Three-dimensional analysis of fracture, corrosion and wear surfaces

A brief look at the history of fractography has shown a recent trend in the quantification of topographic parameters through the use of three-dimensional reconstruction techniques, which associate SEM stereoscopy and stereophotogrammetry software, allowing the calculation of the elevation measurement at numerous points of the topography due to the parallax that takes place during the tilting of the sample along the microscope eucentric plane. Several investigators have used reconstruction techniques to correlate some fractographic parameters, such as fractal dimension and fractured to projected area ratio, to the mechanical properties of materials, such as fracture toughness and tensile strength. So far, the search for a clear relationship between the fracture topography and mechanical properties has provided ambiguous results. The present work applied a surface metrology software to reconstruct three-dimensionally fracture surfaces (transgranular cleavage, intergranular and dimple fracture), corrosion pits and tribo-surfaces in order to explore the potential of this stereophotogrammetry technique. The existence of a variation in the calculated topographic parameters with the conditions of SEM image acquisition reinforces the importance of both good image acquisition and accurate calibration methods in order to validate this 3D reconstruction technique in metrological terms. Preliminary results did not indicate the existence of a clear relationship between either the true to project area ratio and CVN absorbed energy or the fractal dimension and CVN absorbed energy. It is likely that each fracture mechanism presents a proper relationship between the fractographic parameters and mechanical properties. (C) 2009 Elsevier Ltd. All rights reserved.

The relationship between interimplant distances and vascularization of the interimplant bone

Background Long-term success of the implant restorations is based upon the biology and vasculature of the bone surrounding the implants, especially for the bone between two implants. Purpose The aim of this study was to evaluate how loaded implants placed 2 or 3 mm apart influence bone vessel organization. Material and methods Six mongrel dogs were used for the study. The four mandibular premolars were extracted and 3 months later, four 4.5 x 10 mm implants were placed on each side of the mandible. The implants were placed so that two adjacent implants were 2 mm (group 1) or 3 mm (group 2) distant from each other. After 12 weeks, the implants were loaded with provisional prostheses, then metallic crowns were placed 4 weeks later. Both temporary and metallic restorations were made so that the distance between the contact point and the bone crest was 5 mm. The animals were sacrificed after 8 weeks. The hemi-mandibles were removed and prepared for analysis. The interimplant bone vasculature of the two groups was studied using scanning electron microscopic images fractal analysis. The fractal dimension (D(f)) was calculated using the box-counting method. Results The values of the D(f) for the blood vessels were significantly higher (P <.05) in the specimens of the group 2 (1.969 +/- 0.169) than the group 1 (1.556 +/- 0.246). Conclusion The presence of more blood vessels in the group 2 is another indication that 3 mm is a preferable distance for contiguous implants than the 2 mm distance. To cite this article:Traini T, Novaes AB, Piattelli A, Papalexiou V, Muglia VA. The relationship between interimplant distances and vascularization of the interimplant bone.Clin. Oral Impl. Res. 21, 2010; 822-829.doi: 10.1111/j.1600-0501.2010.01926.x.

PedVis: A Structured, Space-Efficient Technique for Pedigree Visualization

Public genealogical databases are becoming increasingly populated with historical data and records of the current population`s ancestors. As this increasing amount of available information is used to link individuals to their ancestors, the resulting trees become deeper and more dense, which justifies the need for using organized, space-efficient layouts to display the data. Existing layouts are often only able to show a small subset of the data at a time. As a result, it is easy to become lost when navigating through the data or to lose sight of the overall tree structure. On the contrary, leaving space for unknown ancestors allows one to better understand the tree`s structure, but leaving this space becomes expensive and allows fewer generations to be displayed at a time. In this work, we propose that the H-tree based layout be used in genealogical software to display ancestral trees. We will show that this layout presents an increase in the number of displayable generations, provides a nicely arranged, symmetrical, intuitive and organized fractal structure, increases the user`s ability to understand and navigate through the data, and accounts for the visualization requirements necessary for displaying such trees. Finally, user-study results indicate potential for user acceptance of the new layout.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Texture analysis and classification using deterministic tourist walk

In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Texture analysis using graphs generated by deterministic partially self-avoiding walks

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.

A complex network-based approach for boundary shape analysis

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.

Plant Leaf Identification Using Gabor Wavelets

This article presents a novel method of plant classification using Gabor wavelet filters to extract texture filters in a foliar surface. The aim of this promising method is to add to the results obtained by other leaf attributes (such as shape, contour, color, among others), increasing, therefore, the percentage of classification of plant species. To corroborate the efficiency of the technique, an experiment using 20 species from Brazilian flora was done and discussed. The results are also compared with texture Fourier descriptors and cooccurrence matrices. (C) 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 236-243, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20201