A proposal to estimate the motion of an underwater vehicle through visual mosaicking

This thesis proposes a solution to the problem of estimating the motion of an Unmanned Underwater Vehicle (UUV). Our approach is based on the integration of the incremental measurements which are provided by a vision system. When the vehicle is close to the underwater terrain, it constructs a visual map (so called "mosaic") of the area where the mission takes place while, at the same time, it localizes itself on this map, following the Concurrent Mapping and Localization strategy. The proposed methodology to achieve this goal is based on a feature-based mosaicking algorithm. A down-looking camera is attached to the underwater vehicle. As the vehicle moves, a sequence of images of the sea-floor is acquired by the camera. For every image of the sequence, a set of characteristic features is detected by means of a corner detector. Then, their correspondences are found in the next image of the sequence. Solving the correspondence problem in an accurate and reliable way is a difficult task in computer vision. We consider different alternatives to solve this problem by introducing a detailed analysis of the textural characteristics of the image. This is done in two phases: first comparing different texture operators individually, and next selecting those that best characterize the point/matching pair and using them together to obtain a more robust characterization. Various alternatives are also studied to merge the information provided by the individual texture operators. Finally, the best approach in terms of robustness and efficiency is proposed. After the correspondences have been solved, for every pair of consecutive images we obtain a list of image features in the first image and their matchings in the next frame. Our aim is now to recover the apparent motion of the camera from these features. Although an accurate texture analysis is devoted to the matching pro-cedure, some false matches (known as outliers) could still appear among the right correspon-dences. For this reason, a robust estimation technique is used to estimate the planar transformation (homography) which explains the dominant motion of the image. Next, this homography is used to warp the processed image to the common mosaic frame, constructing a composite image formed by every frame of the sequence. With the aim of estimating the position of the vehicle as the mosaic is being constructed, the 3D motion of the vehicle can be computed from the measurements obtained by a sonar altimeter and the incremental motion computed from the homography. Unfortunately, as the mosaic increases in size, image local alignment errors increase the inaccuracies associated to the position of the vehicle. Occasionally, the trajectory described by the vehicle may cross over itself. In this situation new information is available, and the system can readjust the position estimates. Our proposal consists not only in localizing the vehicle, but also in readjusting the trajectory described by the vehicle when crossover information is obtained. This is achieved by implementing an Augmented State Kalman Filter (ASKF). Kalman filtering appears as an adequate framework to deal with position estimates and their associated covariances. Finally, some experimental results are shown. A laboratory setup has been used to analyze and evaluate the accuracy of the mosaicking system. This setup enables a quantitative measurement of the accumulated errors of the mosaics created in the lab. Then, the results obtained from real sea trials using the URIS underwater vehicle are shown.

Layer-by-layer coating of alginate matrices with chitosan–alginate for the improved survival and targeted delivery of probiotic bacteria after oral administration

The oral administration of probiotic bacteria has shown potential in clinical trials for the alleviation of specific disorders of the gastrointestinal tract. However, cells must be alive in order to exert these benefits. The low pH of the stomach can greatly reduce the number of viable microorganisms that reach the intestine, thereby reducing the efficacy of the administration. Herein, a model probiotic, Bifidobacterium breve, has been encapsulated into an alginate matrix before coating in multilayers of alternating alginate and chitosan. The intention of this formulation was to improve the survival of B. breve during exposure to low pH and to target the delivery of the cells to the intestine. The material properties were first characterized before in vitro testing. Biacore™ experiments allowed for the polymer interactions to be confirmed; additionally, the stability of these multilayers to buffers simulating the pH of the gastrointestinal tract was demonstrated. Texture analysis was used to monitor changes in the gel strength during preparation, showing a weakening of the matrices during coating as a result of calcium ion sequestration. The build-up of multilayers was confirmed by confocal laser-scanning microscopy, which also showed the increase in the thickness of coat over time. During exposure to in vitro gastric conditions, an increase in viability from <3 log(CFU) per mL, seen in free cells, up to a maximum of 8.84 ± 0.17 log(CFU) per mL was noted in a 3-layer coated matrix. Multilayer-coated alginate matrices also showed a targeting of delivery to the intestine, with a gradual release of their loads over 240 min.

PLANT LEAF IDENTIFICATION BASED ON VOLUMETRIC FRACTAL DIMENSION

Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.

Plant Leaf Identification Using Gabor Wavelets

This article presents a novel method of plant classification using Gabor wavelet filters to extract texture filters in a foliar surface. The aim of this promising method is to add to the results obtained by other leaf attributes (such as shape, contour, color, among others), increasing, therefore, the percentage of classification of plant species. To corroborate the efficiency of the technique, an experiment using 20 species from Brazilian flora was done and discussed. The results are also compared with texture Fourier descriptors and cooccurrence matrices. (C) 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 236-243, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20201

Colorizing Grey Scale Images

The purpose of this thesis is to develop a working methodology to color a grey scale image. This thesis is based on approach of using a colored reference image. Coloring grey scale images has no exact solution till date and all available methods are based on approximation. This technique of using a color reference image for approximating color information in grey scale image is among most modern techniques.Method developed here in this paper is better than existing methods of approximation of color information addition in grey scale images in brightness, sharpness, color shade gradients and distribution of colors over objects.Color and grey scale images are analyzed for statistical and textural features. This analysis is done only on basis of luminance value in images. These features are then segmented and segments of color and grey scale images are mapped on basis of distances of segments from origin. Then chromatic values are transferred between these matched segments from color image to grey scale image.Technique proposed in this paper uses better mechanism of mapping clusters and mapping colors between segments, resulting in notable improvement in existing techniques in this category.

Adição de areia para dispersão de solos na análise granulométrica

A acurácia da análise granulométrica depende da obtenção de suspensões de solo completamente dispersas e estáveis para possibilitar a separação das suas frações granulométricas. O objetivo do presente trabalho foi avaliar a eficácia da adição de quantidades e tamanhos de grãos de areia na fase de dispersão da análise granulométrica de solos, visando à maior acurácia na obtenção dos resultados da análise granulométrica. Os solos utilizados foram: Latossolo Vermelho eutroférrico (LVef), LatossoloVermelho acriférrico (LVwf), Latossolo Vermelho eutrófico (LVe), Argissolo Vermelho-Amarelo eutrófico (PVAe) e Nitossolo Vermelho eutroférrico (NVef). A dispersão das amostras dos solos foi realizada por meio da adição de hidróxido de sódio e agitação rotativa (60 rpm) por 16 h. O delineamento experimental adotado foi o inteiramente casualizado, com esquema fatorial 6 x 2, com três repetições. Os tratamentos foram constituídos por seis quantidades (0, 5, 10, 15, 20 e 25 g) e dois diâmetros (2,0-1,0 e 1,0-0,5 mm) de areia, adicionados na fase de dispersão da análise granulométrica dos solos. de acordo com as equações ajustadas, a adição de areia com diâmetro entre 1,0 e 0,5 mm nas quantidades de 21,4 g para LVef, 19,6 g para LVwf e 25,8 g para NVef proporciona, respectivamente para esses solos, aumentos de 50, 38 e 14,5 % nos teores de argila. No LVe e no PVAe não se justifica a adição de areia na análise granulométrica, pois esses solos não apresentaram problemas de dispersão. Os resultados demonstram que a adição de 25 g de areia, com diâmetro entre 1,0 e 0,5 mm, na fase de dispersão da análise granulométrica de solos argilosos com altos teores de óxidos de Fe e com dificuldades de dispersão, é eficiente para promover efetiva dispersão das partículas primárias do solo.

Plant species identification using multi-scale fractal dimension applied to images of adaxial surface epidermis

This paper presents the study of computational methods applied to histological texture analysis in order to identify plant species, a very difficult task due to the great similarity among some species and presence of irregularities in a given species. Experiments were performed considering 300 ×300 texture windows extracted from adaxial surface epidermis from eight species. Different texture methods were evaluated using Linear Discriminant Analysis (LDA). Results showed that methods based on complexity analysis perform a better texture discrimination, so conducting to a more accurate identification of plant species. © 2009 Springer Berlin Heidelberg.

Classification of masses in mammographic image using wavelet domain features and polynomial classifier

Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.

Desequilíbrio de ligação e associação entre polimorfismos de base única com maciez da carne e espessura de gordura em bovinos Nelore utilizando painéis de alta densidade

Pós-graduação em Genética e Melhoramento Animal - FCAV

Síntese e caracterização de híbridos inorgânico-orgânicos funcionalizados com tiouréia e 2,2’-dipiridilamina: aplicação em adsorção de íons metálicos, pré-concentração e catálise

Pós-graduação em Ciência dos Materiais - FEIS

Método de detecção e classificação de lesões de pele em imagens digitais a partir do modelo Chan-Vese e máquina de vetor de suporte

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização do surimi de tilápia do Nilo: morfologia e propiedades físicas, químicas e sensoriais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterização de argilas usadas para produção de cerâmica vermelha e estudo das alterações nas suas propriedades pela adição de resíduos

Neste trabalho são apresentados os resultados de caracterização das principais argilas usadas pela indústria cerâmica vermelha regional e, também, de alguns resíduos sólidos produzidos na região de Presidente Prudente - SP. Os resultados da incorporação destes resíduos em massas cerâmicas são avaliados através do estudo de suas propriedades tecnológicas. Para a caracterização dos materiais foram utilizadas as seguintes técnicas: análise textural (concentração das frações areia, silte e argila), difratometria de raios X e análise térmica. As propriedades tecnológicas de corpos de prova cerâmicos foram avaliadas através dos seguintes parâmetros: retração linear (RL), perda de massa ao fogo (PF), massa específica aparente (MEA), porosidade aparente (PA), absorção de água (AA) e resistência mecânica à flexão (RMF). Corpos de prova, com diferentes concentrações de resíduos, foram prensados (prensa uniaxial manual) e queimados em temperaturas que variaram de 800 a 1200 oC, usando um forno tipo mufla com controle de temperatura. As argilas sedimentares foram coletadas nas margens do rio Paraná e em áreas de várzea, próximas as cerâmicas. As amostras estudadas, coletadas nos depósitos das cerâmicas, são usadas para produção de tijolos maciços, blocos furados e telhas. Quatro tipos diferentes de resíduos foram estudados: (1) lodo de estação de tratamento de água ETA, (2) torta de filtro de indústria de re-refino de óleo lubrificante, (3) pó de vidro (soda-cal) de garrafa tipo long neck descartável, e (4) cinza de bagaço de cana. Estes resíduos foram incorporados em massas cerâmicas coletadas nas indústrias... (Resumo completo, clicar acesso eletrônico abaixo)

Síntese e caracterização de hidrogéis de amido retrogradado e goma gelana utilizados como matriz em sistemas de liberação cólon específica de fármacos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Avaliação sensorial e influência do tratamento térmico no teor de ácido ascórbico de sorvete de pimenta

In this work were prepared with three ice cream added peppers of different varieties: Capsicum baccatum, Capsicum annuum and Capsicum frutescens. The peppers were first pasteurized and evaluated in relation to the effect of heat treatment on the ascorbic acid content. Results showed that the Capsicum annuum showed higher ascorbic acid content, but the heat treatment resulted in greater loss of biocompounds. The higher retention of ascorbic acid was observed with Capsicum frutescens, which presented lower content of biocompound, but near of the pepper Capsicum annuum. The follow attributes was performed to evaluate the acceptance of ice cream through the sensory attributes: color, aroma, flavor and texture. Analysis of variance showed no significant difference between ice cream formulations at the 5% level of significance with regard to color, aroma and texture. Regarding taste, the samples differed significantly, at 5% significance, and the most preferred was the ice cream made with pepper Capsicum frutescens.