Morphology of collagen fibers and elastic system fibers in actinic cheilitis

Background: Actinic cheilitis (AC) is a premalignant condition intimately related to exposure of the lips to sun rays. Aim: The objective of this study was to evaluate the elastic and collagen fibers in the lamina propria of AC. The degree of epithelial atypia was correlated with the quantity of elastic and collagen fibers. Materials and Methods: Fifty-one cases were investigated. One slide was stained with hematoxylin-eosin for the evaluation of atypia, the second was stained with Weigert′s resorcin-fuchsin for the assessment of elastic fibers, and the third slide was stained with Mallory′s trichrome for the analysis of collagen fibers. Results: Ordinal logistic regression analysis revealed a significant correlation between the presence of atypia and collagen fibers (P<0.05). Conclusions: It was concluded that there seems to be a reduction in the quantity of collagen fibers in cases of moderate and severe atypia. No correlation was observed between the degradation of elastic system fibers and the grade of dysplasia.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Geometric modeling from the medical images in the CAD system to support prosthesis design

This paper presents an individual designing prosthesis for surgical use and proposes a methodology for such design through mathematical extrapolation of data from digital images obtained via tomography of individual patient's bones. Individually tailored prosthesis designed to fit particular patient requirements as accurately as possible should result in more successful reconstruction, enable better planning before surgery and consequently fewer complications during surgery. Fast and accurate design and manufacture of personalized prosthesis for surgical use in bone replacement or reconstruction is potentially feasible through the application and integration of several different existing technologies, which are each at different stages of maturity. Initial case study experiments have been undertaken to validate the research concepts by making dimensional comparisons between a bone and a virtual model produced using the proposed methodology and a future research directions are discussed.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

The aster mission: Exploring for the first time a triple system asteroid

2001 SN263 is a triple system asteroid. Although it was discovery in 2001, in 2008 astronomical observation carried out by Arecibo observatory revealed that it is actually a system with three bodies orbiting each other. The main central body is an irregular object with a diameter about 2.8 km, while the other two are small objects with less than 1 km across. This system presents an orbital eccentricity of 0.47, with perihelion of 1.04 and aphelion of 1.99, which means that it can be considered as a Near Earth Object. This interesting system was chosen as the target for the Aster mission - first Brazilian space exploration undertaking. A small spacecraft with 150 kg of total mass, 30 kg of payload with 110 W available for the instruments, is scheduled to be launched in 2015, and in 2018 it will approach and will be put in orbit of the triple system. This spacecraft will use electric propulsion and in its payload it will carry image camera, laser rangefinder, infrared spectrometer, mass spectrometer, and experiments to be performed in its way to the asteroid. This mission represents a great challenge for the Brazilian space program. It is being structured to allow the full engagement of the Brazilian universities and technological companies in all the necessary developments to be carried out. In this paper, we present some aspects of this mission, including the transfer trajectories to be used, and details of buss and payload subsystems that are being developed and will be used. Copyright ©2010 by the International Astronautical Federation. All rights reserved.

Characterization of texture in image of skin lesions by support vector machine

Due to the increased incidence of skin cancer, computational methods based on intelligent approaches have been developed to aid dermatologists in the diagnosis of skin lesions. This paper proposes a method to classify texture in images, since it is an important feature for the successfully identification of skin lesions. For this is defined a feature vector, with the fractal dimension of images through the box-counting method (BCM), which is used with a SVM to classify the texture of the lesions in to non-irregular or irregular. With the proposed solution, we could obtain an accuracy of 72.84%. © 2012 AISTI.

Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Generating virtual images from oblique frames

Image acquisition systems based on multi-head arrangement of digital camerasare attractive alternatives enabling a larger imaging area when compared to a single framecamera. The calibration of this kind of system can be performed in several steps or byusing simultaneous bundle adjustment with relative orientation stability constraints. Thepaper will address the details of the steps of the proposed approach for system calibration,image rectification, registration and fusion. Experiments with terrestrial and aerial imagesacquired with two Fuji FinePix S3Pro cameras were performed. The experiments focusedon the assessment of the results of self-calibrating bundle adjustment with and withoutrelative orientation constraints and the effects to the registration and fusion when generatingvirtual images. The experiments have shown that the images can be accurately rectified andregistered with the proposed approach, achieving residuals smaller than one pixel. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Sparse arrays and image compounding techniques for non-destructive testing using guided acoustic waves

Piezoelectric array transducers applications are becoming usual in the ultrasonic non-destructive testing area. However, the number of elements can increase the system complexity, due to the necessity of multichannel circuitry and to the large amount of data to be processed. Synthetic aperture techniques, where one or few transmission and reception channels are necessary, and the data are post-processed, can be used to reduce the system complexity. Another possibility is to use sparse arrays instead of a full-populated array. In sparse arrays, there is a smaller number of elements and the interelement spacing is larger than half wavelength. In this work, results of ultrasonic inspection of an aluminum plate with artificial defects using guided acoustic waves and sparse arrays are presented. Synthetic aperture techniques are used to obtain a set of images that are then processed with an image compounding technique, which was previously evaluated only with full-populated arrays, in order to increase the resolution and contrast of the images. The results with sparse arrays are equivalent to the ones obtained with full-populated arrays in terms of resolution. Although there is an 8 dB contrast reduction when using sparse arrays, defect detection is preserved and there is the advantage of a reduction in the number of transducer elements and data volume. © 2013 Brazilian Society for Automatics - SBA.

Classification of masses in mammographic image using wavelet domain features and polynomial classifier

Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.

Performance of race instrumentation system in curved root canals: a comprehensive analysis by three study methods

In this study, curved maxillary molar root canals were instrumented with RaCe rotary system to evaluate: 1. the occurrence of canal transportation using a radiographic platform; 2. the action of the instruments on the dentin walls, centering ability and canal enlargement by analysis of digital images; and the percentage of regular dentin surfaces and debris within the canal by histological analysis. Ten mesiobuccal roots of extracted human maxillary molars were embedded in acrylic resin and sectioned at the middle and apical thirds. Root canal shaping was performed using the RaCe rotary system at 250 rpm and 1 Ncm torque. Each instrument set was used five times according to a crowndown technique in the following sequence: 40/0.10, 35/0.08, 25/0.06, 25/0.04, 25/0.02 (working length - WL), 30/0.02 (WL) and 35/0.02 (WL). Each instrument was inserted until resistance was felt and then pulled back, followed by brushing movements towards all canal walls. Each specimen was assessed by three study methods: radiographic platform, digitized image assessment and histological analysis. The radiographic platform showed lack of apical transportation. No statistically significant difference (Wilcoxon test, p>0.05) was found between the middle and apical thirds regarding instrument action on dentin walls, centering ability, area of root canal enlargement, percentage of regular dentin surfaces and debris within the root canal. It may be concluded that RaCe system is a suitable method for the preparation of curved root canals, regarding the maintenance of root canal original path, action on dentin walls, canal enlargement and removal of debris from the root canal lumen.

A hybrid image restoration algorithm based on Projections onto Convex Sets and Harmony Search

Image restoration is a research field that attempts to recover a blurred and noisy image. Since it can be modeled as a linear system, we propose in this paper to use the meta-heuristics optimization algorithm Harmony Search (HS) to find out near-optimal solutions in a Projections Onto Convex Sets-based formulation to solve this problem. The experiments using HS and four of its variants have shown that we can obtain near-optimal and faster restored images than other evolutionary optimization approach. © 2013 IEEE.

Optimizing feature selection through binary charged system search

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

Formação de imagens multiespectrais por meio de fusão de imagens adquiridas por múltiplas câmaras

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Interações entre o ambiente físico, uso e cobertura da terra e as características físicas e químicas no canal fluvial: a bacia hidrográfica do rio Santo Anastácio, Oeste Paulista (Dez. 2009 – Dez. 2010)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)