77 resultados para Processamento de imagem

em Universidade Federal do Rio Grande do Norte(UFRN)


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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

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This dissertation presents a cooperative virtual multimedia enviroment for employing on time medical Field, using a TCP/IP computer network. The Virtual Diagnosis Room environment make it possible to perform cooperative tasks using classical image processing. Synchronous and assynchronous text conversation (chat) and content markup, in order to produce remote cooperative diagnosis. The dissertation also describes the tool in detail and its functions, that enables the interaction among users, along with implementation detals, contributions and weakness of this work

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The precision and the fast identification of abnormalities of bottom hole are essential to prevent damage and increase production in the oil industry. This work presents a study about a new automatic approach to the detection and the classification of operation mode in the Sucker-rod Pumping through dynamometric cards of bottom hole. The main idea is the recognition of the well production status through the image processing of the bottom s hole dynamometric card (Boundary Descriptors) and statistics and similarity mathematics tools, like Fourier Descriptor, Principal Components Analysis (PCA) and Euclidean Distance. In order to validate the proposal, the Sucker-Rod Pumping system real data are used

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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

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The municipality of Areia Branca is within the mesoregion of West Potiguar and within the microregion of Mossoró, covering an area of 357,58 km2. Covering an area of weakness in terms of environmental, housing, together with the municipality of Grossos-RN, the estuary of River Apodi-Mossoró. The municipality of Areia Branca has historically suffered from a lack of planning regarding the use and occupation of land as some economic activities, attracted by the extremely favorable natural conditions, have exploited their natural resources improperly. The aim of this study is to quantify and analyze the environmental degradation in the municipality. Thus initially was performed a characterization of land use using remote sensing, geoprocessing and geographic information system GIS in order to generate data and information on the municipal scale, which may serve as input to the environmental planning and land use planning in the region. From this perspective, were used a Landsat 5 image TM sensor for the year 2010. In the processing of this image was used SPRING 5.2 and applied a supervised classification using the classifier regions, which was employed Bhattacharya Distance method with a threshold at 30%. Thus was obtained the land use map that was analyzed the spatial distribution of different types of the use that is occurring in the city, identifying areas that are being used incorrectly and the main types of environmental degradation. And further, were applied the methodology proposed by Beltrame (1994), Physical Diagnosis Conservationist under some adaptations for quantifying the level of degradation or conservation study area. As results, the indexes were obtained for the parameters in the proposed methodology, allowing quantitatively analyze the degradation potential of each sector. From this perspective, considering a scale of 0 to 100, sector A and sector B had value 31.20 units of risk of physical deterioration. And the C sector, has shown its value - 34.64 units degradation risk and should be considered a priority in relation to the achievement of conservation actions

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The main objective of this work was to enable the recognition of human gestures through the development of a computer program. The program created captures the gestures executed by the user through a camera attached to the computer and sends it to the robot command referring to the gesture. They were interpreted in total ve gestures made by human hand. The software (developed in C ++) widely used the computer vision concepts and open source library OpenCV that directly impact the overall e ciency of the control of mobile robots. The computer vision concepts take into account the use of lters to smooth/blur the image noise reduction, color space to better suit the developer's desktop as well as useful information for manipulating digital images. The OpenCV library was essential in creating the project because it was possible to use various functions/procedures for complete control lters, image borders, image area, the geometric center of borders, exchange of color spaces, convex hull and convexity defect, plus all the necessary means for the characterization of imaged features. During the development of the software was the appearance of several problems, as false positives (noise), underperforming the insertion of various lters with sizes oversized masks, as well as problems arising from the choice of color space for processing human skin tones. However, after the development of seven versions of the control software, it was possible to minimize the occurrence of false positives due to a better use of lters combined with a well-dimensioned mask size (tested at run time) all associated with a programming logic that has been perfected over the construction of the seven versions. After all the development is managed software that met the established requirements. After the completion of the control software, it was observed that the overall e ectiveness of the various programs, highlighting in particular the V programs: 84.75 %, with VI: 93.00 % and VII with: 94.67 % showed that the nal program performed well in interpreting gestures, proving that it was possible the mobile robot control through human gestures without the need for external accessories to give it a better mobility and cost savings for maintain such a system. The great merit of the program was to assist capacity in demystifying the man set/machine therefore uses an easy and intuitive interface for control of mobile robots. Another important feature observed is that to control the mobile robot is not necessary to be close to the same, as to control the equipment is necessary to receive only the address that the Robotino passes to the program via network or Wi-Fi.

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This work aims to develop a methodology for analysis of images using overlapping, which assists in identification of microstructural features in areas of titanium, which may be associated with its biological response. That way, surfaces of titanium heat treated for 08 (eight) different ways have been subjected to a test culture of cells. It was a relationship between the grain, texture and shape of grains of surface of titanium (attacked) trying to relate to the process of proliferation and adhesion. We used an open source software for cell counting adhered to the surface of titanium. The juxtaposition of images before and after cell culture was obtained with the aid of micro-hardness of impressions made on the surface of samples. From this image where there is overlap, it is possible to study a possible relationship between cell growth with microstructural characteristics of the surface of titanium. This methodology was efficient to describe a set of procedures that are useful in the analysis of surfaces of titanium subjected to a culture of cells

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With the growth of energy consumption worldwide, conventional reservoirs, the reservoirs called "easy exploration and production" are not meeting the global energy demand. This has led many researchers to develop projects that will address these needs, companies in the oil sector has invested in techniques that helping in locating and drilling wells. One of the techniques employed in oil exploration process is the reverse time migration (RTM), in English, Reverse Time Migration, which is a method of seismic imaging that produces excellent image of the subsurface. It is algorithm based in calculation on the wave equation. RTM is considered one of the most advanced seismic imaging techniques. The economic value of the oil reserves that require RTM to be localized is very high, this means that the development of these algorithms becomes a competitive differentiator for companies seismic processing. But, it requires great computational power, that it still somehow harms its practical success. The objective of this work is to explore the implementation of this algorithm in unconventional architectures, specifically GPUs using the CUDA by making an analysis of the difficulties in developing the same, as well as the performance of the algorithm in the sequential and parallel version

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In Simultaneous Localization and Mapping (SLAM - Simultaneous Localization and Mapping), a robot placed in an unknown location in any environment must be able to create a perspective of this environment (a map) and is situated in the same simultaneously, using only information captured by the robot s sensors and control signals known. Recently, driven by the advance of computing power, work in this area have proposed to use video camera as a sensor and it came so Visual SLAM. This has several approaches and the vast majority of them work basically extracting features of the environment, calculating the necessary correspondence and through these estimate the required parameters. This work presented a monocular visual SLAM system that uses direct image registration to calculate the image reprojection error and optimization methods that minimize this error and thus obtain the parameters for the robot pose and map of the environment directly from the pixels of the images. Thus the steps of extracting and matching features are not needed, enabling our system works well in environments where traditional approaches have difficulty. Moreover, when addressing the problem of SLAM as proposed in this work we avoid a very common problem in traditional approaches, known as error propagation. Worrying about the high computational cost of this approach have been tested several types of optimization methods in order to find a good balance between good estimates and processing time. The results presented in this work show the success of this system in different environments

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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.

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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.

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This work aims to develop a methodology for analysis of images using overlapping, which assists in identification of microstructural features in areas of titanium, which may be associated with its biological response. That way, surfaces of titanium heat treated for 08 (eight) different ways have been subjected to a test culture of cells. It was a relationship between the grain, texture and shape of grains of surface of titanium (attacked) trying to relate to the process of proliferation and adhesion. We used an open source software for cell counting adhered to the surface of titanium. The juxtaposition of images before and after cell culture was obtained with the aid of micro-hardness of impressions made on the surface of samples. From this image where there is overlap, it is possible to study a possible relationship between cell growth with microstructural characteristics of the surface of titanium. This methodology was efficient to describe a set of procedures that are useful in the analysis of surfaces of titanium subjected to a culture of cells

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With the growth of energy consumption worldwide, conventional reservoirs, the reservoirs called "easy exploration and production" are not meeting the global energy demand. This has led many researchers to develop projects that will address these needs, companies in the oil sector has invested in techniques that helping in locating and drilling wells. One of the techniques employed in oil exploration process is the reverse time migration (RTM), in English, Reverse Time Migration, which is a method of seismic imaging that produces excellent image of the subsurface. It is algorithm based in calculation on the wave equation. RTM is considered one of the most advanced seismic imaging techniques. The economic value of the oil reserves that require RTM to be localized is very high, this means that the development of these algorithms becomes a competitive differentiator for companies seismic processing. But, it requires great computational power, that it still somehow harms its practical success. The objective of this work is to explore the implementation of this algorithm in unconventional architectures, specifically GPUs using the CUDA by making an analysis of the difficulties in developing the same, as well as the performance of the algorithm in the sequential and parallel version

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The growing importance of tourism in overall economic activity worldwide has favored the intensification of competition among cities that seek to create environments attractive to tourists and potential investors. It has been common practice to import characteristics of the business environment in the public management of cities. The city marketing is a key tool used by public leaders to promote a linkage between the tourism image and urban image and involves, in addition to promoting the image of the city, the planning of interventions in urban space, trying to formulate a positive image of the city able to facilitate the deployment of capital. This research seeks to understand the nature of city marketing as part of contemporary urban management and analyzes how is its application in decisions concerning the promotion of tourism in Natal/RN. The approach of this research is qualitative, exploratory and descriptive, in which respondents were the main leaders of two of the official tourism site, the Empresa Potiguar de Promoção Turística and the Secretaria Municipal de Turismo e Desenvolvimento Econômico. It was found that there is a strong articulation of public power with private enterprise in the design and conduct of the actions of urban marketing, that from the survey data show that the behavior of target markets provide guidelines for taking strategic decisions relating to tourism. Sun and sea are some key elements explored to form the image of Natal and to authorize the sale of the city as a tropical paradise. However, there is an increase in the diversification of tourism products, seeking to increase flow to the segments of ecotourism, adventure, business and culture. It s also growing the use of local culture as a tourism product, however, the cultural representation focuses on superficial values and does not bring to light the social and historical richness that the city has. Public authorities use the city marketing strategies as a means able to maximize the attractiveness of Natal urban space to investors, business groups and tourists. It can be observed that urban managers seek solutions that can continuously increase the tours, which often manifests in interventions that focus the tourist areas of the city, in oposition of those who do not contribute to a positive reading of the city, which ultimately generate the worsening of spacial and social inequalities