Refraction corrected transmission ultrasound computed tomography for application in breast imaging

Purpose: We present an iterative framework for CT reconstruction from transmission ultrasound data which accurately and efficiently models the strong refraction effects that occur in our target application: Imaging the female breast. Methods: Our refractive ray tracing framework has its foundation in the fast marching method (FNMM) and it allows an accurate as well as efficient modeling of curved rays. We also describe a novel regularization scheme that yields further significant reconstruction quality improvements. A final contribution is the development of a realistic anthropomorphic digital breast phantom based on the NIH Visible Female data set. Results: Our system is able to resolve very fine details even in the presence of significant noise, and it reconstructs both sound speed and attenuation data. Excellent correspondence with a traditional, but significantly more computationally expensive wave equation solver is achieved. Conclusions: Apart from the accurate modeling of curved rays, decisive factors have also been our regularization scheme and the high-quality interpolation filter we have used. An added benefit of our framework is that it accelerates well on GPUs where we have shown that clinical 3D reconstruction speeds on the order of minutes are possible.

An Information Theory framework for two-stage binary image operator design

The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.

MACHINE VISION FOR AUTOMATICVISUAL INSPECTION OF WOODENRAILWAY SLEEPERS USING UNSUPERVISED NEURAL NETWORKS

The motivation for this thesis work is the need for improving reliability of equipment and quality of service to railway passengers as well as a requirement for cost-effective and efficient condition maintenance management for rail transportation. This thesis work develops a fusion of various machine vision analysis methods to achieve high performance in automation of wooden rail track inspection.The condition monitoring in rail transport is done manually by a human operator where people rely on inference systems and assumptions to develop conclusions. The use of conditional monitoring allows maintenance to be scheduled, or other actions to be taken to avoid the consequences of failure, before the failure occurs. Manual or automated condition monitoring of materials in fields of public transportation like railway, aerial navigation, traffic safety, etc, where safety is of prior importance needs non-destructive testing (NDT).In general, wooden railway sleeper inspection is done manually by a human operator, by moving along the rail sleeper and gathering information by visual and sound analysis for examining the presence of cracks. Human inspectors working on lines visually inspect wooden rails to judge the quality of rail sleeper. In this project work the machine vision system is developed based on the manual visual analysis system, which uses digital cameras and image processing software to perform similar manual inspections. As the manual inspection requires much effort and is expected to be error prone sometimes and also appears difficult to discriminate even for a human operator by the frequent changes in inspected material. The machine vision system developed classifies the condition of material by examining individual pixels of images, processing them and attempting to develop conclusions with the assistance of knowledge bases and features.A pattern recognition approach is developed based on the methodological knowledge from manual procedure. The pattern recognition approach for this thesis work was developed and achieved by a non destructive testing method to identify the flaws in manually done condition monitoring of sleepers.In this method, a test vehicle is designed to capture sleeper images similar to visual inspection by human operator and the raw data for pattern recognition approach is provided from the captured images of the wooden sleepers. The data from the NDT method were further processed and appropriate features were extracted.The collection of data by the NDT method is to achieve high accuracy in reliable classification results. A key idea is to use the non supervised classifier based on the features extracted from the method to discriminate the condition of wooden sleepers in to either good or bad. Self organising map is used as classifier for the wooden sleeper classification.In order to achieve greater integration, the data collected by the machine vision system was made to interface with one another by a strategy called fusion. Data fusion was looked in at two different levels namely sensor-level fusion, feature- level fusion. As the goal was to reduce the accuracy of the human error on the rail sleeper classification as good or bad the results obtained by the feature-level fusion compared to that of the results of actual classification were satisfactory.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Detecting Plants on Railway Embankments

This paper investigates problems concerning vegetation along railways and proposes automatic means of detecting ground vegetation. Digital images of railway embankments have been acquired and used for the purpose. The current work mainly proposes two algorithms to be able to achieve automation. Initially a vegetation detection algorithm has been investigated for the purpose of detecting vegetation. Further a rail detection algorithm that is capable of identifying the rails and eventually the valid sampling area has been investigated. Results achieved in the current work report satisfactory (qualitative) detection rates.

Análise digital de imagem e estereologia da angiogênese em adenomas e no adenocarcinoma colorretal invasivo de submucosa

A angiogênese é essencial no desenvolvimento neoplásico, associando-se às metástases à distância e recorrência em diversas neoplasias malignas. Em carcinomas colorretais, os parâmetros da análise digital de imagem e estereologia da angiogênese foram pouco estudados. Objetivo: avaliar parâmetros tridimensionais e a quantificação microvascular bidimensional nas diferentes apresentações morfológicas dos adenomas colorretais e no adenocarcinoma colorretal restrito à submucosa, a fim de determinar o papel da angiogênese nas diferentes etapas da seqüência adenoma-carcinoma e sua relação com as diferentes apresentações das lesões precursoras do carcinoma colorretal. Material e métodos: foi realizado estudo histórico de delineamento transversal, incluindo 115 lesões neoplásicas colorretais, ressecadas endoscópica ou cirurgicamente no período de 1997 a 2001, obtidas de pacientes do Hospital de Clínicas de Porto Alegre e da Fundação Universitária de Gastroenterologia (FUGAST). Para análise da angiogênese foram utilizadas as técnicas de imuno-histoquímica, análise digital de imagem, quantificação microvascular e estereologia. Os resultados foram apresentados como mediana e intervalos interquartis. Resultados: a quantificação microvascular foi progressivamente mais elevada nas lesões polipóides com displasia de alto grau comparadas às de baixo grau. Quanto maior o grau de atipia observado, maior foi o número de microvasos (regressão linear, P < 0,05). O volume e extensão microvascular foram diferentes entre as fases evolutivas da neoplasia colorretal, resultando em aumento no volume 728 (416 - 1408) versus 178 (93 - 601) e extensão microvascular 242,4 (131,1 - 936,8) vs 24,0 (6,5 - 142,2) (P < 0,001) nas lesões polipóides com displasia de alto grau comparadas às de baixo grau, respectivamente. A quantificação microvascular foi progressivamente mais elevada, acompanhando a progressão neoplásica polipóide: displasia de baixo grau 41,8 (15,8 - 71,9), displasia de alto grau 60,0 (23,0 - 95,6) e carcinoma de submucosa 76,0 (37,5 - 132,6) (P < 0,001). Concomitante, o volume 956 (436 - 2188) vs 178 (93 - 601) e a extensão microvascular 534,6 (146,7 - 1262) vs 24,0 (6,5 - 142,2) foram mais elevados nos adenocarcinomas colorretais restritos à submucosa em relação às lesões polipóides com displasia de baixo grau, respectivamente (P < 0,001). Não foi encontrada diferença estatisticamente significativa na angiogênese entre os adenomas polipóides e não-polipóides através da quantificação 41,8 (15,8 - 71,9) vs 22 (16 - 40) e estimativa da extensão microvascular 24 (6,5-142,2) vs 17,5 (4,4-54,7), respectivamente. Conclusão: a utilização da análise digital de imagem e estereologia acrescentou maior objetividade e eficácia na metodologia de avaliação angiogênica, pois permitiu a precisa segmentação das áreas hipervasculares, a representação da morfologia tridimensional característica do suprimento vascular e a identificação de diferenças na microvascularização nas etapas evolutivas do câncer colorretal.

Plane detection from monocular image sequences

AIRES, Kelson R. T. ; ARAÚJO, Hélder J. ; MEDEIROS, Adelardo A. D. . Plane Detection from Monocular Image Sequences. In: VISUALIZATION, IMAGING AND IMAGE PROCESSING, 2008, Palma de Mallorca, Spain. Proceedings..., Palma de Mallorca: VIIP, 2008

Uma fundamentação matemática para processamento digital de sinais intervalares

This work deals with a mathematical fundament for digital signal processing under point view of interval mathematics. Intend treat the open problem of precision and repesention of data in digital systems, with a intertval version of signals representation. Signals processing is a rich and complex area, therefore, this work makes a cutting with focus in systems linear invariant in the time. A vast literature in the area exists, but, some concepts in interval mathematics need to be redefined or to be elaborated for the construction of a solid theory of interval signal processing. We will construct a basic fundaments for signal processing in the interval version, such as basic properties linearity, stability, causality, a version to intervalar of linear systems e its properties. They will be presented interval versions of the convolution and the Z-transform. Will be made analysis of convergences of systems using interval Z-transform , a essentially interval distance, interval complex numbers , application in a interval filter.

Análise da imagem digital para estimativa da área foliar em plantas de laranja Pêra

Objetivou-se, com o trabalho, avaliar dois métodos de estimativa da área foliar, em plantas de laranja Pêra, pela análise da imagem digital obtida com scanner e câmera fotográfica digital. Para determinar a área das folhas, um grupo de discos foi colocado sobre um leitor de scanner, sendo que a imagem obtida foi armazenada. Os mesmos grupos de discos foram fixados sobre cartolina branca e fotografados com câmera fotográfica digital. As imagens obtidas da câmera fotográfica e do scanner foram processadas utilizando ferramentas de um editor de imagem que permite a contagem de pixels de determinada cor, no caso verde. Para a comparação dos métodos, os discos foram submetidos a integrador óptico de área foliar modelo LICOR-3100, utilizando os mesmos agrupamentos. Foram coletadas 20 folhas (cinco em cada quadrante da planta) por parcela de um experimento para comparação de fertilizantes comerciais e doses de zinco, aplicados via foliar, em plantas de sete anos de idade. O experimento foi composto de sete tratamentos e quatro repetições, num total de 28 parcelas. Os dois métodos apresentaram alta correlação com a área estimada pelo integrador óptico de área, considerado como método de referência. O método da análise da imagem obtida com câmera fotográfica, na resolução de 5.0 megapixel, foi mais precisa quando comparada à área estimada pelo integrador óptico de área.

Compressão auto-adaptativa de imagens coloridas

Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

Escalabilidade Paralela de um Algoritmo de Migração Reversa no Tempo (RTM) Pré-empilhamento

The seismic method is of extreme importance in geophysics. Mainly associated with oil exploration, this line of research focuses most of all investment in this area. The acquisition, processing and interpretation of seismic data are the parts that instantiate a seismic study. Seismic processing in particular is focused on the imaging that represents the geological structures in subsurface. Seismic processing has evolved significantly in recent decades due to the demands of the oil industry, and also due to the technological advances of hardware that achieved higher storage and digital information processing capabilities, which enabled the development of more sophisticated processing algorithms such as the ones that use of parallel architectures. One of the most important steps in seismic processing is imaging. Migration of seismic data is one of the techniques used for imaging, with the goal of obtaining a seismic section image that represents the geological structures the most accurately and faithfully as possible. The result of migration is a 2D or 3D image which it is possible to identify faults and salt domes among other structures of interest, such as potential hydrocarbon reservoirs. However, a migration fulfilled with quality and accuracy may be a long time consuming process, due to the mathematical algorithm heuristics and the extensive amount of data inputs and outputs involved in this process, which may take days, weeks and even months of uninterrupted execution on the supercomputers, representing large computational and financial costs, that could derail the implementation of these methods. Aiming at performance improvement, this work conducted the core parallelization of a Reverse Time Migration (RTM) algorithm, using the parallel programming model Open Multi-Processing (OpenMP), due to the large computational effort required by this migration technique. Furthermore, analyzes such as speedup, efficiency were performed, and ultimately, the identification of the algorithmic scalability degree with respect to the technological advancement expected by future processors

Estado nutricional em nitrogênio da grama esmeralda avaliado por meio do teor foliar, clorofilômetro e imagem digital, em área adubada com lodo de esgoto

A intensidade da cor verde da folha pode ser alternativa para estimar a concentração de N na planta, devido à relação entre o teor de clorofila e o de N no tecido foliar. Objetivou-se neste trabalho avaliar índices da cor verde da grama esmeralda obtidos da análise da imagem digital e pelo uso do clorofilômetro para predizer o estado nutricional em N fornecido pelo lodo de esgoto. O experimento foi instalado e desenvolvido em uma propriedade comercial de grama esmeralda, localizada na cidade de Itapetininga (SP). O delineamento experimental foi em blocos casualizados, com quatro repetições e cinco doses de lodo de esgoto: 0, 10, 20, 30 e 40 Mg ha-1, base seca. As doses de lodo aplicadas correspondem a 100, 200, 300 e 400 kg ha-1 de nitrogênio disponível. Foram avaliadas as concentrações de N e a intensidade de coloração verde da folha pelo uso do clorofilômetro (ICV) e por meio da análise da imagem digital (G, H e ICVE) aos 45, 105 e 165 dias após a aplicação do lodo. Os valores de intensidade obtidos foram correlacionados com a concentração de N na lâmina foliar e com a taxa de cobertura do solo determinada nas mesmas épocas. A aplicação de doses de lodo de esgoto proporcionou aumento dos índices de cor verde e da concentração de N nas folhas da grama esmeralda. A concentração de N na lâmina foliar pode auxiliar a adubação nitrogenada em cobertura, pois proporcionou altas correlações com a taxa de cobertura do solo. O matiz (H) obtido com a imagem digital e a intensidade de cor verde da folha (ICV) obtida com o clorofilômetro correlacionaram-se com a concentração de N e com a taxa de cobertura do solo e, dessa forma, podem servir como índices na recomendação da adubação nitrogenada.

Segmentação fuzzy de imagens coloridas com características texturais: uma aplicação a rochas sedimentares

Image segmentation is the process of labeling pixels on di erent objects, an important step in many image processing systems. This work proposes a clustering method for the segmentation of color digital images with textural features. This is done by reducing the dimensionality of histograms of color images and using the Skew Divergence to calculate the fuzzy a nity functions. This approach is appropriate for segmenting images that have colorful textural features such as geological, dermoscopic and other natural images, as images containing mountains, grass or forests. Furthermore, experimental results of colored texture clustering using images of aquifers' sedimentary porous rocks are presented and analyzed in terms of precision to verify its e ectiveness.

Caracterização morfológica e sedimentologica da plataforma, continental brasileira adjacente aos municípios de Fortim, Aracati e Icapuí- CE

The study area is located on the Brazilian Continental Shelf adjacent to Ceará State, inserted in the submerged Potiguar Basin. This area was submitted to extensional efforts during Upper Cretaceous, associated to the begining of the rifting that resulted in African and South American Continent separation. The main goal of this research was to better understand the sedimentary and geomorphological characteristics of the continental shelf adjacent to Fortim, Aracati and Icapuí (Ceará State). The used data base included geophysical (sides scan sonar and bathymetry studies) and sedimentological survey, associated to satellite image processing and interpretation. Inferences about suspended material and longshore drift was possible using satellite images, and differente bedforms were characterized such as: different kinds of dunes (longitudinal, cross and oblique), bioclastic banks, paleochannels, flat and rock bottom. The researched area comprehended about 2509,13 km2, where 6 different sedimentary facies, based on sediment composition and texture, could be recognized, such as: Bioclastic Sand, Siliciclastic Sand, Biosiliciclastic Sand, Bioclastic gravel, Biosiliciclastic sand with granule and gravel, and Silicibioclastic sand with granule and gravel. The integration of bathymetric, satellite image, side scan sonar and sedimentological data allow us a better characterization of this continental shelf area, as to advance in the knowledge of the continental shelf of the state of Ceara, a very important area to the oil industry because of its potential exploration and e exploitation, and to environmental survey as well

Avaliação da posição do supercílio por medidas angulares

OBJETIVO: Avaliar a posição do supercílio em diferentes idades, utilizando medidas angulares. MÉTODOS: Foram avaliados indivíduos com idade de 4 a 6 anos (Grupo de crianças) e igual ou superior a 50 anos (Grupo de idosos), separados em faixas etárias, avaliando-se a posição do supercílio por meio de imagens digitais, utilizando medidas angulares. As imagens foram tomadas em posição primária do olhar, utilizando filmadora Sony Lithium, e posteriormente transferidas para computador MacIntosh G4 e processadas pelo programa NIH 1,58. Os parâmetros analisados foram: ângulo interno, externo e vertical da cauda do supercílio. As comparações foram entre sexos, faixas etárias e lateralidade. Os resultados obtidos foram submetidos à análise estatística. RESULTADOS: A comparação das medidas angulares mostrou que houve diferença significativa na posição da cauda do supercílio entre os grupos estudados quando comparados dentro do grupo com faixa etária semelhante. Porém, comparando-se crianças e adultos, houve diferença em todos os tipos de ângulos estudados. CONCLUSÕES: A posição do supercílio avaliada por medidas angulares mostrou diferenças entre crianças e idosos, revelando associação positiva com a idade.