Evaluation of 2D image reconstruction using fan-beam FBP algorithm with no backprojection weight from WLP completed truncated projection data

This paper presents the image reconstruction using the fan-beam filtered backprojection (FBP) algorithm with no backprojection weight from windowed linear prediction (WLP) completed truncated projection data. The image reconstruction from truncated projections aims to reconstruct the object accurately from the available limited projection data. Due to the incomplete projection data, the reconstructed image contains truncation artifacts which extends into the region of interest (ROI) making the reconstructed image unsuitable for further use. Data completion techniques have been shown to be effective in such situations. We use windowed linear prediction technique for projection completion and then use the fan-beam FBP algorithm with no backprojection weight for the 2-D image reconstruction. We evaluate the quality of the reconstructed image using fan-beam FBP algorithm with no backprojection weight after WLP completion.

Foto-assemblage

FOTO-ASSEMBLAGE consiste em nomenclatura sugestionada para definir os trabalhos que tenho produzido a partir da junção de fotografias digitais. As elaborações e fundamentações desses trabalhos representam também o cerne das pesquisas que resultaram na presente dissertação. Em princípio, o termo foto-assemblage haveria de referir-se a questões técnicas ou formais dessa prática. Contudo, ao desenvolver as pesquisas alguns procedimentos acabaram por determinar certas nuances que revelaram aspectos comuns também em seus e conteúdos. Como resultado de construções artísticas juntando fotografias desde 2009, cheguei às composições sintéticas aqui apresentadas, construídas a partir de duas fotografias. Aventei o nome foto-assemblage por observar nas imagens resultantes ressalvas que as distinguiriam de certas convenções atribuídas à ideia de fotografia. Ao mesmo tempo, as referidas imagens proporiam um possível desdobramento ao entendimento de assemblage enquanto técnica artística. Ainda que não seja uma regra, fotografias revelam imagens de momentos. Em sua relação com a compreensão humana de tempo ou espaço, fotografias quase sempre contêm instâncias mínimas. Fotografias, contudo, podem ser também compreendidas como uma contração de um percurso de tempo. Toda imagem fotográfica pode ser assimilada como resultante de determinados acontecimentos anteriores e mesmo tida como elemento gerador de conseqüências futuras. Seguindo esse entendimento, o que proponho com a foto-assemblage é que essa lide com segmentos de tempo ou de espaço contidos numa mesma imagem. Essas fotografias originárias ganhariam uma nova atribuição, sendo retiradas de seu contexto original, serviriam de balizas do percurso de tempo ou espaço suprimido e subjetivado entre elas. Poeticamente, eventos ocorridos entre as fotografias originárias estariam contidos nas imagens produzidas. O termo assemblage foi incorporado às artes a partir de 1953, por Jean Dubuffet, para descrever trabalhos que seriam algo mais do que simples colagem. A ideia de assemblage se baseia no princípio de que todo e qualquer material ou objeto colhido de nosso mundo cotidiano pode ser incorporado a uma obra de arte, criando um novo conjunto, sem que perca seu sentido original. Esse objeto é arrancado de seu uso habitual e inserido num novo contexto, tecendo laços de relação com os demais elementos, construindo narrativas num novo ambiente, o da obra. Na ideia da foto-assemblage, entretanto, é sugerido uso das imagens fotográficas originárias não como objetos que estariam em um mundo cotidiano, mas sim como imagem na concepção do que seria uma entidade mental. Adoto como que uma visão mágica onde as imagens originárias e básicas estariam numa outra dimensão, num plano bidimensional, não manipulável por nós habitantes da tridimensionalidade. Nesse ambiente imaginário ou não, as fotografias são assentadas consolidando a foto-assemblage. Quando a foto-assemblage se concretiza, se corporifica numa mídia, sendo impressa para uma contemplação, ai então, passaria a integrar nosso mundo tridimensional. O resultado poderia ser admitido como um híbrido, uma terceira coisa, a partir de duas que já não se dissociam mais no ensejo de uma compreensão estética. Ao final da dissertação, apresento experiências práticas que resultaram em quatro séries de imagens em foto-assemblage. Cada série enfatiza aspectos peculiares do que denomino paisagem expandida, representando percursos de tempo, espaço ou trajetos entre o mundo concreto e mundos do inconsciente.

Autonomous extraction of optimal flame fronts in OH planar laser-induced fluorescence images.

The location of a flame front is often taken as the point of maximum OH gradient. Planar laser-induced fluorescence of OH can be used to obtain the flame front by extracting the points of maximum gradient. This operation is typically performed using an edge detection algorithm. The choice of operating parameters a priori poses significant problems of robustness when handling images with a range of signal-to-noise ratios. A statistical method of parameter selection originating in the image processing literature is detailed, and its merit for this application is demonstrated. A reduced search space method is proposed to decrease computational cost and render the technique viable for large data sets. This gives nearly identical output to the full method. These methods demonstrate substantial decreases in data rejection compared to the use of a priori parameters. These methods are viable for any application where maximum gradient contours must be accurately extracted from images of species or temperature, even at very low signal-to-noise ratios.

Combinations of Deformable Shape Prototypes

We propose to investigate a model-based technique for encoding non-rigid object classes in terms of object prototypes. Objects from the same class can be parameterized by identifying shape and appearance invariants of the class to devise low-level representations. The approach presented here creates a flexible model for an object class from a set of prototypes. This model is then used to estimate the parameters of low-level representation of novel objects as combinations of the prototype parameters. Variations in the object shape are modeled as non-rigid deformations. Appearance variations are modeled as intensity variations. In the training phase, the system is presented with several example prototype images. These prototype images are registered to a reference image by a finite element-based technique called Active Blobs. The deformations of the finite element model to register a prototype image with the reference image provide the shape description or shape vector for the prototype. The shape vector for each prototype, is then used to warp the prototype image onto the reference image and obtain the corresponding texture vector. The prototype texture vectors, being warped onto the same reference image have a pixel by pixel correspondence with each other and hence are "shape normalized". Given sufficient number of prototypes that exhibit appropriate in-class variations, the shape and the texture vectors define a linear prototype subspace that spans the object class. Each prototype is a vector in this subspace. The matching phase involves the estimation of a set of combination parameters for synthesis of the novel object by combining the prototype shape and texture vectors. The strengths of this technique lie in the combined estimation of both shape and appearance parameters. This is in contrast with the previous approaches where shape and appearance parameters were estimated separately.

MosaicShape: Stochastic Region Grouping with Shape Prior

A novel method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multi-scale curvature form, the proposed method identifies the target objects in images by grouping oversegmented image regions. The problem is formulated in a unified probabilistic framework and solved by a stochastic Markov Chain Monte Carlo (MCMC) mechanism. By this means, object segmentation and recognition are accomplished simultaneously. Within each sampling move during the simulation process,probabilistic region grouping operations are influenced by both the image information and the shape similarity constraint. The latter constraint is measured by a partial shape matching process. A generalized parallel algorithm by Barbu and Zhu,combined with a large sampling jump and other implementation improvements, greatly speeds up the overall stochastic process. The proposed method supports the segmentation and recognition of multiple occluded objects in images. Experimental results are provided for both synthetic and real images.

ART-EMAP: A Neural Network Architecture for Object Recognition by Evidence Accumulation

A new neural network architecture is introduced for the recognition of pattern classes after supervised and unsupervised learning. Applications include spatio-temporal image understanding and prediction and 3-D object recognition from a series of ambiguous 2-D views. The architecture, called ART-EMAP, achieves a synthesis of adaptive resonance theory (ART) and spatial and temporal evidence integration for dynamic predictive mapping (EMAP). ART-EMAP extends the capabilities of fuzzy ARTMAP in four incremental stages. Stage 1 introduces distributed pattern representation at a view category field. Stage 2 adds a decision criterion to the mapping between view and object categories, delaying identification of ambiguous objects when faced with a low confidence prediction. Stage 3 augments the system with a field where evidence accumulates in medium-term memory (MTM). Stage 4 adds an unsupervised learning process to fine-tune performance after the limited initial period of supervised network training. Each ART-EMAP stage is illustrated with a benchmark simulation example, using both noisy and noise-free data. A concluding set of simulations demonstrate ART-EMAP performance on a difficult 3-D object recognition problem.

Finding Texture Boundaries in Images

Texture provides one cue for identifying the physical cause of an intensity edge, such as occlusion, shadow, surface orientation or reflectance change. Marr, Julesz, and others have proposed that texture is represented by small lines or blobs, called 'textons' by Julesz [1981a], together with their attributes, such as orientation, elongation, and intensity. Psychophysical studies suggest that texture boundaries are perceived where distributions of attributes over neighborhoods of textons differ significantly. However, these studies, which deal with synthetic images, neglect to consider two important questions: How can these textons be extracted from images of natural scenes? And how, exactly, are texture boundaries then found? This thesis proposes answers to these questions by presenting an algorithm for computing blobs from natural images and a statistic for measuring the difference between two sample distributions of blob attributes. As part of the blob detection algorithm, methods for estimating image noise are presented, which are applicable to edge detection as well.

Image Based Rendering Using Algebraic Techniques

This paper presents an image-based rendering system using algebraic relations between different views of an object. The system uses pictures of an object taken from known positions. Given three such images it can generate "virtual'' ones as the object would look from any position near the ones that the two input images were taken from. The extrapolation from the example images can be up to about 60 degrees of rotation. The system is based on the trilinear constraints that bind any three view so fan object. As a side result, we propose two new methods for camera calibration. We developed and used one of them. We implemented the system and tested it on real images of objects and faces. We also show experimentally that even when only two images taken from unknown positions are given, the system can be used to render the object from other view points as long as we have a good estimate of the internal parameters of the camera used and we are able to find good correspondence between the example images. In addition, we present the relation between these algebraic constraints and a factorization method for shape and motion estimation. As a result we propose a method for motion estimation in the special case of orthographic projection.

An approach to coded structured light to obtain three dimensional information

The human visual ability to perceive depth looks like a puzzle. We perceive three-dimensional spatial information quickly and efficiently by using the binocular stereopsis of our eyes and, what is mote important the learning of the most common objects which we achieved through living. Nowadays, modelling the behaviour of our brain is a fiction, that is why the huge problem of 3D perception and further, interpretation is split into a sequence of easier problems. A lot of research is involved in robot vision in order to obtain 3D information of the surrounded scene. Most of this research is based on modelling the stereopsis of humans by using two cameras as if they were two eyes. This method is known as stereo vision and has been widely studied in the past and is being studied at present, and a lot of work will be surely done in the future. This fact allows us to affirm that this topic is one of the most interesting ones in computer vision. The stereo vision principle is based on obtaining the three dimensional position of an object point from the position of its projective points in both camera image planes. However, before inferring 3D information, the mathematical models of both cameras have to be known. This step is known as camera calibration and is broadly describes in the thesis. Perhaps the most important problem in stereo vision is the determination of the pair of homologue points in the two images, known as the correspondence problem, and it is also one of the most difficult problems to be solved which is currently investigated by a lot of researchers. The epipolar geometry allows us to reduce the correspondence problem. An approach to the epipolar geometry is describes in the thesis. Nevertheless, it does not solve it at all as a lot of considerations have to be taken into account. As an example we have to consider points without correspondence due to a surface occlusion or simply due to a projection out of the camera scope. The interest of the thesis is focused on structured light which has been considered as one of the most frequently used techniques in order to reduce the problems related lo stereo vision. Structured light is based on the relationship between a projected light pattern its projection and an image sensor. The deformations between the pattern projected into the scene and the one captured by the camera, permits to obtain three dimensional information of the illuminated scene. This technique has been widely used in such applications as: 3D object reconstruction, robot navigation, quality control, and so on. Although the projection of regular patterns solve the problem of points without match, it does not solve the problem of multiple matching, which leads us to use hard computing algorithms in order to search the correct matches. In recent years, another structured light technique has increased in importance. This technique is based on the codification of the light projected on the scene in order to be used as a tool to obtain an unique match. Each token of light is imaged by the camera, we have to read the label (decode the pattern) in order to solve the correspondence problem. The advantages and disadvantages of stereo vision against structured light and a survey on coded structured light are related and discussed. The work carried out in the frame of this thesis has permitted to present a new coded structured light pattern which solves the correspondence problem uniquely and robust. Unique, as each token of light is coded by a different word which removes the problem of multiple matching. Robust, since the pattern has been coded using the position of each token of light with respect to both co-ordinate axis. Algorithms and experimental results are included in the thesis. The reader can see examples 3D measurement of static objects, and the more complicated measurement of moving objects. The technique can be used in both cases as the pattern is coded by a single projection shot. Then it can be used in several applications of robot vision. Our interest is focused on the mathematical study of the camera and pattern projector models. We are also interested in how these models can be obtained by calibration, and how they can be used to obtained three dimensional information from two correspondence points. Furthermore, we have studied structured light and coded structured light, and we have presented a new coded structured light pattern. However, in this thesis we started from the assumption that the correspondence points could be well-segmented from the captured image. Computer vision constitutes a huge problem and a lot of work is being done at all levels of human vision modelling, starting from a)image acquisition; b) further image enhancement, filtering and processing, c) image segmentation which involves thresholding, thinning, contour detection, texture and colour analysis, and so on. The interest of this thesis starts in the next step, usually known as depth perception or 3D measurement.

Workflow data exchange semantics, object discovery & integration architecture for cross media production & distribution

There has been a clear lack of common data exchange semantics for inter-organisational workflow management systems where the research has mainly focused on technical issues rather than language constructs. This paper presents the neutral data exchanges semantics required for the workflow integration within the AXAEDIS framework and presents the mechanism for object discovery from the object repository where little or no knowledge about the object is available. The paper also presents workflow independent integration architecture with the AXAEDIS Framework.

Marine object detection using background modelling and blob analysis

Monitoring marine object is important for understanding the marine ecosystem and evaluating impacts on different environmental changes. One prerequisite of monitoring is to identify targets of interest. Traditionally, the target objects are recognized by trained scientists through towed nets and human observation, which cause much cost and risk to operators and creatures. In comparison, a noninvasive way via setting up a camera and seeking objects in images is more promising. In this paper, a novel technique of object detection in images is presented, which is applicable to generic objects. A robust background modelling algorithm is proposed to extract foregrounds and then blob features are introduced to classify foregrounds. Particular marine objects, box jellyfish and sea snake, are successfully detected in our work. Experiments conducted on image datasets collected by the Australian Institute of Marine Science (AIMS) demonstrate the effectiveness of the proposed technique.

Representações sociais de professor partilhadas por licenciados a partir de imagens de professor

This investigation had the teacher as object of study, whose objective was to know and analyze the teacher‟s Social Representations (SR) shared by undergraduates, as from images of this professional (teachers´ photos of several levels and school systems). It was searched out the process of depreciation or estimation, in which the teaching profession has been passing, trying to catch, specifically, possible existing correlations among such SR and the reflections in the attitudes developed by these students about their own development and professional practice. The data collection was carried out at the Federal University of Piauí Teresina with 165 undergraduates (15 from each course). It was applied a semi-structured interview, mediated by iconographic grouping (SALES, 2000, 2007), outlining a methodological widening of the studies fulfilled by (ROAZZI, 1995). It was used the function Factor Analysis, available in the SPSS (Statistical Package for the Social Sciences) for the analysis of the quantitative data, and it was proceeded a content analysis through the categorical analysis technique (BARDIN, 1977) for the analytical procedures of the qualitative data. It was resorted to the SR theory (MOSCOVICI, 1978) for the data interpretation and the Theory of Signs (PEIRCE. 1995) in the understanding of the decodification processes of signs that were present in the photos worked. It became evident that the undergraduates perceived the teaching profession inserted in a hierarchical scale of values (positive/negative), directly related to the school system and the teaching level, in which the teacher works. Most undergraduates share teacher‟s SR of negative content, consolidating the hegemonic SR about the teacher‟s social depreciation, although some of them imagine themselves, in the future, inserted among the teachers more appraised, showing that the SR orientate the positive and negative attitudes about the teacher. The presence of SR that mobilize the interviewers‟ attitudes in opposite senses related to the teacher, offer evidence of the necessity of future studies that can use a methodology more focused to understand other motivation factors that the undergraduates give evidence of having to the course they have chosen, besides the ones inferred by the SR caught in this investigation, as well as to establish a correlation between the teacher‟s SR (positive and negative) and the social economic level of the interviewers that share them. Such data revealed itself necessary since the literature signalizes for a relation between the course chosen and the applicant‟s social-economic level, and that the applicants‟ objective conditions to the licenciature courses are related to the subjective hopes that their group supplies

Extração semi-automática de rodovia baseada em um par estéreo de imagens aéreas e em otimização por programação dinâmica no espaço-objeto

This article proposes a method for 3D road extraction from a stereopair of aerial images. The dynamic programming (DP) algorithm is used to carry out the optimization process in the object-space, instead of usually doing it in the image-space such as the DP traditional methodologies. This means that road centerlines are directly traced in the object-space, implying that a mathematical relationship is necessary to connect road points in object and image-space. This allows the integration of radiometric information from images into the associate mathematical road model. As the approach depends on an initial approximation of each road, it is necessary a few seed points to coarsely describe the road. Usually, the proposed method allows good results to be obtained, but large anomalies along the road can disturb its performance. Therefore, the method can be used for practical application, although it is expected some kind of local manual edition of the extracted road centerline.

Determinação da velocidade de um objeto, a partir de uma seqüência de imagens, aplicando as equações de colinearidade modificadas

Pós-graduação em Ciências Cartográficas - FCT

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)