Seleção de features guiada por atenção visual em imagens com fóvea

Visual attention is a very important task in autonomous robotics, but, because of its complexity, the processing time required is significant. We propose an architecture for feature selection using foveated images that is guided by visual attention tasks and that reduces the processing time required to perform these tasks. Our system can be applied in bottom-up or top-down visual attention. The foveated model determines which scales are to be used on the feature extraction algorithm. The system is able to discard features that are not extremely necessary for the tasks, thus, reducing the processing time. If the fovea is correctly placed, then it is possible to reduce the processing time without compromising the quality of the tasks outputs. The distance of the fovea from the object is also analyzed. If the visual system loses the tracking in top-down attention, basic strategies of fovea placement can be applied. Experiments have shown that it is possible to reduce up to 60% the processing time with this approach. To validate the method, we tested it with the feature algorithm known as Speeded Up Robust Features (SURF), one of the most efficient approaches for feature extraction. With the proposed architecture, we can accomplish real time requirements of robotics vision, mainly to be applied in autonomous robotics

Algoritmo SOM com estrutura hierárquica e dinâmica aplicado a compressão de imagens

ln this work the implementation of the SOM (Self Organizing Maps) algorithm or Kohonen neural network is presented in the form of hierarchical structures, applied to the compression of images. The main objective of this approach is to develop an Hierarchical SOM algorithm with static structure and another one with dynamic structure to generate codebooks (books of codes) in the process of the image Vector Quantization (VQ), reducing the time of processing and obtaining a good rate of compression of images with a minimum degradation of the quality in relation to the original image. Both self-organizing neural networks developed here, were denominated HSOM, for static case, and DHSOM, for the dynamic case. ln the first form, the hierarchical structure is previously defined and in the later this structure grows in an automatic way in agreement with heuristic rules that explore the data of the training group without use of external parameters. For the network, the heuristic mIes determine the dynamics of growth, the pruning of ramifications criteria, the flexibility and the size of children maps. The LBO (Linde-Buzo-Oray) algorithm or K-means, one ofthe more used algorithms to develop codebook for Vector Quantization, was used together with the algorithm of Kohonen in its basic form, that is, not hierarchical, as a reference to compare the performance of the algorithms here proposed. A performance analysis between the two hierarchical structures is also accomplished in this work. The efficiency of the proposed processing is verified by the reduction in the complexity computational compared to the traditional algorithms, as well as, through the quantitative analysis of the images reconstructed in function of the parameters: (PSNR) peak signal-to-noise ratio and (MSE) medium squared error

Sistema inteligente para detecção de manchas de óleo na superfície marinha através de imagens de SAR

Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents

Compressão Seletiva de Imagens Coloridas com Detecção Automática de Regiões de Interesse

There has been an increasing tendency on the use of selective image compression, since several applications make use of digital images and the loss of information in certain regions is not allowed in some cases. However, there are applications in which these images are captured and stored automatically making it impossible to the user to select the regions of interest to be compressed in a lossless manner. A possible solution for this matter would be the automatic selection of these regions, a very difficult problem to solve in general cases. Nevertheless, it is possible to use intelligent techniques to detect these regions in specific cases. This work proposes a selective color image compression method in which regions of interest, previously chosen, are compressed in a lossless manner. This method uses the wavelet transform to decorrelate the pixels of the image, competitive neural network to make a vectorial quantization, mathematical morphology, and Huffman adaptive coding. There are two options for automatic detection in addition to the manual one: a method of texture segmentation, in which the highest frequency texture is selected to be the region of interest, and a new face detection method where the region of the face will be lossless compressed. The results show that both can be successfully used with the compression method, giving the map of the region of interest as an input

Avaliação do potencial das imagens quickbird ortorretificadas para o mapeamento das propriedades localizadas na área de expansão e vazios urbanos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Renderizações não fotorealísticas para estilização de imagens e vídeos usando areia colorida

Non-Photorealisitc Rendering (NPR) is a class of techniques that aims to reproduce artistic techniques, trying to express feelings and moods on the rendered scenes, giving an aspect of that they had been made "by hand". Another way of defining NPR is that it is the processing of scenes, images or videos into artwork, generating scenes, images or videos that can have the visual appeal of pieces of art, expressing the visual and emotional characteristics of artistic styles. This dissertation presents a new method of NPR for stylization of images and videos, based on a typical artistic expression of the Northeast region of Brazil, that uses colored sand to compose landscape images on the inner surface of glass bottles. This method is comprised by one technique for generating 2D procedural textures of sand, and two techniques that mimic effects created by the artists using their tools. It also presents a method for generating 21 2D animations in sandbox from the stylized video. The temporal coherence within these stylized videos can be enforced on individual objects with the aid of a video segmentation algorithm. The present techniques in this work were used on stylization of synthetic and real videos, something close to impossible to be produced by artist in real life

Monitoramento geoambiental do estuário do Rio Paraíba do Norte - PB por meio da cartografia temática digital e de produtos de sensoriamento remoto

The North Paraíba River Estuary, located in the eastern portion of the Paraíba State, Northeast Brazil, on coordinates 34º50 00 -34º57 30 S and 6º55 00 -7º7 30 W, constitutes a fluvio-marine plain formed by the North Paraíba River and its tributaries Sanhauá, Paroeira, Mandacaru, Tiriri, Tambiá, Ribeira and Guia. This estuary comprises an area of about 260 km2. Increasing human demands on the estuary area and inadequate environment managing have generated conflicts. The present work main purpose is to evaluate the geodynamic evolution of the North Paraíba River Estuary in the period from 1969 to 2001, using digital image processing techniques, thematic digital cartography and multitemporal data integration, combined to geological-geophysical field surveys. The SUDENE cartographic database, converted to digital format were, used to obtain occupation and topographic maps from 1969 and to generate a Digital Elevation Model (DEM). Digital Landsat 7 ETM+ and Spot HRVIR-PAN satellite images interpretation allowed the environmental characterization of the estuary. The most important digital processing results were achieved color composites RGB 5-4-3, 5-3-1, 5-2-NDWI and band ratio 7/4-5/3-4/2, 5/7-3/1-5/4). In addition the fusion image technique RGBI was used by the inclusion of the Spot HRVRI and Landsat 7 ETM+ panchromatic band on I layer with RGB triplets 5-4-3, 5-3-1 and 5/7-3/1-5/4. The DEM and digital images integration allowed the identification of seven geomorphological units: coastal tableland, flowing tray, tide plain, fluvial terrace, submerged dune, beach plain and beach). Both Side Scan Sonar and Echosound were used to analyse underwater surface and bedforms of the estuarine channel, sand predominance (fine to very fine) and 2D dune features 5 m wide and 0.5 m height. This investigation characterized the estuary as an environment dominated by regimen of average flow. The channel depth varies between 1 m and 11 m, being this last quota reached in the area of Porto de Cabedelo. The chanel estuary is relatively shallow, with erosion evidences mainly on its superior portion, attested by sand banks exposed during the low tide. Multitemporal digital maps from 1969 and 2001 integration were obtained through geoprocessing techniques, resulting the geodynamic evolution of the estuary based on landuse, DEM geomorphology and bathymetric maps

Aquisição, processamento e análise de dados de sísmica de alta resolução na plataforma continental norte do Rio Grande do Norte: Vale inciso do rio açu

On the modern Continental Shelf to the north of Rio Grande do Norte state (NE Brazil) is located a paleo-valley, submerged during the last glacial sea-level lowstand, that marks continuation of the most important river of this area (Açu River). Despite the high level of exploration activity of oil industry, there is few information about shallow stratigraphy. Aiming to fill this gap, situated on the Neogene, was worked a marine seismic investigation, the development of a processing flow for high resolution data seismic, and the recognition of the main feature morphology of the study area: the incised valley of the River Açu. The acquisition of shallow seismic data was undertaken in conjunction with the laboratory of Marine Geology/Geophysics and Environmental Monitoring - GGEMMA of Federal University of Rio Grande do Norte UFRN, in SISPLAT project, where the geomorphological structure of the Rio paleovale Açu was the target of the investigation survey. The acquisition of geophysical data has been over the longitudinal and transverse sections, which were subsequently submitted to the processing, hitherto little-used and / or few addressed in the literature, which provided a much higher quality result with the raw data. Once proposed for the flow data was developed and applied to the data of X-Star (acoustic sensor), using available resources of the program ReflexW 4.5 A surface fluvial architecture has been constructed from the bathymetric data and remote sensing image fused and draped over Digital Elevation Models to create three-dimensional (3D) perspective views that are used to analyze the 3D geometry geological features and provide the mapping morphologically defined. The results are expressed in the analysis of seismic sections that extend over the region of the continental shelf and upper slope from mouth of the Açu River to the shelf edge, providing the identification / quantification of geometrical features such as depth, thickness, horizons and units seismic stratigraphyc area, with emphasis has been placed on the palaeoenvironmental interpretation of discordance limit and fill sediment of the incised valley, control by structural elements, and marked by the influence of changes in the sea level. The interpretation of the evolution of this river is worth can bring information to enable more precise descriptions and interpretations, which describes the palaeoenvironmental controls influencing incised valley evolution and preservation to provide a better comprehensive understanding of this reservoir analog system

Ajuste radiométrico de imagens aéreas digitais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Concepção, desenvolvimento e aplicação do banco de imagens georreferenciadas no contexto do mapeamento terrestre móvel

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Integração de imagens vetoriais e matriciais na visualização dos levantamentos realizados com a unidade móvel de mapeamento digital

Pós-graduação em Ciências Cartográficas - FCT

Utilização de equações diferenciais parciais no tratamento de imagens orbitais

Pós-graduação em Ciências Cartográficas - FCT

Geração automática de estereomodelos a partir de imagens digitais georreferenciadas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Uma análise da infestação por plantas aquáticas utilizando imagens multiescala e redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geoestística e sensoriamento remoto na classificação de imagens em áreas cultivadas com citros

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)