899 resultados para Multi-scale Fractal Dimension
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Objective: This paper presents a detailed study of fractal-based methods for texture characterization of mammographic mass lesions and architectural distortion. The purpose of this study is to explore the use of fractal and lacunarity analysis for the characterization and classification of both tumor lesions and normal breast parenchyma in mammography. Materials and methods: We conducted comparative evaluations of five popular fractal dimension estimation methods for the characterization of the texture of mass lesions and architectural distortion. We applied the concept of lacunarity to the description of the spatial distribution of the pixel intensities in mammographic images. These methods were tested with a set of 57 breast masses and 60 normal breast parenchyma (dataset1), and with another set of 19 architectural distortions and 41 normal breast parenchyma (dataset2). Support vector machines (SVM) were used as a pattern classification method for tumor classification. Results: Experimental results showed that the fractal dimension of region of interest (ROIs) depicting mass lesions and architectural distortion was statistically significantly lower than that of normal breast parenchyma for all five methods. Receiver operating characteristic (ROC) analysis showed that fractional Brownian motion (FBM) method generated the highest area under ROC curve (A z = 0.839 for dataset1, 0.828 for dataset2, respectively) among five methods for both datasets. Lacunarity analysis showed that the ROIs depicting mass lesions and architectural distortion had higher lacunarities than those of ROIs depicting normal breast parenchyma. The combination of FBM fractal dimension and lacunarity yielded the highest A z value (0.903 and 0.875, respectively) than those based on single feature alone for both given datasets. The application of the SVM improved the performance of the fractal-based features in differentiating tumor lesions from normal breast parenchyma by generating higher A z value. Conclusion: FBM texture model is the most appropriate model for characterizing mammographic images due to self-affinity assumption of the method being a better approximation. Lacunarity is an effective counterpart measure of the fractal dimension in texture feature extraction in mammographic images. The classification results obtained in this work suggest that the SVM is an effective method with great potential for classification in mammographic image analysis.
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Radar reflectivity measurements from three different wavelengths are used to retrieve information about the shape of aggregate snowflakes in deep stratiform ice clouds. Dual-wavelength ratios are calculated for different shape models and compared to observations at 3, 35 and 94 GHz. It is demonstrated that many scattering models, including spherical and spheroidal models, do not adequately describe the aggregate snowflakes that are observed. The observations are consistent with fractal aggregate geometries generated by a physically-based aggregation model. It is demonstrated that the fractal dimension of large aggregates can be inferred directly from the radar data. Fractal dimensions close to 2 are retrieved, consistent with previous theoretical models and in-situ observations.
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Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.
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This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.
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This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.
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In this thesis, a frequency selective surface (FSS) consists of a two-dimensional periodic structure mounted on a dielectric substrate, which is capable of selecting signals in one or more frequency bands of interest. In search of better performance, more compact dimensions, low cost manufacturing, among other characteristics, these periodic structures have been continually optimized over time. Due to its spectral characteristics, which are similar to band-stop or band-pass filters, the FSSs have been studied and used in several applications for more than four decades. The design of an FSS with a periodic structure composed by pre-fractal elements facilitates the tuning of these spatial filters and the adjustment of its electromagnetic parameters, enabling a compact design which generally has a stable frequency response and superior performance relative to its euclidean counterpart. The unique properties of geometric fractals have shown to be useful, mainly in the production of antennas and frequency selective surfaces, enabling innovative solutions and commercial applications in microwave range. In recent applications, the FSSs modify the indoor propagation environments (emerging concept called wireless building ). In this context, the use of pre-fractal elements has also shown promising results, allowing a more effective filtering of more than one frequency band with a single-layer structure. This thesis approaches the design of FSSs using pre-fractal elements based on Vicsek, Peano and teragons geometries, which act as band-stop spatial filters. The transmission properties of the periodic surfaces are analyzed to design compact and efficient devices with stable frequency responses, applicable to microwave frequency range and suitable for use in indoor communications. The results are discussed in terms of the electromagnetic effect resulting from the variation of parameters such as: fractal iteration number (or fractal level), scale factor, fractal dimension and periodicity of FSS, according the pre-fractal element applied on the surface. The analysis of the fractal dimension s influence on the resonant properties of a FSS is a new contribution in relation to researches about microwave devices that use fractal geometry. Due to its own characteristics and the geometric shape of the Peano pre-fractal elements, the reconfiguration possibility of these structures is also investigated and discussed. This thesis also approaches, the construction of efficient selective filters with new configurations of teragons pre-fractal patches, proposed to control the WLAN coverage in indoor environments by rejecting the signals in the bands of 2.4~2.5 GHz (IEEE 802.11 b) and 5.0~6.0 GHz (IEEE 802.11a). The FSSs are initially analyzed through simulations performed by commercial software s: Ansoft DesignerTM and HFSSTM. The fractal design methodology is validated by experimental characterization of the built prototypes, using alternatively, different measurement setups, with commercial horn antennas and microstrip monopoles fabricated for low cost measurements
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In this work we present the principal fractals, their caracteristics, properties abd their classification, comparing them to Euclidean Geometry Elements. We show the importance of the Fractal Geometry in the analysis of several elements of our society. We emphasize the importance of an appropriate definition of dimension to these objects, because the definition we presently know doesn t see a satisfactory one. As an instrument to obtain these dimentions we present the Method to count boxes, of Hausdorff- Besicovich and the Scale Method. We also study the Percolation Process in the square lattice, comparing it to percolation in the multifractal subject Qmf, where we observe som differences between these two process. We analize the histogram grafic of the percolating lattices versus the site occupation probability p, and other numerical simulations. And finaly, we show that we can estimate the fractal dimension of the percolation cluster and that the percolatin in a multifractal suport is in the same universality class as standard percolation. We observe that the area of the blocks of Qmf is variable, pc is a function of p which is related to the anisotropy of Qmf
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The topography of fracture surface along stretch zone front for Al7050 is analyzed about its fractal behavior and compared against local distributions of microstructural parameters and stretch zone height, considered here as a toughness parameter. Major influence on microscale was presented by precipitation density. Larger grains should be significant on topographic behavior at macroscale, besides the local toughness measured along stretch zone. The large scattering of fractal measurements along specimen width should limit the validity of models relating fractal values and fracture toughness. It is proposed that models based on mixed fractals must also consider some dispersion parameter instead of mean fractal measurements due to the overall complexity of fracture relief formation. It is suggested that sampling for fractal measurement must be restricted to plane strain region along fracture surface, due to smaller scattering in this region. (C) 2004 Elsevier B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Deformation bands are structures, developed in porous sandstones, that has small offsets and they are not shown on seismic section. The deformation bands of the pre and synrift sandstones of Araripe Basin were studied in outcrop, macroscopic and microscopic scales. The hierarchical, cinematic and spatial-geometric characteristics, and also the deformational mechanisms acting during its structural evolution were established too. In general, the mesoscopic scale observation allowed to discriminate deformation bands as singles or clusters in three main sets: NNE-SSW dextral; NE-SW normal (sometimes with strike-slip offset); and E-W sinistral; further a bed-parallel deformation bands as a local set. The microscopic characterization allowed to recognize the shearing and cataclastic character of such structures. Through the multi-scale study done in this work we verified that deformation bands analyzed were preferentially developed when sandstones under advanced stage of lithification. We also infer that the geometrical-spatial complexity of these bands, together with the presence of cataclastic matrix, can difficult the migration of fluids in reservoir rocks, resulting on their compartmentalization. Therefore, the study of deformation bands can aid researches about the structural evolution of sedimentary basin, as well as collaborate to understand the hydrodynamic behavior of reservoirs compartmented by these deformational structures
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The tectonics activity on the southern border of Parnaíba Basin resulted in a wide range of brittle structures that affect siliciclastic sedimentary rocks. This tectonic activity and related faults, joints, and folds are poorly known. The main aims of this study were (1) to identify lineaments using several remotesensing systems, (2) to check how the interpretation based on these systems at several scales influence the identification of lineaments, and (3) to contribute to the knowledge of brittle tectonics in the southern border of the Parnaíba Basin. The integration of orbital and aerial systems allowed a multi-scale identification, classification, and quantification of lineaments. Maps of lineaments were elaborated in the following scales: 1:200,000 (SRTM Shuttle Radar Topographic Mission), 1:50,000 (Landsat 7 ETM+ satellite), 1:10,000 (aerial photographs) and 1:5,000 (Quickbird satellite). The classification of the features with structural significance allowed the determination of four structural sets: NW, NS, NE, and EW. They were usually identified in all remote-sensing systems. The NE-trending set was not easily identified in aerial photographs but was better visualized on images of medium-resolution systems (SRTM and Landsat 7 ETM+). The same behavior characterizes the NW-trending. The NS-and EW-trending sets were better identified on images from high-resolution systems (aerial photographs and Quickbird). The structural meaning of the lineaments was established after field work. The NEtrending set is associated with normal and strike-slip faults, including deformation bands. These are the oldest structures identified in the region and are related to the reactivation of Precambrian basement structures from the Transbrazilian Lineament. The NW-trending set represents strike-slip and subordinated normal faults. The high dispersion of this set suggests a more recent origin than the previous structures. The NW-trending set may be related to the Picos-Santa Inês Lineament. The NS-and EW-trending sets correspond to large joints (100 m 5 km long). The truncation relationships between these joint sets indicate that the EW-is older than the NS-trending set. The methodology developed by the present work is an excellent tool for the understanding of the regional and local tectonic structures in the Parnaíba basin. It helps the choice of the best remote-sensing system to identify brittle features in a poorly known sedimentary basin
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The objective of the present study was to evaluate the outcomes of autogenous bone graft (AB) and bioglass (BG) associated or not with leukocyte-poor platelet-rich plasma (LP-PRP) in the rabbit maxillary sinus (MS) by histomorphometric and radiographic analysis. Twenty rabbits divided into 2 groups (G1, G2) were submitted to sinus lift surgery. In G1, 10 MS were grafted with AB and 10 MS were grafted with BG. In G2, 10 MS were grafted with AB + LP-PRP and 10 MS were grafted with BG + LP-PRP. After 90 days, the animals were killed and specimens were obtained, x-rayed, and submitted to histomorphometric, radiographic bone density (RD) and fractal dimension analysis. Radiographic bone density mean values (SD), expressed as aluminum equivalent in mm, of AB, BG, AB + LP-PRP, and BG + LP-PRP groups were 1.79 (0.31), 2.04 (0.39), 1.61 (0.28), and 1.53 (0.30), respectively. Significant differences (P < 0.05) were observed between BG and AB, and BG + PRP and BG. Fractal dimension mean values were 1.48 (0.04), 1.35 (0.08), 1.44 (0.04), and 1.44 (0.06), respectively. Significant differences were observed between BG and AB, and AB + LP-PRP and BG. Mean values for the percentage of bone inside MS were 63.30 (8.60), 52.65 (10.41), 55.25 (7.01), and 51.07 (10.25), respectively. No differences were found. No correlations were observed among percentage of bone, RD and FD. Histological analysis showed that MS treated with AB presented mature and new bone formation. The other groups showed minor bone formation. Within the limitations of this study, the results indicated that at a 90-day time end point, AB yielded better results than AB + LP-PRP, BG, and BG + LP-PRP and should be considered the primary material for MS augmentation.
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Computer systems are used to support breast cancer diagnosis, with decisions taken from measurements carried out in regions of interest (ROIs). We show that support decisions obtained from square or rectangular ROIs can to include background regions with different behavior of healthy or diseased tissues. In this study, the background regions were identified as Partial Pixels (PP), obtained with a multilevel method of segmentation based on maximum entropy. The behaviors of healthy, diseased and partial tissues were quantified by fractal dimension and multiscale lacunarity, calculated through signatures of textures. The separability of groups was achieved using a polynomial classifier. The polynomials have powerful approximation properties as classifiers to treat characteristics linearly separable or not. This proposed method allowed quantifying the ROIs investigated and demonstrated that different behaviors are obtained, with distinctions of 90% for images obtained in the Cranio-caudal (CC) and Mediolateral Oblique (MLO) views.
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Silica sonogels with different porosities were prepared by acid sono-hydrolysis of tetraethoxysilane. Wet sonogels were studied using small-angle x-ray scattering (SAXS) and differential scanning calorimetry (DSC). The DSC shows a broad thermal peak below the normal water melting point associated with the melting of confined ice nanocrystals, or nanoporosity. The nanopore size distribution was determined from the Gibbs-Thomson equation. As the porosity is increased, a second sharp DSC thermal peak with onset temperature at the water melting point is apparent, which was associated with the melting of ice macrocrystals, or macroporosity. The DSC result could be causing misinterpretation of the macroporosity because water may not be exactly confined in very feeble silica network regions in sonogels with high porosity. The structure of the wet gels can be described fairly well as mutually self-similar mass fractal structures with characteristic length. increasing from similar to 1.8 to similar to 5.4 nm and mass fractal dimension D diminishing discretely from similar to 2.6 to similar to 2.3 as the porosity increases in the range studied. More specifically, such a structure could be described using a two-parameter correlation function gamma(r) similar to r(D-3) exp(-r/xi), which is limited at larger scale by the cut-off distance xi but without a well-defined small scale cut-off distance, at least up to the maximum angular domain probed using SAXS in the present study.