven terms to all the possible colors: red, yellow, blue, green, pink, brown, black, white, purple, orange and gray. This work purpose a methodology based on fuzzy logic that allows to associate the eleven cultural color terms with all of digitized colors by a perceptual color histogram. The image color quantization generates a feature vector used for content-based image retrieval. The results show that it is possible to use the perceptual color histogram for CBIR and in the semantic gap reduction.

Úlceras de pele são causadas devido à deficiência na circulação sanguínea. O diagnóstico é feito pela análise visual das regiões afetadas. A quantificação da distribuição de cores da lesão, por meio de técnicas de processamento de imagens pode auxiliar na caracterização e análise da dinâmica do processo patológico e resposta ao tratamento. O processamento de imagens de úlceras dermatológicas envolve etapas relacionadas a segmentação, caracterização e indexação. Esta análise é importante para classificação, recuperação de imagens similares e acompanhamento da evolução de uma lesão. Este trabalho apresenta um estudo sobre técnicas de segmentação e caracterização de imagens coloridas de úlceras de pele, baseadas nos modelos de cores RGB, HSV, L*a*b* e L*u*v*, utilizando suas componentes na extração de informações de textura e cor. Foram utilizadas técnicas de Aprendizado de Máquina e algoritmos matemáticos para a segmentação e extração de atributos, utilizando uma base de dados com 172 imagens. Nos testes de recuperação, foram utilizadas diferentes métricas de distância para avaliação do desempenho e técnicas de seleção de atributos. Os resultados obtidos evidenciam bom potencial para apoio ao diagnóstico e acompanhamento da evolução do tratamento com valores de até 75% de precisão para as técnicas de recuperação, 0,9 de área embaixo da curva receiver-operating-characteristic na classificação e 0,04 de erro médio quadrático entre a composição de cores da imagem segmentada automaticamente e a segmentada manualmente. Nos testes utilizando seleção de atributos, foi observado uma redução nos valores de precisão de recuperação (60%) e valores similares nos tetes de classificação (0,85). / Skin ulcers are caused due to deficiency in the bloodstream. The diagnosis is made by a visual analysis of the affected area. Quantification of color distribution of the lesion by image processing techniques can aid in the characterization and response to treatment. The image processing steps involves skin ulcers related to segmentation, characterization and indexing. This analysis is important for classification, image retrieval and similar tracking the evolution of an injury. This project presents a study of segmentation techniques and characterization of color images of dermatological skin ulcers, based on the color models RGB, HSV, L*a*b* and L*u*v*, using their components in the extraction of texture and color information. Were used Machine Learning techniques, mathematical algorithms for segmentation and extraction of attributes, using a database containing 172 images in two versions. In recovery tests were used different distance metrics for performance evaluation and techniques of features selection. The results show good potential to support the diagnosis and monitoring of treatment progress with values up to 75% precision in recovery techniques, 0.9 area under the curve receiver-operating-characteristic) in classification, and 0.04 mean square error between the color composition of the automatically segmented image and the manually segmented image. In tests utilizing feature selection was observed a decrease in precision values of image retrieval (60%) and similar values in the classification\'s tests (0.85).

Dans cette thèse, nous nous intéressons à la reconnaissance d’images couleur à l’aide d’une nouvelle approche géométrique du domaine fréquentiel. La plupart des méthodes existantes ne traitent que les images en niveaux de gris au travers de descripteurs issus de la transformée de Fourier usuelle. L’extension de telles méthodes aux images multicanaux, comme par exemple les images couleur, consiste généralement à reproduire un traitement identique sur chacun des canaux. Afin d’éviter ce traitement marginal, nous étudions et mettons en perspective les différentes généralisations de la transformée de Fourier pour les images couleur. Ce travail nous oriente vers la transformée de Fourier Clifford pour les images couleur définie dans le cadre des algèbres géométriques. Une étude approfondie de celle-ci nous conduit à définir un algorithme de calcul rapide et à proposer une méthode de corrélation de phase pour les images couleur. Dans un deuxième temps, nous cherchons à généraliser à travers cette transformée de Fourier les définitions des descripteurs de Fourier de la littérature. Nous étudions ainsi les propriétés, notamment l’invariance à la translation, rotation et échelle, des descripteurs existants. Ce travail nous mène à proposer trois nouveaux descripteurs appelés “descripteurs de Fourier couleur généralisés”(GCFD) invariants en translation et en rotation.Les méthodes proposées sont évaluées sur des bases d’images usuelles afin d’estimer l’apport du contenu fréquentiel couleur par rapport aux méthodes niveaux de gris et marginales. Les résultats obtenus à l’aide d’un classifieur SVM montrent le potentiel des méthodes proposées ; les descripteurs GCFD se révèlent être plus compacts, de complexité algorithmique moindre pour des performances de classification au minimum équivalentes. Nous proposons également des heuristiques pour le choix du paramètre de la transformée de Fourier Clifford.Cette thèse constitue un premier pas vers une généralisation des méthodes fréquentielles aux images multicanaux. / In this thesis, we focus on color image recognition using a new geometric approach in the frequency domain. Most existing methods only process grayscale images through descriptors defined from the usual Fourier transform. The extension of these methods to multichannel images such as color images usually consists in reproducing the same processing for each channel. To avoid this marginal processing,we study and compare the different generalizations of color Fourier transforms. This work leads us to use the Clifford Fourier transform for color images defined in the framework of geometric algebra. A detailed study of it leads us to define a fast algorithm and to propose a phase correlation for colorimages. In a second step, with the aim of generalizing Fourier descriptors of the literature with thisFourier transform, we study their properties, including invariance to translation, rotation and scale.This work leads us to propose three new descriptors called “generalized color Fourier descriptors”(GCFD) invariant in translation and in rotation.The proposed methods are evaluated on usual image databases to estimate the contribution of color frequency content compared with grayscale and marginal methods. The results obtained usingan SVM classifier show the potential of the proposed methods ; the GCFD are more compact, have less computational complexity and give better recognition rates. We also propose heuristics for choosing the parameter of the color Clifford Fourier transform.This thesis is a first step towards a generalization of frequency methods to multichannel images.

Indiana University-Purdue University Indianapolis (IUPUI) / Toner analysis has become an area of increased interest due to the wide availability of laser printers and photocopiers. Toner is most often encountered on paper in questioned document analysis. Because of this, it is important to develop methods that limit the interference of paper without damaging or destroying the document. Previous research using Fourier transform infrared spectroscopy (FTIR) has differentiated toners based on their polymer resin components. However, Raman spectroscopy and chemometric analysis are not typically used for the examination of this material. Raman spectroscopy is a popular tool for the chemical analysis of pigmented samples and was used to characterize cyan, yellow, and magenta toners. Analyses were performed using a dispersive micro-Raman spectrometer equipped with a 785nm diode laser, a CCD detector, and an objective at 20X magnification. One hundred samples of each color toner were collected. Three different and separate methods were developed for cyan, yellow, and magenta toners on paper to optimize results. Further analysis of the magenta toners was excluded due to a weak signal and significant paper interference. The data collected from the analyses of the blue and yellow toners was then processed using a combination of statistical procedures, including principal component analysis (PCA), agglomerative hierarchal clustering (AHC), and discriminative analysis (DA). Ninety-six blue toners were analyzed by PCA and three classes of spectra were suggested. Discriminant analysis showed that the three classes were well-differentiated with a cross-validation accuracy of 100% for the training set and 100% cross-validation accuracy for the external validation set. Eighty-eight yellow toners were analyzed by AHC and four classes of spectra were suggested. Discriminant analysis showed good differentiation between the classes with a cross-validation accuracy of 95.45% for the training set, but showed poor differentiation for the external validation set with a cross-validation accuracy of 72%. While these toners were able to be discriminated, no correlation could be made between the manufacturer, printer make and model, and the toner sample.