996 resultados para Processamento de imagens - Técnicas digitais
Resumo:
Este trabalho apresenta o desenvolvimento de uma ferramenta computacional de apoio ao diagnóstico através de imagens ecocardiográficas, denominada de “Echo Offline”. O “Echo Offline” foi projetado para mensuração de grandezas lineares em imagens ecocardiográficas digitais, possibilitando a realização de diagnósticos pós-exame e a integração dos dados colhidos no banco de dados da instituição médica. Um estudo transversal contemporâneo e aleatório foi realizado com uma população de quarenta e nove pacientes submetidos a exames ecocardiográficos, as imagens resultantes deste exame foram digitalizadas e um médico especialista mensurou um conjunto de variáveis pré-definidas utilizando o método convencional, ou seja, usando as facilidades oferecidas pelo equipamento de ultra-som comercial. Um segundo médico especialista produziu outros dois conjuntos de dados utilizando o “Echo offline” e desta forma foi possível avaliar a exatidão e a repetibilidade das medidas realizadas pela ferramenta “Echo offline”. O “Echo offline” apresentou uma elevada concordância com o método convencional e apresentou significativa redução no tempo de realização das medidas.
Resumo:
A velocidade de veículos em vias públicas pode ser obtida de diversas formas. A técnica mais usada é de laços magnéticos, onde se instalam sensores sob o asfalto. Entretanto, esta técnica apresenta desvantagens, tais como, a não detecção de motocicletas (o campo magnético gerado por este tipo de veículo é imperceptível ao sistema) e dificuldade de manutenção da via (se o órgão publico tiver que mexer numa rede cloacal que passa perto dos sensores, por exemplo, pode ser necessário reinstalá-los). Nesse contexto, este trabalho propõe-se a discutir uma nova maneira de se calcular a velocidade de veículos, através do processamento de imagens. Para isto, torna-se fundamental conhecer os conceitos que envolvem as técnicas mais utilizadas (além dos laços magnéticos, a captura de dois quadros consecutivos e o sistema Doppler), os equipamentos disponíveis no mercado (Pardais, Lombadas Eletrônicas, Bandeiras, Caetanos e Radares) e a forma como o INMETRO faz a aferição destes equipamentos. O estudo apresenta, igualmente, os principais fundamentos relacionados ao processamento digital de imagens, com especial atenção para detecção de bordas, de forma que seja possível avaliar a nova técnica proposta, que calcula a velocidade a partir de um único quadro. O presente trabalho objetiva apresentar o Pardalzito como alternativa técnica inovadora para aplicação de um, sistema que implementa esta idéia na prática.
Resumo:
In this work, spoke about the importance of image compression for the industry, it is known that processing and image storage is always a challenge in petrobrás to optimize the storage time and store a maximum number of images and data. We present an interactive system for processing and storing images in the wavelet domain and an interface for digital image processing. The proposal is based on the Peano function and wavelet transform in 1D. The storage system aims to optimize the computational space, both for storage and for transmission of images. Being necessary to the application of the Peano function to linearize the images and the 1D wavelet transform to decompose it. These applications allow you to extract relevant information for the storage of an image with a lower computational cost and with a very small margin of error when comparing the images, original and processed, ie, there is little loss of quality when applying the processing system presented . The results obtained from the information extracted from the images are displayed in a graphical interface. It is through the graphical user interface that the user uses the files to view and analyze the results of the programs directly on the computer screen without the worry of dealing with the source code. The graphical user interface, programs for image processing via Peano Function and Wavelet Transform 1D, were developed in Java language, allowing a direct exchange of information between them and the user
Resumo:
With the rapid growth of databases of various types (text, multimedia, etc..), There exist a need to propose methods for ordering, access and retrieve data in a simple and fast way. The images databases, in addition to these needs, require a representation of the images so that the semantic content characteristics are considered. Accordingly, several proposals such as the textual annotations based retrieval has been made. In the annotations approach, the recovery is based on the comparison between the textual description that a user can make of images and descriptions of the images stored in database. Among its drawbacks, it is noted that the textual description is very dependent on the observer, in addition to the computational effort required to describe all the images in database. Another approach is the content based image retrieval - CBIR, where each image is represented by low-level features such as: color, shape, texture, etc. In this sense, the results in the area of CBIR has been very promising. However, the representation of the images semantic by low-level features is an open problem. New algorithms for the extraction of features as well as new methods of indexing have been proposed in the literature. However, these algorithms become increasingly complex. So, doing an analysis, it is natural to ask whether there is a relationship between semantics and low-level features extracted in an image? and if there is a relationship, which descriptors better represent the semantic? which leads us to a new question: how to use descriptors to represent the content of the images?. The work presented in this thesis, proposes a method to analyze the relationship between low-level descriptors and semantics in an attempt to answer the questions before. Still, it was observed that there are three possibilities of indexing images: Using composed characteristic vectors, using parallel and independent index structures (for each descriptor or set of them) and using characteristic vectors sorted in sequential order. Thus, the first two forms have been widely studied and applied in literature, but there were no records of the third way has even been explored. So this thesis also proposes to index using a sequential structure of descriptors and also the order of these descriptors should be based on the relationship that exists between each descriptor and semantics of the users. Finally, the proposed index in this thesis revealed better than the traditional approachs and yet, was showed experimentally that the order in this sequence is important and there is a direct relationship between this order and the relationship of low-level descriptors with the semantics of the users
Resumo:
We propose a multi-resolution, coarse-to-fine approach for stereo matching, where the first matching happens at a different depth for each pixel. The proposed technique has the potential of attenuating several problems faced by the constant depth algorithm, making it possible to reduce the number of errors or the number of comparations needed to get equivalent results. Several experiments were performed to demonstrate the method efficiency, including comparison with the traditional plain correlation technique, where the multi-resolution matching with variable depth, proposed here, generated better results with a smaller processing time
Resumo:
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
Resumo:
A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms
Resumo:
A 3D binary image is considered well-composed if, and only if, the union of the faces shared by the foreground and background voxels of the image is a surface in R3. Wellcomposed images have some desirable topological properties, which allow us to simplify and optimize algorithms that are widely used in computer graphics, computer vision and image processing. These advantages have fostered the development of algorithms to repair bi-dimensional (2D) and three-dimensional (3D) images that are not well-composed. These algorithms are known as repairing algorithms. In this dissertation, we propose two repairing algorithms, one randomized and one deterministic. Both algorithms are capable of making topological repairs in 3D binary images, producing well-composed images similar to the original images. The key idea behind both algorithms is to iteratively change the assigned color of some points in the input image from 0 (background)to 1 (foreground) until the image becomes well-composed. The points whose colors are changed by the algorithms are chosen according to their values in the fuzzy connectivity map resulting from the image segmentation process. The use of the fuzzy connectivity map ensures that a subset of points chosen by the algorithm at any given iteration is the one with the least affinity with the background among all possible choices
Resumo:
Image segmentation is the process of subdiving an image into constituent regions or objects that have similar features. In video segmentation, more than subdividing the frames in object that have similar features, there is a consistency requirement among segmentations of successive frames of the video. Fuzzy segmentation is a region growing technique that assigns to each element in an image (which may have been corrupted by noise and/or shading) a grade of membership between 0 and 1 to an object. In this work we present an application that uses a fuzzy segmentation algorithm to identify and select particles in micrographs and an extension of the algorithm to perform video segmentation. Here, we treat a video shot is treated as a three-dimensional volume with different z slices being occupied by different frames of the video shot. The volume is interactively segmented based on selected seed elements, that will determine the affinity functions based on their motion and color properties. The color information can be extracted from a specific color space or from three channels of a set of color models that are selected based on the correlation of the information from all channels. The motion information is provided into the form of dense optical flows maps. Finally, segmentation of real and synthetic videos and their application in a non-photorealistic rendering (NPR) toll are presented
Resumo:
OBJETIVO: Quantificar, usando o sistema de imagem digital, medidas palpebrais antes e após a cirurgia de blefaroplastia superior. MÉTODOS: Foram avaliadas 18 pálpebras de 9 pacientes atendidas no HC da FMB - UNESP, com idade entre 40 a 75 anos, do sexo feminino, portadoras de dermatocálase. Foram obtidas fotografias das pacientes antes e após 60 dias da blefaroplastia da pálpebra superior. As imagens foram transferidas para um computador e analisadas pelo programa Scion Image Frame Grabber. Os parâmetros avaliados foram: a altura da fenda palpebral em posição primária do olhar, altura do sulco palpebral superior e o ângulo palpebral lateral antes e depois de 60 dias da realização da cirurgia de blefaroplastia superior. RESULTADOS: Após a cirurgia, houve aumento da altura da fenda palpebral e do sulco palpebral superior. Contudo, o ângulo palpebral lateral não se alterou. CONCLUSÃO: A posição palpebral se altera após a blefaroplastia e o processamento de imagens digitais possibilita quantificar estas alterações, mensurando os resultados obtidos com a cirurgia.
Resumo:
OBJETIVOS: Avaliar o posicionamento palpebral em portadores de cavidade anoftálmica com e sem prótese ocular externa, utilizando o processamento de imagem digital. MÉTODOS: Dezoito pacientes foram avaliados qualitativa e quantitativamente na Faculdade de Medicina de Botucatu - Universidade Estadual Paulista - UNESP, com e sem a prótese externa. Usando imagens obtidas por filmadora e processadas usando o programa Scion Image, mediu-se a altura do sulco palpebral superior, a altura da fenda palpebral e os ângulos palpebrais dos cantos interno e externo. RESULTADOS: Pseudo-estrabismo e sulco palpebral superior profundo foram as alterações mais freqüentes ao exame externo. Houve diferença significativa em todas as variáveis estudadas, com diminuição da altura do sulco palpebral superior, aumento da área da fenda palpebral e aumento dos ângulos palpebrais interno e externo quando o paciente estava usando a prótese externa. CONCLUSÃO: Todos os pacientes avaliados apresentaram algum tipo de anormalidade órbito-palpebral, o que reflete a dificuldade em se proporcionar ao portador de cavidade anoftálmica um aspecto idêntico ao que existe na órbita normal. O processamento de imagens digitais permitiu avaliação objetiva das dimensões óculo-palpebrais, o que poderá contribuir nas avaliações seqüenciais dos portadores de cavidade anoftálmica.
Resumo:
Pós-graduação em Ciências Cartográficas - FCT
Resumo:
Pós-graduação em Biologia Geral e Aplicada - IBB
Resumo:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)