Border figure detection using a phase oscillator network with dynamical coupling

Oscillator networks have been developed in order to perform specific tasks related to image processing. Here we analytically investigate the existence of synchronism in a pair of phase oscillators that are short-range dynamically coupled. Then, we use these analytical results to design a network able of detecting border of black-and-white figures. Each unit composing this network is a pair of such phase oscillators and is assigned to a pixel in the image. The couplings among the units forming the network are also dynamical. Border detection emerges from the network activity.

First stars XII. Abundances in extremely metal-poor turnoff stars, and comparison with the giants

Context. The detailed chemical abundances of extremely metal-poor (EMP) stars are key guides to understanding the early chemical evolution of the Galaxy. Most existing data, however, treat giant stars that may have experienced internal mixing later. Aims. We aim to compare the results for giants with new, accurate abundances for all observable elements in 18 EMP turno. stars. Methods. VLT/UVES spectra at R similar to 45 000 and S/N similar to 130 per pixel (lambda lambda 330-1000 nm) are analysed with OSMARCS model atmospheres and the TURBOSPECTRUM code to derive abundances for C, Mg, Si, Ca, Sc, Ti, Cr, Mn, Co, Ni, Zn, Sr, and Ba. Results. For Ca, Ni, Sr, and Ba, we find excellent consistency with our earlier sample of EMP giants, at all metallicities. However, our abundances of C, Sc, Ti, Cr, Mn and Co are similar to 0.2 dex larger than in giants of similar metallicity. Mg and Si abundances are similar to 0.2 dex lower (the giant [Mg/Fe] values are slightly revised), while Zn is again similar to 0.4 dex higher than in giants of similar [Fe/H] (6 stars only). Conclusions. For C, the dwarf/giant discrepancy could possibly have an astrophysical cause, but for the other elements it must arise from shortcomings in the analysis. Approximate computations of granulation (3D) effects yield smaller corrections for giants than for dwarfs, but suggest that this is an unlikely explanation, except perhaps for C, Cr, and Mn. NLTE computations for Na and Al provide consistent abundances between dwarfs and giants, unlike the LTE results, and would be highly desirable for the other discrepant elements as well. Meanwhile, we recommend using the giant abundances as reference data for Galactic chemical evolution models.

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 2: Model sensitivity to the biomass burning

We describe an estimation technique for biomass burning emissions in South America based on a combination of remote-sensing fire products and field observations, the Brazilian Biomass Burning Emission Model (3BEM). For each fire pixel detected by remote sensing, the mass of the emitted tracer is calculated based on field observations of fire properties related to the type of vegetation burning. The burnt area is estimated from the instantaneous fire size retrieved by remote sensing, when available, or from statistical properties of the burn scars. The sources are then spatially and temporally distributed and assimilated daily by the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) in order to perform the prognosis of related tracer concentrations. Three other biomass burning inventories, including GFEDv2 and EDGAR, are simultaneously used to compare the emission strength in terms of the resultant tracer distribution. We also assess the effect of using the daily time resolution of fire emissions by including runs with monthly-averaged emissions. We evaluate the performance of the model using the different emission estimation techniques by comparing the model results with direct measurements of carbon monoxide both near-surface and airborne, as well as remote sensing derived products. The model results obtained using the 3BEM methodology of estimation introduced in this paper show relatively good agreement with the direct measurements and MOPITT data product, suggesting the reliability of the model at local to regional scales.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Registration of temporal sequences of coronal and sagittal MR images through respiratory patterns

This work discusses the determination of the breathing patterns in time sequence of images obtained from magnetic resonance (MR) and their use in the temporal registration of coronal and sagittal images. The registration is made without the use of any triggering information and any special gas to enhance the contrast. The temporal sequences of images are acquired in free breathing. The real movement of the lung has never been seen directly, as it is totally dependent on its surrounding muscles and collapses without them. The visualization of the lung in motion is an actual topic of research in medicine. The lung movement is not periodic and it is susceptible to variations in the degree of respiration. Compared to computerized tomography (CT), MR imaging involves longer acquisition times and it is preferable because it does not involve radiation. As coronal and sagittal sequences of images are orthogonal to each other, their intersection corresponds to a segment in the three-dimensional space. The registration is based on the analysis of this intersection segment. A time sequence of this intersection segment can be stacked, defining a two-dimension spatio-temporal (2DST) image. The algorithm proposed in this work can detect asynchronous movements of the internal lung structures and lung surrounding organs. It is assumed that the diaphragmatic movement is the principal movement and all the lung structures move almost synchronously. The synchronization is performed through a pattern named respiratory function. This pattern is obtained by processing a 2DST image. An interval Hough transform algorithm searches for synchronized movements with the respiratory function. A greedy active contour algorithm adjusts small discrepancies originated by asynchronous movements in the respiratory patterns. The output is a set of respiratory patterns. Finally, the composition of coronal and sagittal image pairs that are in the same breathing phase is realized by comparing of respiratory patterns originated from diaphragmatic and upper boundary surfaces. When available, the respiratory patterns associated to lung internal structures are also used. The results of the proposed method are compared with the pixel-by-pixel comparison method. The proposed method increases the number of registered pairs representing composed images and allows an easy check of the breathing phase. (C) 2010 Elsevier Ltd. All rights reserved.

Quantifying subclinical central nervous lesions in primary antiphospholipid syndrome: The role of magnetization transfer imaging

Purpose: To define the role of magnetization transfer imaging (MTI) in detecting subclinical central nervous system (CNS) lesions in primary antiphospholipid syndrome (PAPS). Materials and Methods: Ten non-CNS PAPS patients were compared to 10 CNS PAPS patients and 10 age- and sex-matched controls. All PAPS patients met Sapporo criteria. All Subjects underwent conventional MRI and complementary MTI analysis to compose histograms. CNS viability was determined according to the magnetization transfer ratio (MTR) by mean pixel intensity (MPI) and the mean peak height (MPH). Volumetric cerebral measurements were assessed by brain parenchyma factor (BPF) and total/cerebral volume. Results: MTR histograms analysis revealed that MPI was significantly different among groups (P < 0.0001). Non-CNS PAPS had a higher MPI than CNS PAPS, (30.5 +/- 1.01 vs. 25.1 +/- 3.17 percent unit (pu); P < 0.05) although lower than controls (30.5 +/- 1.01 vs. 31.20 < 0.50 pu; P < 0.05). MPH in non-CNS PAPS (5.57 +/- 0.20% (1/pu)} was similar to controls (5.63 +/- 0.20% (1/pu), P > 0.05) and higher than CNS PAPS (4.71 +/- 0.30% (1/pu), P < 0.05). A higher peak location (PL) was also observed in the CNS PAPS group in comparison with the other groups (P < 0.0001). In addition, a lower BPF was found in non-CNS PAPS compared to controls (0.80 +/- 0.03 vs. 0.84 +/- 0.02 units; P < 0.05) but similar to CNS PAPS (0.80 +/- 0.03 vs. 0.79 +/- 0.05 units; P > 0.05). Conclusion: Our findings suggest that non-CNS PAPS patients have subclinical cerebral damage. The long-term-clinical relevance of MTI analysis in these patients needs to be defined by prospective studies.

Kallmann syndrome and mirror movements: White matter quantitative evaluation with magnetic resonance imaging

Kallmann syndrome (KS), characterized by the association of hypogonadotropic hypogonadism and anosmia, may present many other phenotypic abnormalities, including neurologic features as involuntary movements, called mirror movements (MM). MM etiology probably involves a complex mechanism comprising corticospinal tract abnormal development associated with deficient contralateral motor cortex inhibitory system. In this study, in order to address previous hypotheses concerning MM etiology, we identified and quantified white matter (WM) alterations in 21 KS patients, comparing subjects with and without MM and 16 control subjects, using magnetization transfer ratio (MTR) and T2 relaxometry (R2). Magnetization transfer and 12 double-echo images were acquired in a 1.5 T system. MTR and R2 were calculated pixel by pixel to initially create individual maps, and then, group average maps, co-registered with MNI305 stereotaxic coordinate system. After analysis of selected regions of interest, we demonstrated areas with higher 12 relaxation time and lower MTR values in KS patients, with and without MM, differently involving corticospinal tract projection, frontal lobes and corpus callosum. Higher MTR was observed only in pyramidal decussation when compared in both groups of patients with controls. In conclusion, we demonstrated that patients with KS have altered WM areas, presenting in a different manner in patients with and without MM. These data suggest axonal loss or disorganization involving abnormal pyramidal tracts and other associative/connective areas, relating to the presence or absence of MM. We also found a different pattern of alteration in pyramidal decussation, which can represent the primary area of neuronal disarrangement. (C) 2010 Elsevier B.V. All rights reserved.

On the efficiency of evolutionary fuzzy clustering

This paper tackles the problem of showing that evolutionary algorithms for fuzzy clustering can be more efficient than systematic (i.e. repetitive) approaches when the number of clusters in a data set is unknown. To do so, a fuzzy version of an Evolutionary Algorithm for Clustering (EAC) is introduced. A fuzzy cluster validity criterion and a fuzzy local search algorithm are used instead of their hard counterparts employed by EAC. Theoretical complexity analyses for both the systematic and evolutionary algorithms under interest are provided. Examples with computational experiments and statistical analyses are also presented.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

PLANT LEAF IDENTIFICATION BASED ON VOLUMETRIC FRACTAL DIMENSION

Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.

Texture analysis based on maximum contrast walker

Recently, the deterministic tourist walk has emerged as a novel approach for texture analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional texture analysis methods in the classification of a set of Brodatz textures and their rotated versions, thus confirming the potential of the method as a feasible texture analysis methodology. (C) 2010 Elsevier B.V. All rights reserved.

VSImG: A high frame rate bitmap based display system for neuroscience research

This paper describes a visual stimulus generator (VSImG) capable of displaying a gray-scale, 256 x 256 x 8 bitmap image with a frame rate of 500 Hz using a boustrophedonic scanning technique. It is designed for experiments with motion-sensitive neurons of the fly`s visual system, where the flicker fusion frequency of the photoreceptors can reach up to 500 Hz. Devices with such a high frame rate are not commercially available, but are required, if sensory systems with high flicker fusion frequency are to be studied. The implemented hardware approach gives us complete real-time control of the displacement sequence and provides all the signals needed to drive an electrostatic deflection display. With the use of analog signals, very small high-resolution displacements, not limited by the image`s pixel size can be obtained. Very slow image displacements with visually imperceptible steps can also be generated. This can be of interest for other vision research experiments. Two different stimulus files can be used simultaneously, allowing the system to generate X-Y displacements on one display or independent movements on two displays as long as they share the same bitmap image. (C) 2011 Elsevier B.V. All rights reserved.

A novel MAP-MRF approach for multispectral image contextual classification using combination of suboptimal iterative algorithms

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.

Multiple camera people detection and tracking using support integration

This paper proposes a method to locate and track people by combining evidence from multiple cameras using the homography constraint. The proposed method use foreground pixels from simple background subtraction to compute evidence of the location of people on a reference ground plane. The algorithm computes the amount of support that basically corresponds to the ""foreground mass"" above each pixel. Therefore, pixels that correspond to ground points have more support. The support is normalized to compensate for perspective effects and accumulated on the reference plane for all camera views. The detection of people on the reference plane becomes a search for regions of local maxima in the accumulator. Many false positives are filtered by checking the visibility consistency of the detected candidates against all camera views. The remaining candidates are tracked using Kalman filters and appearance models. Experimental results using challenging data from PETS`06 show good performance of the method in the presence of severe occlusion. Ground truth data also confirms the robustness of the method. (C) 2010 Elsevier B.V. All rights reserved.

Generating segmented meshes from textured color images

This paper presents a new framework for generating triangular meshes from textured color images. The proposed framework combines a texture classification technique, called W-operator, with Imesh, a method originally conceived to generate simplicial meshes from gray scale images. An extension of W-operators to handle textured color images is proposed, which employs a combination of RGB and HSV channels and Sequential Floating Forward Search guided by mean conditional entropy criterion to extract features from the training data. The W-operator is built into the local error estimation used by Imesh to choose the mesh vertices. Furthermore, the W-operator also enables to assign a label to the triangles during the mesh construction, thus allowing to obtain a segmented mesh at the end of the process. The presented results show that the combination of W-operators with Imesh gives rise to a texture classification-based triangle mesh generation framework that outperforms pixel based methods. Crown Copyright (C) 2009 Published by Elsevier Inc. All rights reserved.