910 resultados para 3D feature extraction
Resumo:
We introduce a novel algorithm for medial surfaces extraction that is based on the density-corrected Hamiltonian analysis. The approach extracts the skeleton directly from a triangulated mesh and adopts an adaptive octree-based approach in which only skeletal voxels are refined to a lower level of the hierarchy, resulting in robust and accurate skeletons at extremely high resolution. The quality of the extracted medial surfaces is confirmed by an extensive set of experiments. © 2012 IEEE.
Resumo:
3D Reconstruction is the process used to obtain a detailed graphical model in three dimensions that represents some real objectified scene. This process uses sequences of images taken from the scene, so it can automatically extract the information about the depth of feature points. These points are then highlighted using some computational technique on the images that compose the used dataset. Using SURF feature points this work propose a model for obtaining depth information of feature points detected by the system. At the ending, the proposed system extract three important information from the images dataset: the 3D position for feature points; relative rotation and translation matrices between images; the realtion between the baseline for adjacent images and the 3D point accuracy error found.
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Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.
Resumo:
Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.
Resumo:
To detect the presence of male DNA in vaginal samples collected from survivors of sexual violence and stored on filter paper. A pilot study was conducted to evaluate 10 vaginal samples spotted on sterile filter paper: 6 collected at random in April 2009 and 4 in October 2010. Time between sexual assault and sample collection was 4-48hours. After drying at room temperature, the samples were placed in a sterile envelope and stored for 2-3years until processing. DNA extraction was confirmed by polymerase chain reaction for human β-globin, and the presence of prostate-specific antigen (PSA) was quantified. The presence of the Y chromosome was detected using primers for sequences in the TSPY (Y7/Y8 and DYS14) and SRY genes. β-Globin was detected in all 10 samples, while 2 samples were positive for PSA. Half of the samples amplified the Y7/Y8 and DYS14 sequences of the TSPY gene and 30% amplified the SRY gene sequence of the Y chromosome. Four male samples and 1 female sample served as controls. Filter-paper spots stored for periods of up to 3years proved adequate for preserving genetic material from vaginal samples collected following sexual violence.
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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.
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In the current study, a new approach has been developed for correcting the effect that moisture reduction after virgin olive oil (VOO) filtration exerts on the apparent increase of the secoiridoid content by using an internal standard during extraction. Firstly, two main Spanish varieties (Picual and Hojiblanca) were submitted to industrial filtration of VOOs. Afterwards, the moisture content was determined in unfiltered and filtered VOOs, and liquid-liquid extraction of phenolic compounds was performed using different internal standards. The resulting extracts were analyzed by HPLC-ESI-TOF/MS, in order to gain maximum information concerning the phenolic profiles of the samples under study. The reduction effect of filtration on the moisture content, phenolic alcohols, and flavones was confirmed at the industrial scale. Oleuropein was chosen as internal standard and, for the first time, the apparent increase of secoiridoids in filtered VOO was corrected, using a correction coefficient (Cc) calculated from the variation of internal standard area in filtered and unfiltered VOO during extraction. This approach gave the real concentration of secoiridoids in filtered VOO, and clarified the effect of the filtration step on the phenolic fraction. This finding is of great importance for future studies that seek to quantify phenolic compounds in VOOs.
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Originally from Asia, Dovyalis hebecarpa is a dark purple/red exotic berry now also produced in Brazil. However, no reports were found in the literature about phenolic extraction or characterisation of this berry. In this study we evaluate the extraction optimisation of anthocyanins and total phenolics in D. hebecarpa berries aiming at the development of a simple and mild analytical technique. Multivariate analysis was used to optimise the extraction variables (ethanol:water:acetone solvent proportions, times, and acid concentrations) at different levels. Acetone/water (20/80 v/v) gave the highest anthocyanin extraction yield, but pure water and different proportions of acetone/water or acetone/ethanol/water (with >50% of water) were also effective. Neither acid concentration nor time had a significant effect on extraction efficiency allowing to fix the recommended parameters at the lowest values tested (0.35% formic acid v/v, and 17.6 min). Under optimised conditions, extraction efficiencies were increased by 31.5% and 11% for anthocyanin and total phenolics, respectively as compared to traditional methods that use more solvent and time. Thus, the optimised methodology increased yields being less hazardous and time consuming than traditional methods. Finally, freeze-dried D. hebecarpa showed high content of target phytochemicals (319 mg/100g and 1,421 mg/100g of total anthocyanin and total phenolic content, respectively).
Resumo:
Extraction processes are largely used in many chemical, biotechnological and pharmaceutical industries for recovery of bioactive compounds from medicinal plants. To replace the conventional extraction techniques, new techniques as high-pressure extraction processes that use environment friendly solvents have been developed. However, these techniques, sometimes, are associated with low extraction rate. The ultrasound can be effectively used to improve the extraction rate by the increasing the mass transfer and possible rupture of cell wall due the formation of microcavities leading to higher product yields with reduced processing time and solvent consumption. This review presents a brief survey about the mechanism and aspects that affecting the ultrasound assisted extraction focusing on the use of ultrasound irradiation for high-pressure extraction processes intensification.
Resumo:
Purified genomic DNA can be difficult to obtain from some plant species because of the presence of impurities such as polysaccharides, which are often co-extracted with DNA. In this study, we developed a fast, simple, and low-cost protocol for extracting DNA from plants containing high levels of secondary metabolites. This protocol does not require the use of volatile toxic reagents such as mercaptoethanol, chloroform, or phenol and allows the extraction of high-quality DNA from wild and cultivated tropical species.
Resumo:
Extracts from malagueta pepper (Capsicum frutescens L.) were obtained using supercritical fluid extraction (SFE) assisted by ultrasound, with carbon dioxide as solvent at 15MPa and 40°C. The SFE global yield increased up to 77% when ultrasound waves were applied, and the best condition of ultrasound-assisted extraction was ultrasound power of 360W applied during 60min. Four capsaicinoids were identified in the extracts and quantified by high performance liquid chromatography. The use of ultrasonic waves did not influence significantly the capsaicinoid profiles and the phenolic content of the extracts. However, ultrasound has enhanced the SFE rate. A model based on the broken and intact cell concept was adequate to represent the extraction kinetics and estimate the mass transfer coefficients, which were increased with ultrasound. Images obtained by field emission scanning electron microscopy showed that the action of ultrasonic waves did not cause cracks on the cell wall surface. On the other hand, ultrasound promoted disturbances in the vegetable matrix, leading to the release of extractable material on the solid surface. The effects of ultrasound were more significant on SFE from larger solid particles.
Resumo:
This work encompasses a direct and coherent strategy to synthesise a molecularly imprinted polymer (MIP) capable of extracting fluconazole from its sample. The MIP was successfully prepared from methacrylic acid (functional monomer), ethyleneglycoldimethacrylate (crosslinker) and acetonitrile (porogenic solvent) in the presence of fluconazole as the template molecule through a non-covalent approach. The non-imprinted polymer (NIP) was prepared following the same synthetic scheme, but in the absence of the template. The data obtained from scanning electronic microscopy, infrared spectroscopy, thermogravimetric and nitrogen Brunauer-Emmett-Teller plot helped to elucidate the structural as well as the morphological characteristics of the MIP and NIP. The application of MIP as a sorbent was demonstrated by packing it in solid phase extraction cartridges to extract fluconazole from commercial capsule samples through an offline analytical procedure. The quantification of fluconazole was accomplished through UPLC-MS, which resulted in LOD≤1.63×10(-10) mM. Furthermore, a high percentage recovery of 91±10% (n=9) was obtained. The ability of the MIP for selective recognition of fluconazole was evaluated by comparison with the structural analogues, miconazole, tioconazole and secnidazole, resulting in percentage recoveries of 51, 35 and 32%, respectively.
Resumo:
The aim of this work is to obtain, purify and characterize biochemically a peroxidase from Copaifera langsdorffii leaves (COP). COP was obtained by acetone precipitation followed by ion-exchange chromatography. Purification yielded 3.5% of peroxidase with the purification factor of 46.86. The COP optimum pH is 6.0 and the temperature is 35 ºC. COP was stable in the pH range of 4.5 to 9.3 and at temperatures below 50.0 ºC. The apparent Michaelis-Menten constants (Km) for guaiacol and H2O2 were 0.04 mM and 0.39 mM respectively. Enzyme turnover was 0.075 s-1 for guaiacol and 0.28 s-1 for hydrogen peroxide. Copaifera langsdorffii leaves showed to be a rich source of active peroxidase (COP) during the whole year. COP could replace HRP, the most used peroxidase, in analytical determinations and treatment of industrial effluents at low cost.
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This paper investigates the relationship between structural and semantic properties of factive sentences and the pattern of extraction exhibited. It is argued that a classification as weak or strong island is unfeasible for what has been termed Factive Island. The kinds of structures allowed as factive complements are analyzed as well as their corresponding behavior concerning extraction. The common feature these structures show is their presuppositional character, which is derived from a selection requirement. I assume that factive predicates select a [+ specific] complement. The differences showed concerning extraction constitute a spontaneous effect from the structural way each construction may satisfy this requirement.
Resumo:
This article addresses diagnostic parameters that should be assessed in the treatment of extraction sockets with dental implant placement by presenting three case reports that emphasize the relevance of the amount of remaining bone walls. Diagnosis was based on the analysis of clinical and radiographic parameters (e.g.: bone defect morphology, remaining bone volume, presence of infections on the receptor site). Case 1 presents a 5-wall defect in the maxillary right central incisor region with severe root resorption, which was treated with immediate implant placement. Cases 2 and 3 present, respectively, two- and three-wall bone defects that did not have indication for immediate implants. These cases were first submitted to a guided bone regeneration (GBR) procedure with bone graft biomaterial and membrane barriers, and the implants were installed in a second surgical procedure. The analysis of the preoperative periodontal condition of the adjacent teeth and bone defect morphology is extremely important because these factors determine the choice between immediate implant or GBR treatment followed by implant installation in a subsequent intervention.