Um método para localização facial Invariante a rotação

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Implementação de rotinas computacionais básicas para cabeça estéreo robótica

O Laboratório de Sistemas Inteligentes do Departamento de Engenharia de Computação e Automação da Universidade Federal do Rio Grande do Norte - UFRN -tem como um de seus projetos de pesquisa -Robosense -a construção de uma plataforma robótica móvel. Trata-se de um robô provido de duas rodas, acionadas de forma diferencial, dois braços, com 5 graus de liberdade cada, um cinturão de sonares e uma cabeça estéreo. Como objetivo principal do projeto Robosense, o robô deverá ser capaz de navegar por todo o prédio do LECA, desviando de obstáculos. O sistema de navegação do robô, responsável pela geração e seguimento de rotas, atuará em malha fechada. Ou seja, sensores serão utilizados pelo sistema com o intuito de informar ao robô a sua pose atual, incluindo localização e a configuração de seus recursos. Encoders (sensores especiais de rotação) foram instalados nas rodas, bem como em todos os motores dos dois braços da cabeça estéreo. Sensores de fim-de-curso foram instalados em todas as juntas da cabeça estéreo para que seja possível sua pré-calibração. Sonares e câmeras também farão parte do grupo de sensores utilizados no projeto. O robô contará com uma plataforma composta por, a princípio, dois computadores ligados a um barramento único para uma operação em tempo real, em paralelo. Um deles será responsável pela parte de controle dos braços e de sua navegação, tomando como base as informações recebidas dos sensores das rodas e dos próximos objetivos do robô. O outro computador processará todas as informações referentes à cabeça estéreo do robô, como as imagens recebidas das câmeras. A utilização de técnicas de imageamento estéreo torna-se necessária, pois a informação de uma única imagem não determina unicamente a posição de um dado ponto correspondente no mundo. Podemos então, através da utilização de duas ou mais câmeras, recuperar a informação de profundidade da cena. A cabeça estéreo proposta nada mais é que um artefato físico que deve dar suporte a duas câmeras de vídeo, movimentá-las seguindo requisições de programas (softwares) apropriados e ser capaz de fornecer sua pose atual. Fatores como velocidade angular de movimentação das câmeras, precisão espacial e acurácia são determinantes para o eficiente resultado dos algoritmos que nesses valores se baseiam

Desenvolvimento de esquema de controle com realimentação visual para um robô manipulador

This work proposes a kinematic control scheme, using visual feedback for a robot arm with five degrees of freedom. Using computational vision techniques, a method was developed to determine the cartesian 3d position and orientation of the robot arm (pose) using a robot image obtained through a camera. A colored triangular label is disposed on the robot manipulator tool and efficient heuristic rules are used to obtain the vertexes of that label in the image. The tool pose is obtained from those vertexes through numerical methods. A color calibration scheme based in the K-means algorithm was implemented to guarantee the robustness of the vision system in the presence of light variations. The extrinsic camera parameters are computed from the image of four coplanar points whose cartesian 3d coordinates, related to a fixed frame, are known. Two distinct poses of the tool, initial and final, obtained from image, are interpolated to generate a desired trajectory in cartesian space. The error signal in the proposed control scheme consists in the difference between the desired tool pose and the actual tool pose. Gains are applied at the error signal and the signal resulting is mapped in joint incrementals using the pseudoinverse of the manipulator jacobian matrix. These incrementals are applied to the manipulator joints moving the tool to the desired pose

Localização de um robô móvel usando odometria e marcos naturais

Several methods of mobile robot navigation request the mensuration of robot position and orientation in its workspace. In the wheeled mobile robot case, techniques based on odometry allow to determine the robot localization by the integration of incremental displacements of its wheels. However, this technique is subject to errors that accumulate with the distance traveled by the robot, making unfeasible its exclusive use. Other methods are based on the detection of natural or artificial landmarks present in the environment and whose location is known. This technique doesnt generate cumulative errors, but it can request a larger processing time than the methods based on odometry. Thus, many methods make use of both techniques, in such a way that the odometry errors are periodically corrected through mensurations obtained from landmarks. Accordding to this approach, this work proposes a hybrid localization system for wheeled mobile robots in indoor environments based on odometry and natural landmarks. The landmarks are straight lines de.ned by the junctions in environments floor, forming a bi-dimensional grid. The landmark detection from digital images is perfomed through the Hough transform. Heuristics are associated with that transform to allow its application in real time. To reduce the search time of landmarks, we propose to map odometry errors in an area of the captured image that possesses high probability of containing the sought mark

Controle de Manipulador Redundante Utilizando Realimentação Visual

In conventional robot manipulator control, the desired path is specified in cartesian space and converted to joint space through inverse kinematics mapping. The joint references generated by this mapping are utilized for dynamic control in joint space. Thus, the end-effector position is, in fact, controlled indirectly, in open-loop, and the accuracy of grip position control directly depends on the accuracy of the available kinematic model. In this report, a new scheme for redundant manipulator kinematic control, based on visual servoing is proposed. In the proposed system, a robot image acquired through a CCD camera is processed in order to compute the position and orientation of each link of the robot arm. The robot task is specified as a temporal sequence of reference images of the robot arm. Thus, both the measured pose and the reference pose are specified in the same image space, and its difference is utilized to generate a cartesian space error for kinematic control purposes. The proposed control scheme was applied in a four degree-of-freedom planar redundant robot arm, experimental results are shown

Compressão auto-adaptativa de imagens coloridas

Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

Identificação Visual de Caixas de Medicamentos Usando Features Correspondentes

This work uses computer vision algorithms related to features in the identification of medicine boxes for the visually impaired. The system is for people who have a disease that compromises his vision, hindering the identification of the correct medicine to be ingested. We use the camera, available in several popular devices such as computers, televisions and phones, to identify the box of the correct medicine and audio through the image, showing the poor information about the medication, such: as the dosage, indication and contraindications of the medication. We utilize a model of object detection using algorithms to identify the features in the boxes of drugs and playing the audio at the time of detection of feauteres in those boxes. Experiments carried out with 15 people show that where 93 % think that the system is useful and very helpful in identifying drugs for boxes. So, it is necessary to make use of this technology to help several people with visual impairments to take the right medicine, at the time indicated in advance by the physician

Escalabilidade Paralela de um Algoritmo de Migração Reversa no Tempo (RTM) Pré-empilhamento

The seismic method is of extreme importance in geophysics. Mainly associated with oil exploration, this line of research focuses most of all investment in this area. The acquisition, processing and interpretation of seismic data are the parts that instantiate a seismic study. Seismic processing in particular is focused on the imaging that represents the geological structures in subsurface. Seismic processing has evolved significantly in recent decades due to the demands of the oil industry, and also due to the technological advances of hardware that achieved higher storage and digital information processing capabilities, which enabled the development of more sophisticated processing algorithms such as the ones that use of parallel architectures. One of the most important steps in seismic processing is imaging. Migration of seismic data is one of the techniques used for imaging, with the goal of obtaining a seismic section image that represents the geological structures the most accurately and faithfully as possible. The result of migration is a 2D or 3D image which it is possible to identify faults and salt domes among other structures of interest, such as potential hydrocarbon reservoirs. However, a migration fulfilled with quality and accuracy may be a long time consuming process, due to the mathematical algorithm heuristics and the extensive amount of data inputs and outputs involved in this process, which may take days, weeks and even months of uninterrupted execution on the supercomputers, representing large computational and financial costs, that could derail the implementation of these methods. Aiming at performance improvement, this work conducted the core parallelization of a Reverse Time Migration (RTM) algorithm, using the parallel programming model Open Multi-Processing (OpenMP), due to the large computational effort required by this migration technique. Furthermore, analyzes such as speedup, efficiency were performed, and ultimately, the identification of the algorithmic scalability degree with respect to the technological advancement expected by future processors

Desenvolvimento de solução para SLAM utilizando visão de teto

This work intends to show a new and few explored SLAM approach inside the simultaneous localization and mapping problem (SLAM). The purpose is to put a mobile robot to work in an indoor environment. The robot should map the environment and localize itself in the map. The robot used in the tests has an upward camera and encoders on the wheels. The landmarks in this built map are light splotches on the images of the camera caused by luminaries on the ceil. This work develops a solution based on Extended Kalman Filter to the SLAM problem using a developed observation model. Several developed tests and softwares to accomplish the SLAM experiments are shown in details

Sistema inteligente para detecção de manchas de óleo na superfície marinha através de imagens de SAR

Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents

Desenvolvimento de um Sistema de Visão Global para uma Frota de Mini-Robôs Móveis

Navigation based on visual feedback for robots, working in a closed environment, can be obtained settling a camera in each robot (local vision system). However, this solution requests a camera and capacity of local processing for each robot. When possible, a global vision system is a cheapest solution for this problem. In this case, one or a little amount of cameras, covering all the workspace, can be shared by the entire team of robots, saving the cost of a great amount of cameras and the associated processing hardware needed in a local vision system. This work presents the implementation and experimental results of a global vision system for mobile mini-robots, using robot soccer as test platform. The proposed vision system consists of a camera, a frame grabber and a computer (PC) for image processing. The PC is responsible for the team motion control, based on the visual feedback, sending commands to the robots through a radio link. In order for the system to be able to unequivocally recognize each robot, each one has a label on its top, consisting of two colored circles. Image processing algorithms were developed for the eficient computation, in real time, of all objects position (robot and ball) and orientation (robot). A great problem found was to label the color, in real time, of each colored point of the image, in time-varying illumination conditions. To overcome this problem, an automatic camera calibration, based on clustering K-means algorithm, was implemented. This method guarantees that similar pixels will be clustered around a unique color class. The obtained experimental results shown that the position and orientation of each robot can be obtained with a precision of few millimeters. The updating of the position and orientation was attained in real time, analyzing 30 frames per second

Compressão Seletiva de Imagens Coloridas com Detecção Automática de Regiões de Interesse

There has been an increasing tendency on the use of selective image compression, since several applications make use of digital images and the loss of information in certain regions is not allowed in some cases. However, there are applications in which these images are captured and stored automatically making it impossible to the user to select the regions of interest to be compressed in a lossless manner. A possible solution for this matter would be the automatic selection of these regions, a very difficult problem to solve in general cases. Nevertheless, it is possible to use intelligent techniques to detect these regions in specific cases. This work proposes a selective color image compression method in which regions of interest, previously chosen, are compressed in a lossless manner. This method uses the wavelet transform to decorrelate the pixels of the image, competitive neural network to make a vectorial quantization, mathematical morphology, and Huffman adaptive coding. There are two options for automatic detection in addition to the manual one: a method of texture segmentation, in which the highest frequency texture is selected to be the region of interest, and a new face detection method where the region of the face will be lossless compressed. The results show that both can be successfully used with the compression method, giving the map of the region of interest as an input

Desenvolvimento de métodos construtivos e de novos materiais empregados na confecção de cartuchos de próteses de membros inferiores

The manufacture of prostheses for lower limb amputees (transfemural and transtibial) requires the preparation of a cartridge with appropriate and custom fit to the profile of each patient. The traditional process to the patients, mainly in public hospitals in Brazil, begins with the completion of a form where types of equipment, plugins, measures, levels of amputation etc. are identified. Currently, such work is carried out manually using a common metric tape and caliper of wood to take the measures of the stump, featuring a very rudimentary, and with a high degree of uncertainty geometry of the final product. To address this problem, it was necessary to act in two simultaneously and correlated directions. Originally, it was developed an integrated tool for viewing 3D CAD for transfemoral types of prostheses and transtibial called OrtoCAD I. At the same time, it was necessary to design and build a reader Mechanical equipment (sort of three-dimensional scanner simplified) able to obtain, automatically and with accuracy, the geometric information of either of the stump or the healthy leg. The methodology includes the application of concepts of reverse engineering to computationally generate the representation of the stump and/or the reverse image of the healthy member. The materials used in the manufacturing of prostheses nor always obey to a technical scientific criteria, because, if by one way it meets the criteria of resistance, by the other, it brings serious problems mainly due to excess of weight. This causes to the user various disorders due to lack of conformity. That problem was addressed with the creation of a hybrid composite material for the manufacture of cartridges of prostheses. Using the Reader Fitter and OrtoCAD, the new composite material, which aggregates the mechanical properties of strength and rigidity on important parameters such as low weight and low cost, it can be defined in its better way. Besides, it brings a reduction of up steps in the current processes of manufacturing or even the feasibility of using new processes, in the industries, in order to obtain the prostheses. In this sense, the hybridization of the composite with the combination of natural and synthetic fibers can be a viable solution to the challenges offered above

Controle feedback de nível baseado em sensor de imagem aplicado ao equipamento misturador-decantador à inversão de fases (MDIF®)

The treatment of wastewaters contaminated with oil is of great practical interest and it is fundamental in environmental issues. A relevant process, which has been studied on continuous treatment of contaminated water with oil, is the equipment denominated MDIF® (a mixer-settler based on phase inversion). An important variable during the operation of MDIF® is the water-solvent interface level in the separation section. The control of this level is essential both to avoid the dragging of the solvent during the water removal and improve the extraction efficiency of the oil by the solvent. The measurement of oil-water interface level (in line) is still a hard task. There are few sensors able to measure oil-water interface level in a reliable way. In the case of lab scale systems, there are no interface sensors with compatible dimensions. The objective of this work was to implement a level control system to the organic solvent/water interface level on the equipment MDIF®. The detection of the interface level is based on the acquisition and treatment of images obtained dynamically through a standard camera (webcam). The control strategy was developed to operate in feedback mode, where the level measure obtained by image detection is compared to the desired level and an action is taken on a control valve according to an implemented PID law. A control and data acquisition program was developed in Fortran to accomplish the following tasks: image acquisition; water-solvent interface identification; to perform decisions and send control signals; and to record data in files. Some experimental runs in open-loop were carried out using the MDIF® and random pulse disturbances were applied on the input variable (water outlet flow). The responses of interface level permitted the process identification by transfer models. From these models, the parameters for a PID controller were tuned by direct synthesis and tests in closed-loop were performed. Preliminary results for the feedback loop demonstrated that the sensor and the control strategy developed in this work were suitable for the control of organic solvent-water interface level

A construção da imagem de leitor em memórias de leitura

In this work, we analyzed reading memories of mother language teachers in continuing education context. Our objective was to understand how each individual has built his/her reader image. Our theoretical approach to the construction of selfimage was based on the concept of discursive ethos, understanding it with Charaudeau (2006) as something constructed in the intersection of glances (of the self and the other). To understand how each teacher has built his/her reader image in that intertwining of glances (of the self and the other) we are on the contributions of Bakhtin (2003, 2010b) on exotopic glance or distant/external glance. Therefore, in the analysis, we tried to capture the exotopic glance of the teachers about themselves in the various stages of their reader formation and from our exotopic look of researcher; we gave provisional finish of the reader image that teachers built of themselves. For the analysis, we adopted other theoretical assumptions: about genres, theme, composition and style, statement and social voices we based on Bakhtin (1997, 2003, 2010a, 2010b); on the notion of the discursive ethos we anchored in studies conducted by Maingueneau (2008a, 2008b); about reading, we adopted the theoretical references of Rojo (2005, 2008, 2009a, 2009b, 2009c, 2009d), Garcez (2002), Freire (2008) and Silva Neto (2007). For the discursive genre reading memories makes reference to the theme memory as well as is related to the context of teacher training, the study was supported in Aragão (1992) and Nóvoa`s (2007) theory. Situated in the area of Applied Linguistics, the research aligns with qualitative-interpretative approach of socio-historical basis. Finally, from the analysis of the corpus, data that emerged from the findings, we conclude by stating that readers have created images of themselves as active readers, readers interested in both readings, the ones respected and the ones unappreciated by the official culture