Navegação cooperativa de um robô humanóide e um robô com rodas usando informação visual

This work presents a cooperative navigation systemof a humanoid robot and a wheeled robot using visual information, aiming to navigate the non-instrumented humanoid robot using information obtained from the instrumented wheeled robot. Despite the humanoid not having sensors to its navigation, it can be remotely controlled by infra-red signals. Thus, the wheeled robot can control the humanoid positioning itself behind him and, through visual information, find it and navigate it. The location of the wheeled robot is obtained merging information from odometers and from landmarks detection, using the Extended Kalman Filter. The marks are visually detected, and their features are extracted by image processing. Parameters obtained by image processing are directly used in the Extended Kalman Filter. Thus, while the wheeled robot locates and navigates the humanoid, it also simultaneously calculates its own location and maps the environment (SLAM). The navigation is done through heuristic algorithms based on errors between the actual and desired pose for each robot. The main contribution of this work was the implementation of a cooperative navigation system for two robots based on visual information, which can be extended to other robotic applications, as the ability to control robots without interfering on its hardware, or attaching communication devices

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

Localização e mapeamento simultâneos de ambientes planos usando visão monocular e representação híbrida do ambiente

The goal of this work is to propose a SLAM (Simultaneous Localization and Mapping) solution based on Extended Kalman Filter (EKF) in order to make possible a robot navigates along the environment using information from odometry and pre-existing lines on the floor. Initially, a segmentation step is necessary to classify parts of the image in floor or non floor . Then the image processing identifies floor lines and the parameters of these lines are mapped to world using a homography matrix. Finally, the identified lines are used in SLAM as landmarks in order to build a feature map. In parallel, using the corrected robot pose, the uncertainty about the pose and also the part non floor of the image, it is possible to build an occupancy grid map and generate a metric map with the obstacle s description. A greater autonomy for the robot is attained by using the two types of obtained map (the metric map and the features map). Thus, it is possible to run path planning tasks in parallel with localization and mapping. Practical results are presented to validate the proposal

Sistema de teleoftalmologia para auxílio ao pré-diagnóstico de disfunções oculomotoras

The vision is one of the five senses of the human body and, in children is responsible for up to 80% of the perception of world around. Studies show that 50% of children with multiple disabilities have some visual impairment, and 4% of all children are diagnosed with strabismus. The strabismus is an eye disability associated with handling capacity of the eye, defined as any deviation from perfect ocular alignment. Besides of aesthetic aspect, the child may report blurred or double vision . Ophthalmological cases not diagnosed correctly are reasons for many school abandonments. The Ministry of Education of Brazil points to the visually impaired as a challenge to the educators of children, particularly in literacy process. The traditional eye examination for diagnosis of strabismus can be accomplished by inducing the eye movements through the doctor s instructions to the patient. This procedure can be played through the computer aided analysis of images captured on video. This paper presents a proposal for distributed system to assist health professionals in remote diagnosis of visual impairment associated with motor abilities of the eye, such as strabismus. It is hoped through this proposal to contribute improving the rates of school learning for children, allowing better diagnosis and, consequently, the student accompaniment

Sistema não-Intrusivo para Estimação da Direção do olhar utilizando redes neurais artificiais

The fundamental senses of the human body are: vision, hearing, touch, taste and smell. These senses are the functions that provide our relationship with the environment. The vision serves as a sensory receptor responsible for obtaining information from the outside world that will be sent to the brain. The gaze reflects its attention, intention and interest. Therefore, the estimation of gaze direction, using computer tools, provides a promising alternative to improve the capacity of human-computer interaction, mainly with respect to those people who suffer from motor deficiencies. Thus, the objective of this work is to present a non-intrusive system that basically uses a personal computer and a low cost webcam, combined with the use of digital image processing techniques, Wavelets transforms and pattern recognition, such as artificial neural network models, resulting in a complete system that performs since the image acquisition (including face detection and eye tracking) to the estimation of gaze direction. The obtained results show the feasibility of the proposed system, as well as several feature advantages.

Um sistema inteligente de teleoftalmologia para o auxílio no diagnóstico de catarata

The increasing in world population, with higher proportion of elderly, leads to an increase in the number of individuals with vision loss and cataracts are one of the leading causes of blindness worldwide. Cataract is an eye disease that is the partial or total opacity of the crystalline lens (natural lens of the eye) or its capsule. It can be triggered by several factors such as trauma, age, diabetes mellitus, and medications, among others. It is known that the attendance by ophthalmologists in rural and poor areas in Brazil is less than needed and many patients with treatable diseases such as cataracts are undiagnosed and therefore untreated. In this context, this project presents the development of OPTICA, a system of teleophthalmology using smartphones for ophthalmic emergencies detection, providing a diagnostic aid for cataract using specialists systems and image processing techniques. The images are captured by a cellphone camera and along with a questionnaire filled with patient information are transmitted securely via the platform Mobile SANA to a online server that has an intelligent system available to assist in the diagnosis of cataract and provides ophthalmologists who analyze the information and write back the patient’s report. Thus, the OPTICA provides eye care to the poorest and least favored population, improving the screening of critically ill patients and increasing access to diagnosis and treatment.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Sistema inteligente para o processamento de imagens digitais intrabucais oclusais

Several are the areas in which digital images are used in solving day-to-day problems. In medicine the use of computer systems have improved the diagnosis and medical interpretations. In dentistry it’s not different, increasingly procedures assisted by computers have support dentists in their tasks. Set in this context, an area of dentistry known as public oral health is responsible for diagnosis and oral health treatment of a population. To this end, oral visual inspections are held in order to obtain oral health status information of a given population. From this collection of information, also known as epidemiological survey, the dentist can plan and evaluate taken actions for the different problems identified. This procedure has limiting factors, such as a limited number of qualified professionals to perform these tasks, different diagnoses interpretations among other factors. Given this context came the ideia of using intelligent systems techniques in supporting carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent system able to segment, count and classify teeth from occlusal intraoral digital photographic images. The proposed system makes combined use of machine learning techniques and digital image processing. We first carried out a color-based segmentation on regions of interest, teeth and non teeth, in the images through the use of Support Vector Machine. After identifying these regions were used techniques based on morphological operators such as erosion and transformed watershed for counting and detecting the boundaries of the teeth, respectively. With the border detection of teeth was possible to calculate the Fourier descriptors for their shape and the position descriptors. Then the teeth were classified according to their types through the use of the SVM from the method one-against-all used in multiclass problem. The multiclass classification problem has been approached in two different ways. In the first approach we have considered three class types: molar, premolar and non teeth, while the second approach were considered five class types: molar, premolar, canine, incisor and non teeth. The system presented a satisfactory performance in the segmenting, counting and classification of teeth present in the images.

Itinerário educacional de uma aluna cega e a busca pela imagem adaptada

The scope of this study directs an investigation in search of how the blind person learns knowledge at school mediated by the image in context of an inclusive education and how it can be (or is) triggered by the adaptation of images to the tactile seizure of the blind person and his correlative process of reading. To achieve this intent we choose a qualitative approach of research and opted for the modality of case study, based on the empirical field of a public school in the city of Cruzeta, RN and as a the main subject a congenitally blind female student enrolled in high school there, focusing, often, on the discipline of geography in its words mapping. Our procedures for construction of data are directly involved to the documentary analysis of open reflective interview and observation. The base guiding theory of our assessments is located in the current understanding about the human psychological development of its educational process inside an inclusive perspective, of contemporary conceptions about the visual disability as well of image as a cultural product. Accordingly, the human person is a concrete subject, whose development is deeply marked by the culture, historically built by human society. This subject regardless of his specific features, grasping the world in an interactive and immediate way, internalising and producing culture. In this thinking, we believe that the blind person perceives in multiple senses the stimuli of his environment and acts in the world toward his integration into the social environment. The image as a product of culture, historically and socially determined, appears as a sign conventionally used as an icon that in itself concentrates knowledge of which the student who does not realize visually himself and his surroundings cannot be excluded. In this direction, the inclusive educational process must build conditions of access to knowledge for all students without distinction, including access to the interpretation of the images originally intended for the seizure strictly visual to other perceptive models. Based in this theory and adopting principles of content analysis, we circulated inside the interpretation of the data constructed from the analysis of documents, from the subject speeches, from records of the observation made in the classroom and other notes of the field daily. In the search for pictures on the school contents, adapted to the tactile seizure of blind student, was seen little and not systematic in practice and teaching at the school. It showed us the itinerary of the student life marked by a succession of supports, most of the time inappropriate and pioneers in cooling the construction of her autonomy. It also showed us the tensions and contradictions of a school environment, supposedly inclusive, that stumbles in search of its intent, in the attitudinal and cumulative barriers brought, because of its aggravating maintenance. These findings arose of crossing data around of a categorization that gives importance to 1) Concepts regarding the school inclusion, 2) Elements of the school organization, educational proposal and teaching practice, 3) Meaning of the visual image as the object of knowledge, 4) Perception in multiple senses and 5) Development and learning of the blind person before impositions of the social environment. In light of these findings we infer that it must be guaranteed to the disabled person removal of the attitudinal barriers that are against his full development and the construction of his autonomy. In that sense, should be given opportunity to the student with visual disability, similarly to all students, not only access to school, but also the dynamics of a school life efficient, that means the seizure of knowledge in all its modalities, including the imagery. To that end, there is a need of the continued training of teachers, construction of a support network in response to all needs of students, and the opportunity to development of reading skills beyond a perspective eminently focused in the sight

Análise e classificação de imagens de lesões da pele por atributos de cor, forma e textura utilizando máquina de vetor de suporte

The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries

Técnicas de computação natural para segmentação de imagens médicas

Image segmentation is one of the image processing problems that deserves special attention from the scientific community. This work studies unsupervised methods to clustering and pattern recognition applicable to medical image segmentation. Natural Computing based methods have shown very attractive in such tasks and are studied here as a way to verify it's applicability in medical image segmentation. This work treats to implement the following methods: GKA (Genetic K-means Algorithm), GFCMA (Genetic FCM Algorithm), PSOKA (PSO and K-means based Clustering Algorithm) and PSOFCM (PSO and FCM based Clustering Algorithm). Besides, as a way to evaluate the results given by the algorithms, clustering validity indexes are used as quantitative measure. Visual and qualitative evaluations are realized also, mainly using data given by the BrainWeb brain simulator as ground truth

Multi-resolução com fóvea móvel para redução e abstração de dados em tempo real

We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results

Acelerando algoritmos de baixo nível em visão robótica com hardware reconfigurável

A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms

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

Expressão de fos após pulso de escuro no núcleo pré- geniculado do tálamo do sagui (Callithrix jacchus)

The pregeniculate nucleus (PGN) of the primate s thalamus is an agglomerate neuronal having a cap shaped located dorsomedially to the main relay visual information to the cerebral cortex, the dorsal lateral geniculate nucleus (GLD). Several cytoarchitectonic, neurochemical and retinal projections studies have pointed PGN as a structure homologous to intergeniculate leaflet (IGL) of rodents. The IGL receives retinal terminals and appears to be involved in the integration of photic and non-photic information relaying them, through geniculo-hypothalamic tract (TGH), to the main circadian oscillator in mammals, the suprachiasmatic nucleus (SCN) of the hypothalamus. Thus, the IGL participates in the control of the biological rhythm by modulating the activity of the SCN. Pharmacological and IGL injury studies conclude that it is critical in the processing of non-photic information which is transmitted to the SCN. Other studies have found that especially neurons immunoreactive to neuropeptide Y (NPY) respond to this type of stimulation, determined by its colocation with the FOS protein. Has not been determined if the PGN responds, expressing the FOS protein, to the non-photic stimulus nor the neurochemical nature of these cells. Thus, we apply a dark pulse in the specifics circadian phases and analyze the pattern of expression of FOS protein in PGN of the marmoset (Callithrix jacchus). We found that in all animals analyzed the FOS expression was higher in the experimental than in the control group. There was a higher expression of FOS when the dark pulse was applied during the subjective day between the groups. Still, a subregion of the PGN, known by immunoreactive to NPY, had a greater number of FOS-positive cells in relation to his other just close dorsal region. Our data corroborate the theory that the PGN and IGL are homologous structures that were anatomically modified during the evolutionary process, but kept its main neurochemical and functional characteristics. However, injury and hodological studies are still needed for a more accurate conclusion