A Performance Evaluation of Surface Normals-Based Descriptors for Recognition of Objects using CAD-Models

This paper describes a study and analysis of surface normal-base descriptors for 3D object recognition. Specifically, we evaluate the behaviour of descriptors in the recognition process using virtual models of objects created from CAD software. Later, we test them in real scenes using synthetic objects created with a 3D printer from the virtual models. In both cases, the same virtual models are used on the matching process to find similarity. The difference between both experiments is in the type of views used in the tests. Our analysis evaluates three subjects: the effectiveness of 3D descriptors depending on the viewpoint of camera, the geometry complexity of the model and the runtime used to do the recognition process and the success rate to recognize a view of object among the models saved in the database.

Wavelets and decision trees for target detection over sea surface using cosmo-skymed SAR data

We are investigating the combination of wavelets and decision trees to detect ships and other maritime surveillance targets from medium resolution SAR images. Wavelets have inherent advantages to extract image descriptors while decision trees are able to handle different data sources. In addition, our work aims to consider oceanic features such as ship wakes and ocean spills. In this incipient work, Haar and Cohen-Daubechies-Feauveau 9/7 wavelets obtain detailed descriptors from targets and ocean features and are inserted with other statistical parameters and wavelets into an oblique decision tree. © 2011 Springer-Verlag.

Developing descriptors to predict mechanical properties of nanotubes

Descriptors and quantitative structure property relationships (QSPR) were investigated for mechanical property prediction of carbon nanotubes (CNTs). 78 molecular dynamics (MD) simulations were carried out, and 20 descriptors were calculated to build quantitative structure property relationships (QSPRs) for Young's modulus and Poisson's ratio in two separate analyses: vacancy only and vacancy plus methyl functionalization. In the first analysis, C N2/CT (number of non-sp2 hybridized carbons per the total carbons) and chiral angle were identified as critical descriptors for both Young's modulus and Poisson's ratio. Further analysis and literature findings indicate the effect of chiral angle is negligible at larger CNT radii for both properties. Raman spectroscopy can be used to measure CN2/C T, providing a direct link between experimental and computational results. Poisson's ratio approaches two different limiting values as CNT radii increases: 0.23-0.25 for chiral and armchair CNTs and 0.10 for zigzag CNTs (surface defects <3%). In the second analysis, the critical descriptors were CN2/CT, chiral angle, and MN/CT (number of methyl groups per total carbons). These results imply new types of defects can be represented as a new descriptor in QSPR models. Finally, results are qualified and quantified against experimental data. © 2013 American Chemical Society.

Fractal descriptors for discrimination of microscopy images of plant leaves

This study proposes the application of fractal descriptors method to the discrimination of microscopy images of plant leaves. Fractal descriptors have demonstrated to be a powerful discriminative method in image analysis, mainly for the discrimination of natural objects. In fact, these descriptors express the spatial arrangement of pixels inside the texture under different scales and such arrangements are directly related to physical properties inherent to the material depicted in the image. Here, we employ the Bouligand-Minkowski descriptors. These are obtained by the dilation of a surface mapping the gray-level texture. The classification of the microscopy images is performed by the well-known Support Vector Machine (SVM) method and we compare the success rate with other literature texture analysis methods. The proposed method achieved a correctness rate of 89%, while the second best solution, the Co-occurrence descriptors, yielded only 78%. This clear advantage of fractal descriptors demonstrates the potential of such approach in the analysis of the plant microscopy images.

Brazilian sardine (Sardinella brasiliensis Steindachner, 1879) spawning and nursery habitats: spatial-scale partitioning and multiscale relationships with thermohaline descriptors

We provide a detailed account of the spatial structure of the Brazilian sardine (Sardinella brasiliensis) spawning and nursery habitats, using ichthyoplankton data from nine surveys (1976-1993) covering the Southeastern Brazilian Bight (SBB). The spatial variability of sardine eggs and larvae was partitioned into predefined spatial-scale classes (broad scale, 200-500 km; medium scale, 50-100 km; and local scale, <50 km). The relationship between density distributions at both developmental stages and environmental descriptors (temperature and salinity) was also explored within these spatial scales. Spatial distributions of sardine eggs were mostly structured on medium and local scales, while larvae were characterized by broad-and medium-scale distributions. Broad-and medium-scale surface temperatures were positively correlated with sardine densities, for both developmental stages. Correlations with salinity were predominantly negative and concentrated on a medium scale. Broad-scale structuring might be explained by mesoscale processes, such as pulsing upwelling events and Brazil Current meandering at the northern portion of the SBB, while medium-scale relationships may be associated with local estuarine outflows. The results indicate that processes favouring vertical stability might regulate the spatial extensions of suitable spawning and nursery habitats for the Brazilian sardine.

Characterization of nanostructured material images using fractal descriptors

This work presents a methodology to the morphology analysis and characterization of nanostructured material images acquired from FEG-SEM (Field Emission Gun-Scanning Electron Microscopy) technique. The metrics were extracted from the image texture (mathematical surface) by the volumetric fractal descriptors, a methodology based on the Bouligand-Minkowski fractal dimension, which considers the properties of the Minkowski dilation of the surface points. An experiment with galvanostatic anodic titanium oxide samples prepared in oxalyc acid solution using different conditions of applied current, oxalyc acid concentration and solution temperature was performed. The results demonstrate that the approach is capable of characterizing complex morphology characteristics such as those present in the anodic titanium oxide.

Multiscale fractal descriptors applied to nanoscale images

This work proposes the application of fractal descriptors to the analysis of nanoscale materials under different experimental conditions. We obtain descriptors for images from the sample applying a multiscale transform to the calculation of fractal dimension of a surface map of such image. Particularly, we have used the Bouligand-Minkowski fractal dimension. We applied these descriptors to discriminate between two titanium oxide films prepared under different experimental conditions. Results demonstrate the discrimination power of proposed descriptors in such kind of application.

Molecular Surface Features in Modeling the HIV-1 RT Inhibitory Activity of 2-(2,6-Disubstituted phenyl)-3-(substituted pyrimidin-2-yl)-thiazolidin-4-ones

The human immunodeficiency virus-1 reverse transcriptase inhibitory activity of 2-(2,6-disubstituted phenyl)-3-(substituted pyrimidin-2-yl)-thiazolidin-4-ones have been analyzed using combinatorial protocol in multiple linear regression (CP-MLR) with several electronic and molecular surface area features of the compounds obtained from Molecular Operating Environment (MOE) software. The study has indicated the role of different charged molecular surface areas in modeling the inhibitory activity of the compounds. The derived models collectively suggested that the compounds should be compact without bulky substitutions on its peripheries for better HIV-1 RT inhibitory activity. It also emphasized the necessity of hydrophobicity and compact structural features for their activity. The scope of the descriptors identified for these analogues have been verified by extending the dataset with different 2-(disubstituted phenyl)-3-(substituted pyridin-2-yl)-thiazolidin-4-ones. The joint analysis of extended dataset highlighted the information content of identified descriptors in modeling the HIV-1 RT inhibitory activity of the compounds.

Calculated sea surface temperatures of two sediment cores

The reconstruction of ocean history employs a large variety of methods with origins in the biological, chemical, and physical sciences, and uses modern statistical techniques for the interpretation of extensive and complex data sets. Various sediment properties deliver useful information for reconstructing environmental parameters. Those properties that have a close relationship to environmental parameters are called ''proxy variables'' (''proxies'' for short). Proxies are measurable descriptors for desired (but unobservable) variables. Surface water temperature is probably the most important parameter for describing the conditions of past oceans and is crucial for climate modelling. Proxies for temperature are: abundance of microfossils dwelling in surface waters, oxygen isotope composition of planktic foraminifers, the ratio of magnesium or strontium to calcium in calcareous shells or the ratio of certain organic molecules (e.g. alkenones produced by coccolithophorids). Surface water salinity, which is important in modelling of ocean circulation, is much more difficult to reconstruct. At present there is no established method for a direct determination of this parameter. Measurements associated with the paleochemistry of bottom waters to reconstruct bottom water age and flow are made on benthic foraminifers, ostracodes, and deep-sea corals. Important geochemical tracers are d13C and Cd/Ca ratios. When using benthic foraminifers, knowledge of the sediment depth habitat of species is crucial. Reconstructions of productivity patterns are of great interest because of important links to current patterns, mixing of water masses, wind, the global carbon cycle, and biogeography. Productivity is reflected in the flux of carbon into the sediment. There are a number of fluxes other than those of organic carbon that can be useful in assessing productivity fluctuations. Among others, carbonate and opal flux have been used, as well as particulate barite. Furthermore, microfossil assemblages contain clues to the intensity of production as some species occur preferentially in high-productivity regions while others avoid these. One marker for the fertility of sub-surface waters (that is, nutrient availability) is the carbon isotope ratio within that water (13C/12C, expressed as d13C). Carbon isotope ratios in today's ocean are negatively correlated with nitrate and phosphate contents. Another tracer of phosphate content in ocean waters is the Cd/Ca ratio. The correlation between this ratio and phosphate concentrations is quite well documented. A rather new development to obtain clues on ocean fertility (nitrate utilization) is the analysis of the 15N/14N ratio in organic matter. The fractionation dynamics are analogous to those of carbon isotopes. These various ratios are captured within the organisms growing within the tagged water. A number of reconstructions of the partial pressure of CO2 have been attempted using d13C differences between planktic and benthic foraminifers and d13C values of bulk organic material or individual organic components. To define the carbon system in sea water, two elements of the system have to be known in addition to temperature. These can be any combination of total CO2 , alkalinity, or pH. To reconstruct pH, the boron isotope composition of carbonates has been used. Ba patterns have been used to infer the distribution of alkalinity in past oceans. Information relating to atmospheric circulationand climate is transported to the ocean by wind or rivers, in the form of minerals or as plant andanimal remains. The most useful tracers in this respect are silt-sized particles and pollen.

Topological invariance and spatial scaling of surface roughness in two highly eroded zones of Mexico: a comparative study

The Fractal Image Informatics toolbox (Oleschko et al., 2008 a; Torres-Argüelles et al., 2010) was applied to extract, classify and model the topological structure and dynamics of surface roughness in two highly eroded catchments of Mexico. Both areas are affected by gully erosion (Sidorchuk, 2005) and characterized by avalanche-like matter transport. Five contrasting morphological patterns were distinguished across the slope of the bare eroded surface of Faeozem (Queretaro State) while only one (apparently independent on the slope) roughness pattern was documented for Andosol (Michoacan State). We called these patterns ?the roughness clusters? and compared them in terms of metrizability, continuity, compactness, topological connectedness (global and local) and invariance, separability, and degree of ramification (Weyl, 1937). All mentioned topological measurands were correlated with the variance, skewness and kurtosis of the gray-level distribution of digital images. The morphology0 spatial dynamics of roughness clusters was measured and mapped with high precision in terms of fractal descriptors. The Hurst exponent was especially suitable to distinguish between the structure of ?turtle shell? and ?ramification? patterns (sediment producing zone A of the slope); as well as ?honeycomb? (sediment transport zone B) and ?dinosaur steps? and ?corals? (sediment deposition zone C) roughness clusters. Some other structural attributes of studied patterns were also statistically different and correlated with the variance, skewness and kurtosis of gray distribution of multiscale digital images. The scale invariance of classified roughness patterns was documented inside the range of five image resolutions. We conjectured that the geometrization of erosion patterns in terms of roughness clustering might benefit the most semi-quantitative models developed for erosion and sediment yield assessments (de Vente and Poesen, 2005).

Real-time 3D semi-local surface patch extraction using GPGPU

Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore, computing these features in real-time for many points in the scene is impossible. In this work, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used. The use of a GPU as a general purpose processor can achieve considerable speed-ups compared with a CPU implementation. In this work, advantageous results are obtained using the GPU to accelerate the computation of a 3D descriptor based on the calculation of 3D semi-local surface patches of partial views. This allows descriptor computation at several points of a scene in real-time. Benefits of the accelerated descriptor have been demonstrated in object recognition tasks. Source code will be made publicly available as contribution to the Open Source Point Cloud Library.

Evaluation Of The Effect Of Different Methods Of Microabrasion And Polishing On Surface Roughness Of Dental Enamel.

The microabrasion technique of enamel consists of selectively abrading the discolored areas or causing superficial structural changes in a selective way. In microabrasion technique, abrasive products associated with acids are used, and the evaluation of enamel roughness after this treatment, as well as surface polishing, is necessary. This in-vitro study evaluated the enamel roughness after microabrasion, followed by different polishing techniques. Roughness analyses were performed before microabrasion (L1), after microabrasion (L2), and after polishing (L3).Thus, 60 bovine incisive teeth divided into two groups were selected (n=30): G1- 37% phosphoric acid (37%) (Dentsply) and pumice; G2- hydrochloric acid (6.6%) associated with silicon carbide (Opalustre - Ultradent). Thereafter, the groups were divided into three sub-groups (n=10), according to the system of polishing: A - Fine and superfine granulation aluminum oxide discs (SofLex 3M); B - Diamond Paste (FGM) associated with felt discs (FGM); C - Silicone tips (Enhance - Dentsply). A PROC MIXED procedure was applied after data exploratory analysis, as well as the Tukey-Kramer test (5%). No statistical differences were found between G1 and G2 groups. L2 differed statistically from L1 and showed superior amounts of roughness. Differences in the amounts of post-polishing roughness for specific groups (1A, 2B, and 1C) arose, which demonstrated less roughness in L3 and differed statistically from L2 in the polishing system. All products increased enamel roughness, and the effectiveness of the polishing systems was dependent upon the abrasive used.

Tuning The Surface Anisotropy In Fe-doped Nio Nanoparticles.

Ni(1-x)FexO nanoparticles have been obtained by the co-precipitation chemical route. X-ray diffraction analyses using Rietveld refinement have shown a slight decrease in the microstrain and mean particle size as a function of the Fe content. The zero-field-cooling (ZFC) and field-cooling (FC) magnetization curves show superparamagnetic behavior at high temperatures and a low temperature peak (at T = 11 K), which is enhanced with increasing Fe concentration. Unusual behavior of the coercive field in the low temperature region and an exchange bias behavior were also observed. A decrease in the Fe concentration induces an increase in the exchange bias field. We argue that these behaviors can be linked with the strengthening of surface anisotropy caused by the incorporation of Fe ions.

The Effect Of Poly(methyl Methacrylate) Surface Treatments On The Adhesion Of Silicone-based Resilient Denture Liners.

Different surface treatment protocols of poly(methyl methacrylate) have been proposed to improve the adhesion of silicone-based resilient denture liners to poly(methyl methacrylate) surfaces. The purpose of this study was to evaluate the effect of different poly(methyl methacrylate) surface treatments on the adhesion of silicone-based resilient denture liners. Poly(methyl methacrylate) specimens were prepared and divided into 4 treatment groups: no treatment (control), methyl methacrylate for 180 seconds, acetone for 30 seconds, and ethyl acetate for 60 seconds. Poly(methyl methacrylate) disks (30.0 × 5.0 mm; n = 10) were evaluated regarding surface roughness and surface free energy. To evaluate tensile bond strength, the resilient material was applied between 2 treated poly(methyl methacrylate) bars (60.0 × 5.0 × 5.0 mm; n = 20 for each group) to form a 2-mm-thick layer. Data were analyzed by 1-way ANOVA and the Tukey honestly significant difference tests (α = .05). A Pearson correlation test verified the influence of surface properties on tensile bond strength. Failure type was assessed, and the poly(methyl methacrylate) surface treatment modifications were visualized with scanning electron microscopy. The surface roughness was increased (P < .05) by methyl methacrylate treatment. For the acetone and ethyl acetate groups, the surface free energy decreased (P < .05). The tensile bond strength was higher for the methyl methacrylate and ethyl acetate groups (P < .05). No correlation was found regarding surface properties and tensile bond strength. Specimens treated with acetone and methyl methacrylate presented a cleaner surface, whereas the ethyl acetate treatment produced a porous topography. The methyl methacrylate and ethyl acetate surface treatment protocols improved the adhesion of a silicone-based resilient denture liner to poly(methyl methacrylate).

Electrochemical Oxidation Of Landfill Leachate In A Flow Reactor: Optimization Using Response Surface Methodology.

Response surface methodology based on Box-Behnken (BBD) design was successfully applied to the optimization in the operating conditions of the electrochemical oxidation of sanitary landfill leachate aimed for making this method feasible for scale up. Landfill leachate was treated in continuous batch-recirculation system, where a dimensional stable anode (DSA(©)) coated with Ti/TiO2 and RuO2 film oxide were used. The effects of three variables, current density (milliampere per square centimeter), time of treatment (minutes), and supporting electrolyte dosage (moles per liter) upon the total organic carbon removal were evaluated. Optimized conditions were obtained for the highest desirability at 244.11 mA/cm(2), 41.78 min, and 0.07 mol/L of NaCl and 242.84 mA/cm(2), 37.07 min, and 0.07 mol/L of Na2SO4. Under the optimal conditions, 54.99 % of chemical oxygen demand (COD) and 71.07 ammonia nitrogen (NH3-N) removal was achieved with NaCl and 45.50 of COD and 62.13 NH3-N with Na2SO4. A new kinetic model predicted obtained from the relation between BBD and the kinetic model was suggested.