Class-specific metrics for multidimensional data projection applied to CBIR

Content-based image retrieval is still a challenging issue due to the inherent complexity of images and choice of the most discriminant descriptors. Recent developments in the field have introduced multidimensional projections to burst accuracy in the retrieval process, but many issues such as introduction of pattern recognition tasks and deeper user intervention to assist the process of choosing the most discriminant features still remain unaddressed. In this paper, we present a novel framework to CBIR that combines pattern recognition tasks, class-specific metrics, and multidimensional projection to devise an effective and interactive image retrieval system. User interaction plays an essential role in the computation of the final multidimensional projection from which image retrieval will be attained. Results have shown that the proposed approach outperforms existing methods, turning out to be a very attractive alternative for managing image data sets.

Interactive quadrangulation with reeb atlases and connectivity textures

Creating high-quality quad meshes from triangulated surfaces is a highly nontrivial task that necessitates consideration of various application specific metrics of quality. In our work, we follow the premise that automatic reconstruction techniques may not generate outputs meeting all the subjective quality expectations of the user. Instead, we put the user at the center of the process by providing a flexible, interactive approach to quadrangulation design. By combining scalar field topology and combinatorial connectivity techniques, we present a new framework, following a coarse to fine design philosophy, which allows for explicit control of the subjective quality criteria on the output quad mesh, at interactive rates. Our quadrangulation framework uses the new notion of Reeb atlas editing, to define with a small amount of interactions a coarse quadrangulation of the model, capturing the main features of the shape, with user prescribed extraordinary vertices and alignment. Fine grain tuning is easily achieved with the notion of connectivity texturing, which allows for additional extraordinary vertices specification and explicit feature alignment, to capture the high-frequency geometries. Experiments demonstrate the interactivity and flexibility of our approach, as well as its ability to generate quad meshes of arbitrary resolution with high-quality statistics, while meeting the user's own subjective requirements.

Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps

Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.

Chitosan-based biomaterials used in critical-size bone defects: radiographic study in rat's calvaria

OBJETIVO: Este estudo avaliou através de imagens radiográficas digitais, a ação de biomateriais de quitosana e de cloridrato de quitosana, com baixo e alto peso molecular, utilizados na correção de defeitos ósseos de tamanho crítico (DOTC)em calvária de ratos. MATERIAL E MÉTODO: DOTCs com 8 mm de diâmetro foram criados cirurgicamente na calvária de 50 ratos Holtzman. Em 10 animais o defeito foi preenchido foram preenchidos com coágulo sanguíneo (controle negativo). Os 40 animais restantes foram divididos de acordo com o biomaterial utilizado no preenchimento do defeito (quitosana de baixo peso e de alto peso molecular, e cloridrato de quitosana de baixo e de alto peso molecular), e foram avaliados em dois períodos experimentais (15 e 60 dias), totalizando 5 animais/biomaterial/período de avaliação. RESULTADO: A avaliação radiográfica foi feita utilizando duas radiografias digitais do crânio do animal: uma tomada logo após o defeito ósseo ser criado e a outra no momento do sacrifício. Nessas imagens, foi avaliada a densidade óssea radiográfica inicial e a final na área do defeito, que foram comparadas. As análises na densidade óssea radiográfica indicaram aumento da densidade óssea radiográfica dos DOTCs tratados para todos os biomateriais testados, em ambos os períodos. Resultados semelhantes foram encontrados no grupo controle. CONCLUSÃO: Conclui-se que os biomateriais de quitosana testados não foram capazes de aumentar a densidade radiográfica em DOTC realizados em calvária de ratos.

PRoSPer: perceptual similarity queries in medical CBIR systems through user profiles

In this paper, we present a novel approach to perform similarity queries over medical images, maintaining the semantics of a given query posted by the user. Content-based image retrieval systems relying on relevance feedback techniques usually request the users to label relevant/irrelevant images. Thus, we present a highly effective strategy to survey user profiles, taking advantage of such labeling to implicitly gather the user perceptual similarity. The profiles maintain the settings desired for each user, allowing tuning of the similarity assessment, which encompasses the dynamic change of the distance function employed through an interactive process. Experiments on medical images show that the method is effective and can improve the decision making process during analysis.

QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.

Combining fractal and deterministic walkers for texture analysis and classification

In this paper,we present a novel texture analysis method based on deterministic partially self-avoiding walks and fractal dimension theory. After finding the attractors of the image (set of pixels) using deterministic partially self-avoiding walks, they are dilated in direction to the whole image by adding pixels according to their relevance. The relevance of each pixel is calculated as the shortest path between the pixel and the pixels that belongs to the attractors. The proposed texture analysis method is demonstrated to outperform popular and state-of-the-art methods (e.g. Fourier descriptors, occurrence matrix, Gabor filter and local binary patterns) as well as deterministic tourist walk method and recent fractal methods using well-known texture image datasets.

Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks

Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.

Análise das distorções em leituras angulares de imagens fotográficas

CONTEXTUALIZAÇÃO: A biofotogrametria é uma técnica difundida na área da saúde e, apesar dos cuidados metodológicos, há distorções nas leituras angulares das imagens fotográficas. OBJETIVO: Mensurar o erro das medidas angulares em imagens fotográficas com diferentes resoluções digitais em um objeto com ângulos pré-demarcados. MÉTODOS: Utilizou-se uma esfera de borracha com 52 cm de circunferência. O objeto foi previamente demarcado com ângulos de 10º, 30º, 60º e 90º, e os registros fotográficos foram realizados com o eixo focal da câmera a três metros de distância e perpendicular ao objeto, sem utilização de zoom óptico e com resolução de 3, 5 e 10 Megapixels (Mp). Todos os registros fotográficos foram armazenados, e os valores angulares foram analisados por um experimentador previamente treinado, utilizando o programa ImageJ. As aferições das medidas foram realizadas duas vezes, com intervalo de 15 dias entre elas. Posteriormente, foram calculados os valores de acurácia, erro relativo e em graus, precisão e Coeficiente de Correlação Intraclasse (ICC). RESULTADOS: Quando analisado o ângulo de 10º, a média da acurácia das medidas foi maior para os registros com resolução de 3 Mp em relação às resoluções de 5 e 10 Mp. O ICC foi considerado excelente para as três resoluções de imagem analisadas e, em relação aos ângulos analisados nos registros fotográficos, pôde-se verificar maior acurácia, menor erro relativo e em graus e maior precisão para o ângulo de 90º, independentemente da resolução da imagem. CONCLUSÃO: Os registros fotográficos realizados com a resolução de 3 Mp proporcionaram medidas de maiores valores de acurácia e precisão e menores valores de erro, sugerindo ser a resolução mais adequada para gerar imagem de ângulos de 10º e 30º.

Produção e preservação de conteúdos digitais: montagem, operação e gestão de laboratórios de digitalização

Com o objetivo de preservar e disseminar o acervo da Universidade de São Paulo, foi criada a Biblioteca de Obras Raras e Especiais. Contamos atualmente com cerca de 2500 obras digitalizadas em parceria com a Brasiliana USP e apoio da FAPESP. Estas obras estão disponibilizadas online, para consulta aberta pelo amplo público, promovendo assim acesso ao conhecimento. Utilizamos para isto o Corisco, uma plataforma desenvolvida por pesquisadores da Brasiliana USP baseada em DSpace, software de código aberto e com recursos que promovem a interoperabilidade com outras bases. O DSpace é atualmente o aplicativo de Repositório Digital de código aberto mais utilizado nas Universidades ao redor do mundo. As capturas originais em alta resolução das obras são armazenadas e indexadas para fins de preservação. Em outra frente, realiza-se o tratamento, compactação e reconhecimento ótico de caracteres nas imagens, para que então as obras possam ser disponibilizadas na internet com o recurso de busca no conteúdo. A consulta é livre e gratuita, garantindo assim, além da preservação, o acesso ao conhecimento pela comunidade acadêmica e público em geral.