957 resultados para COLOR TEXTURE ANALYSIS


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Uma imagem engloba informação que precisa ser organizada para interpretar e compreender seu conteúdo. Existem diversas técnicas computacionais para extrair a principal informação de uma imagem e podem ser divididas em três áreas: análise de cor, textura e forma. Uma das principais delas é a análise de forma, por descrever características de objetos baseadas em seus pontos fronteira. Propomos um método de caracterização de imagens, por meio da análise de forma, baseada nas propriedades espectrais do laplaciano em grafos. O procedimento construiu grafos G baseados nos pontos fronteira do objeto, cujas conexões entre vértices são determinadas por limiares T_l. A partir dos grafos obtêm-se a matriz de adjacência A e a matriz de graus D, as quais definem a matriz Laplaciana L=D -A. A decomposição espectral da matriz Laplaciana (autovalores) é investigada para descrever características das imagens. Duas abordagens são consideradas: a) Análise do vetor característico baseado em limiares e a histogramas, considera dois parâmetros o intervalo de classes IC_l e o limiar T_l; b) Análise do vetor característico baseado em vários limiares para autovalores fixos; os quais representam o segundo e último autovalor da matriz L. As técnicas foram testada em três coleções de imagens: sintéticas (Genéricas), parasitas intestinais (SADPI) e folhas de plantas (CNShape), cada uma destas com suas próprias características e desafios. Na avaliação dos resultados, empregamos o modelo de classificação support vector machine (SVM), o qual avalia nossas abordagens, determinando o índice de separação das categorias. A primeira abordagem obteve um acerto de 90 % com a coleção de imagens Genéricas, 88 % na coleção SADPI, e 72 % na coleção CNShape. Na segunda abordagem, obtém-se uma taxa de acerto de 97 % com a coleção de imagens Genéricas; 83 % para SADPI e 86 % no CNShape. Os resultados mostram que a classificação de imagens a partir do espectro do Laplaciano, consegue categorizá-las satisfatoriamente.

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Biomedicine is a highly interdisciplinary research area at the interface of sciences, anatomy, physiology, and medicine. In the last decade, biomedical studies have been greatly enhanced by the introduction of new technologies and techniques for automated quantitative imaging, thus considerably advancing the possibility to investigate biological phenomena through image analysis. However, the effectiveness of this interdisciplinary approach is bounded by the limited knowledge that a biologist and a computer scientist, by professional training, have of each other’s fields. The possible solution to make up for both these lacks lies in training biologists to make them interdisciplinary researchers able to develop dedicated image processing and analysis tools by exploiting a content-aware approach. The aim of this Thesis is to show the effectiveness of a content-aware approach to automated quantitative imaging, by its application to different biomedical studies, with the secondary desirable purpose of motivating researchers to invest in interdisciplinarity. Such content-aware approach has been applied firstly to the phenomization of tumour cell response to stress by confocal fluorescent imaging, and secondly, to the texture analysis of trabecular bone microarchitecture in micro-CT scans. Third, this approach served the characterization of new 3-D multicellular spheroids of human stem cells, and the investigation of the role of the Nogo-A protein in tooth innervation. Finally, the content-aware approach also prompted to the development of two novel methods for local image analysis and colocalization quantification. In conclusion, the content-aware approach has proved its benefit through building new approaches that have improved the quality of image analysis, strengthening the statistical significance to allow unveiling biological phenomena. Hopefully, this Thesis will contribute to inspire researchers to striving hard for pursuing interdisciplinarity.

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Postharvest losses vary among the different vegetable products. However, among fruits and vegetables the losses generally range from 30% to 50%. Thus, this paper aimed the application of 1-methylcycloprene (1-MCP) and fast cooling with forced air (PC) on peaches, in order to estimate their effects in the ripening process of this fruit. Physiological analyses were performed, such as loss of fresh mass, firmness, pH, titratable acidity, soluble solids, ratio and CO2 production, as well as sensorial analyses such as color, texture and flavor. The experiment was divided in two phases. In the first one, concentrations of 30, 60, and 90 nL/L 1-MCP, applied at 0 ºC and 20 ºC, were tested. The fruits treated without 1-MCP were denominated control for both temperatures studied. The second phase was composed by the following treatments: cold storage (CS) or control, cooling with forced air (CFA), cooling with forced air followed by 1-MCP application (CFA + 1-MCP) and 1-MCP application (1-MCP). Among these, the CFA + 1-MCP treatment provided more firmness of the fruits in comparison to the control fruits. The respiratory rate of peaches under CFA and CFA + 1-MCP treatments decreased in comparison to the control fruit respiratory rates.

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This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

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The objective was to use natural pigments to replace sodium erythorbate (NaEry), a synthetic compound used as an antioxidant in sausage formulations, and to evaluate the oxidative stability of the samples. Six assays were prepared in which sodium erythorbate (ERY) at 0.05 g/100 g was substituted by norbixin (NOR), lycopene (LYC), zeaxanthin (ZEA), beta-carotene (CAR) or dextrose (used as a control (CON)). Physical, chemical, color, texture and sensory parameters were measured on the first day and after 45 days of storage at 4 degrees C. All pigments used in the sausage formulations were able to maintain the oxidative stability of the sausages (MDA equivalents <038 mg/kg). Zeaxanthin and norbixin were the most efficient antioxidants of those tested. This antioxidant effect might be associated with the intermediate polarities of these two compounds, which would allow them to concentrate in the membrane lipids or emulsion interface, where lipid oxidation is most prevalent. Other volatile secondary products of oxidation besides MDA should be evaluated in further studies involving natural pigments and sensory oxidative stability. (C) 2009 Elsevier Ltd. All rights reserved.

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In this work the effect of pre-treatments on the physical properties of fresh kiwi was studied. For that, a set of tests using chemical pretreatments was used, in which the samples were subjected to aqueous solutions of ascorbic acid and potassium metabisulfite at concentrations of 0.25% and 1% (w/v) for periods of 30 and 60 minutes, in order to understand the implications of the treatments in the color and texture of the kiwi as compared to its original properties. The results showed that the kiwi treated with ascorbic acid changed its color very intensively when compared to the fresh product, and this trend was intensified after storage. Contrarily, when potassium metabisulfite was used, the changes in color were quite negligible right after the treatment and even lower after the storage period of 6 days under refrigeration. After the treatments with both solutions, the kiwi texture was drastically changed, diminishing hardness considerably and increasing elasticity for all treatments. The same could be observed after six days of refrigeration.

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Dissertação para obtenção do Grau de Doutor em Química

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Dissertação para obtenção do Grau de Doutor em Engenharia do Ambiente

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When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot

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La tomodensitométrie (CT) est une technique d'imagerie dont l'intérêt n'a cessé de croître depuis son apparition dans le début des années 70. Dans le domaine médical, son utilisation est incontournable à tel point que ce système d'imagerie pourrait être amené à devenir victime de son succès si son impact au niveau de l'exposition de la population ne fait pas l'objet d'une attention particulière. Bien évidemment, l'augmentation du nombre d'examens CT a permis d'améliorer la prise en charge des patients ou a rendu certaines procédures moins invasives. Toutefois, pour assurer que le compromis risque - bénéfice soit toujours en faveur du patient, il est nécessaire d'éviter de délivrer des doses non utiles au diagnostic.¦Si cette action est importante chez l'adulte elle doit être une priorité lorsque les examens se font chez l'enfant, en particulier lorsque l'on suit des pathologies qui nécessitent plusieurs examens CT au cours de la vie du patient. En effet, les enfants et jeunes adultes sont plus radiosensibles. De plus, leur espérance de vie étant supérieure à celle de l'adulte, ils présentent un risque accru de développer un cancer radio-induit dont la phase de latence peut être supérieure à vingt ans. Partant du principe que chaque examen radiologique est justifié, il devient dès lors nécessaire d'optimiser les protocoles d'acquisitions pour s'assurer que le patient ne soit pas irradié inutilement. L'avancée technologique au niveau du CT est très rapide et depuis 2009, de nouvelles techniques de reconstructions d'images, dites itératives, ont été introduites afin de réduire la dose et améliorer la qualité d'image.¦Le présent travail a pour objectif de déterminer le potentiel des reconstructions itératives statistiques pour réduire au minimum les doses délivrées lors d'examens CT chez l'enfant et le jeune adulte tout en conservant une qualité d'image permettant le diagnostic, ceci afin de proposer des protocoles optimisés.¦L'optimisation d'un protocole d'examen CT nécessite de pouvoir évaluer la dose délivrée et la qualité d'image utile au diagnostic. Alors que la dose est estimée au moyen d'indices CT (CTDIV0| et DLP), ce travail a la particularité d'utiliser deux approches radicalement différentes pour évaluer la qualité d'image. La première approche dite « physique », se base sur le calcul de métriques physiques (SD, MTF, NPS, etc.) mesurées dans des conditions bien définies, le plus souvent sur fantômes. Bien que cette démarche soit limitée car elle n'intègre pas la perception des radiologues, elle permet de caractériser de manière rapide et simple certaines propriétés d'une image. La seconde approche, dite « clinique », est basée sur l'évaluation de structures anatomiques (critères diagnostiques) présentes sur les images de patients. Des radiologues, impliqués dans l'étape d'évaluation, doivent qualifier la qualité des structures d'un point de vue diagnostique en utilisant une échelle de notation simple. Cette approche, lourde à mettre en place, a l'avantage d'être proche du travail du radiologue et peut être considérée comme méthode de référence.¦Parmi les principaux résultats de ce travail, il a été montré que les algorithmes itératifs statistiques étudiés en clinique (ASIR?, VEO?) ont un important potentiel pour réduire la dose au CT (jusqu'à-90%). Cependant, par leur fonctionnement, ils modifient l'apparence de l'image en entraînant un changement de texture qui pourrait affecter la qualité du diagnostic. En comparant les résultats fournis par les approches « clinique » et « physique », il a été montré que ce changement de texture se traduit par une modification du spectre fréquentiel du bruit dont l'analyse permet d'anticiper ou d'éviter une perte diagnostique. Ce travail montre également que l'intégration de ces nouvelles techniques de reconstruction en clinique ne peut se faire de manière simple sur la base de protocoles utilisant des reconstructions classiques. Les conclusions de ce travail ainsi que les outils développés pourront également guider de futures études dans le domaine de la qualité d'image, comme par exemple, l'analyse de textures ou la modélisation d'observateurs pour le CT.¦-¦Computed tomography (CT) is an imaging technique in which interest has been growing since it first began to be used in the early 1970s. In the clinical environment, this imaging system has emerged as the gold standard modality because of its high sensitivity in producing accurate diagnostic images. However, even if a direct benefit to patient healthcare is attributed to CT, the dramatic increase of the number of CT examinations performed has raised concerns about the potential negative effects of ionizing radiation on the population. To insure a benefit - risk that works in favor of a patient, it is important to balance image quality and dose in order to avoid unnecessary patient exposure.¦If this balance is important for adults, it should be an absolute priority for children undergoing CT examinations, especially for patients suffering from diseases requiring several follow-up examinations over the patient's lifetime. Indeed, children and young adults are more sensitive to ionizing radiation and have an extended life span in comparison to adults. For this population, the risk of developing cancer, whose latency period exceeds 20 years, is significantly higher than for adults. Assuming that each patient examination is justified, it then becomes a priority to optimize CT acquisition protocols in order to minimize the delivered dose to the patient. Over the past few years, CT advances have been developing at a rapid pace. Since 2009, new iterative image reconstruction techniques, called statistical iterative reconstructions, have been introduced in order to decrease patient exposure and improve image quality.¦The goal of the present work was to determine the potential of statistical iterative reconstructions to reduce dose as much as possible without compromising image quality and maintain diagnosis of children and young adult examinations.¦The optimization step requires the evaluation of the delivered dose and image quality useful to perform diagnosis. While the dose is estimated using CT indices (CTDIV0| and DLP), the particularity of this research was to use two radically different approaches to evaluate image quality. The first approach, called the "physical approach", computed physical metrics (SD, MTF, NPS, etc.) measured on phantoms in well-known conditions. Although this technique has some limitations because it does not take radiologist perspective into account, it enables the physical characterization of image properties in a simple and timely way. The second approach, called the "clinical approach", was based on the evaluation of anatomical structures (diagnostic criteria) present on patient images. Radiologists, involved in the assessment step, were asked to score image quality of structures for diagnostic purposes using a simple rating scale. This approach is relatively complicated to implement and also time-consuming. Nevertheless, it has the advantage of being very close to the practice of radiologists and is considered as a reference method.¦Primarily, this work revealed that the statistical iterative reconstructions studied in clinic (ASIR? and VECO have a strong potential to reduce CT dose (up to -90%). However, by their mechanisms, they lead to a modification of the image appearance with a change in image texture which may then effect the quality of the diagnosis. By comparing the results of the "clinical" and "physical" approach, it was showed that a change in texture is related to a modification of the noise spectrum bandwidth. The NPS analysis makes possible to anticipate or avoid a decrease in image quality. This project demonstrated that integrating these new statistical iterative reconstruction techniques can be complex and cannot be made on the basis of protocols using conventional reconstructions. The conclusions of this work and the image quality tools developed will be able to guide future studies in the field of image quality as texture analysis or model observers dedicated to CT.

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Considering that information from soil reflectance spectra is underutilized in soil classification, this paper aimed to evaluate the relationship of soil physical, chemical properties and their spectra, to identify spectral patterns for soil classes, evaluate the use of numerical classification of profiles combined with spectral data for soil classification. We studied 20 soil profiles from the municipality of Piracicaba, State of São Paulo, Brazil, which were morphologically described and classified up to the 3rd category level of the Brazilian Soil Classification System (SiBCS). Subsequently, soil samples were collected from pedogenetic horizons and subjected to soil particle size and chemical analyses. Their Vis-NIR spectra were measured, followed by principal component analysis. Pearson's linear correlation coefficients were determined among the four principal components and the following soil properties: pH, organic matter, P, K, Ca, Mg, Al, CEC, base saturation, and Al saturation. We also carried out interpretation of the first three principal components and their relationships with soil classes defined by SiBCS. In addition, numerical classification of the profiles based on the OSACA algorithm was performed using spectral data as a basis. We determined the Normalized Mutual Information (NMI) and Uncertainty Coefficient (U). These coefficients represent the similarity between the numerical classification and the soil classes from SiBCS. Pearson's correlation coefficients were significant for the principal components when compared to sand, clay, Al content and soil color. Visual analysis of the principal component scores showed differences in the spectral behavior of the soil classes, mainly among Argissolos and the others soils. The NMI and U similarity coefficients showed values of 0.74 and 0.64, respectively, suggesting good similarity between the numerical and SiBCS classes. For example, numerical classification correctly distinguished Argissolos from Latossolos and Nitossolos. However, this mathematical technique was not able to distinguish Latossolos from Nitossolos Vermelho férricos, but the Cambissolos were well differentiated from other soil classes. The numerical technique proved to be effective and applicable to the soil classification process.

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Methods of improving highway safety are of major concern to everyone who is involved in the planning, development and construction of improvements of our vast highway network. Other major concerns are the conservation of our rapidly disappearing sources of energy and quality building materials. This research is devoted to further exploration of a process which will: 1. help preserve higher quality aggregates; and, 2. improve the frictional characteristics and surface texture of asphalt pavement surfaces. Sprinkle treatment of asphalt concrete pavement surfaces with a non-polishing aggregate, a procedure which was developed in Europe, is one method which has shown promise in accomplishing the above listed objectives. This research seeks to explore the feasibility and cost effectiveness of using standard asphalt mixtures of local, less expensive aggregates for surface courses followed by a surface sprinkle treatment of a hard, durable, non-polishing layer of precoated chips to produce a durable, non-skid pavement surface for safe highway travel. Three standard mixture types are being evaluated for aggregate retention characteristics and six sprinkle aggregates are being evaluated for durability, polishing and friction characteristics. In addition, measurements of the surface texture by the silicone putty method are being made. Another feature of this research is the evaluation of a rubberized asphalt material called Overflex MS as a crack filler. It has been reported that the material could be beneficial in reducing reflective cracking. The project was begun in July of 1978 and was completed in August. A review made in the spring of 1979 indicates very satisfactory performance. It was determined from slide photos taken after construction and again in the spring that aggregate retention was very good. However, many cracks had reflected indicating that the Overflex MS had not been effective. Follow up friction test results and texture analysis were also very good. The results of these tests are shown in Appendix A.

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A beautiful smile is directly related with white teeth. Nowadays oral care has increased and developed processes for beautiful smiles. Dental bleaching is frequently used in odontology, not just for health care also for aesthetic treatment. With the possibility of teeth bleaching, now the importance is in, how white the tooth is? Because color is relate to an individual perception. In order to assets teeth correct color identification has been developed many color guides, models, spaces and analytical methods. Spite all of these useful tools the color interpretation depends on environmental factors, position of the sample in the data acquisition and most importantly the instrument sensitivity. The commons methods have proved to be useful. They are easy to handle, some are portable but they do not have a high sensitivity. The present work is based on the integration of a new analytical technique for color acquisition. High spectral Image (HSI) is able to performed image analysis with high quality and efficiency. HSI is used in many fields and we used it for color image analysis within the bleaching process. The main comparison was done with the HSI and the colorimeter through the processes of two different bleaching protocols. The results showed that HSI has higher sensitivity than the colorimeter. During the analysis the dental surface with the HSI we were able to notice surface changes. These changes were analyzed by roughness studies.

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The aim of the present study was to determine the impact of trabecular bone score on the probability of fracture above that provided by the clinical risk factors utilized in FRAX. We performed a retrospective cohort study of 33,352 women aged 40-99 years from the province of Manitoba, Canada, with baseline measurements of lumbar spine trabecular bone score (TBS) and FRAX risk variables. The analysis was cohort-specific rather than based on the Canadian version of FRAX. The associations between trabecular bone score, the FRAX risk factors and the risk of fracture or death were examined using an extension of the Poisson regression model and used to calculate 10-year probabilities of fracture with and without TBS and to derive an algorithm to adjust fracture probability to take account of the independent contribution of TBS to fracture and mortality risk. During a mean follow-up of 4.7 years, 1754 women died and 1639 sustained one or more major osteoporotic fractures excluding hip fracture and 306 women sustained one or more hip fracture. When fully adjusted for FRAX risk variables, TBS remained a statistically significant predictor of major osteoporotic fractures excluding hip fracture (HR/SD 1.18, 95 % CI 1.12-1.24), death (HR/SD 1.20, 95 % CI 1.14-1.26) and hip fracture (HR/SD 1.23, 95 % CI 1.09-1.38). Models adjusting major osteoporotic fracture and hip fracture probability were derived, accounting for age and trabecular bone score with death considered as a competing event. Lumbar spine texture analysis using TBS is a risk factor for osteoporotic fracture and a risk factor for death. The predictive ability of TBS is independent of FRAX clinical risk factors and femoral neck BMD. Adjustment of fracture probability to take account of the independent contribution of TBS to fracture and mortality risk requires validation in independent cohorts.

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The thermotolerant capacity of several lactic acid bacteria strains isolated from cooked commercial sausages was determined. Four strains were positively identified as Lactobacillus plantarum, Lactobacillus curvatus, Pediococcus pentosaceus and Pediococcus acidilacti, after surviving thermal treatment (70 °C during 60 minutes). Thermotolerant strains were inoculated in sausage batters before cooking in order to determine their effect on color, texture, acceptance and inhibition of Enterobacteria during 12 days at 8 °C. No significant effect of the inoculated strains was detected on color parameters. Textural profile parameters, cohesiveness and resilience, were not affected by the inoculation of thermotolerant lactic acid bacteria, but L. curvatus sausages resulted softer than the rest of the treatments. Samples inoculated with L. curvatus also obtained the lowest scores for the sensory attributes evaluated, with the remaining treatments causing no unfavorable effects on sausage acceptance. There was a reduction in enterobacterial counts after 12 days of cold storage in inoculated samples. The performance of inoculated lactic acid bacteria strains can be explained in a similar way as that of starter cultures in dry-fermented sausages, where the growth in nests impairs other pathogenic microorganisms present in the rest of the sausage, since environmental conditions and the early inoculation of these thermotolerant strains favor them to become the dominant flora.