Dinâmica da paisagem no litoral oriental do Rio Grande do Norte: geocartografia e padrões espaciais dos campos de dunas móveis

This study shows the results of a research developed in the coastal regions of the Maxaranguape and Touros municipalities, more specific in the mobile dune fields of the Rio Grande do Norte's eastern coast. Although the coastal zones, represent a small percentage of the earth's surface it concentrates a great part of the world's population. The Rio Grande do Norte's state coastal landscape mosaic composed by the dune fields suggest a dynamic scene of changes in the spatial and temporal arranges, with significant changes in the geometry of the sedimentary cover. Following this perspective this research has the objective to map the emerged coastal zone of the Rio Grande do Norte's eastern coast under the perspective of the time-space evolution of the mobile dune fields using geoprocessing techniques, which includes remote sensing, digital images processing and geographic information system (GIS). The results imply the issue of thematic maps: Geologic map; multitemporal evolution map of the mobile dune fields; quantification of the mobile dune fields differences map; temporal evolution of the mobile dune fields surrounds map. The El Niño episodes have directly affected the atmospheric circulation, what have enhanced the sedimentary input in the sand dune, what can justify the relative area growth between the years of 1993 and 2001. The dynamic of the landscape transition were higher than the stability of the spatial pattern of the dune and it's surrounds, as a result the Rio Grande do Norte eastern coast dune fields, specially the mobile dunes from Touros, Zumbi and Maracajau have shown a decrease on the sedimentary cover without vegetation area from 1970 to 2007. Therefore, the data acquired and the techniques used, can be, eventually applied to the mobile dune fields monitoring in order to preserve the dune ecosystems in the Rio Grande do Norte coast

Aplicação de softwares livres no Processamento de dados sísmicos de alta resolução

The increasing use of shallow seismic methods of high resolution, for investigations of geological problems, environmental or industrial, has impelled the development of techniques, flows and computational algorithms. The practice of applying techniques for processing this data, until recently it wasn t used and the interpretation of the data was made as they were acquired. In order to facilitate and contribute to the improvement of the practices adopted, was developed a free graphical application and open source, called OpenSeismic which is based on free software Seismic Un*x, widely used in the treatment of conventional seismic data used in the exploration of hydrocarbon reservoirs. The data used to validate the initiative were marine seismic data of high resolution, acquired by the laboratory of Geology and Marine Geophysics and Environmental Monitoring - GGEMMA, of the Federal University of Rio Grande do Norte UFRN, for the SISPLAT Project, located at the region of paleo-valley of the Rio Acu. These data were submitted to the processing flow developed by Gomes (2009), using the free software developed in this work, the OpenSeismic, as well other free software, the Seismic Un*x and the commercial software ProMAX, where despite its peculiarities has presented similar results

Qualidade fisiológica de sementes de Moringa oleifera lam. por meio da análise de imagens

Several tests that evaluate the quality of seeds are destructive and require time, which is considered long and expensive in the processes that involves the production and marketing of seed. Thus, techniques that allow reducing the time related to assess the quality of seed lots is very favorable, considering the technical, economic and scientific point of view. The techniques images of seed analyzed both by X-ray such as digital images, represent alternative for this sector, and are considered reproducible and fast, giving greater flexibility and autonomy to the activities of production systems. Summarily, the objective was to analyze the internal morphology of seeds of this species through x-rayed images and the efficiency of weed seed area increased during soaking through image analysis and compare them with the results of germination tests and force the evaluation of physiological seed quality. For X-ray tests, the seeds were exposed for 0.14 seconds at radiation 40kV and 2.0 mAs. Were analyzed images using the ImageJ program and subsequently put to germinate in B.O.D chamber at 27 ° C, in which there was the comparison of results for germination. To determine the test area increase (% IA), seeds were used with and without seed coat, maintained the B.O.D chamber at 15 ° to 20 ° C, the seeds were photographed before and after the soaking period, the results were compared to the germination rates. For the X-ray test, it was observed that seeds with empty area greater than 20%, showed a higher percentage of abnormal seedlings. And the area increment analysis showed that it is possible to rank the batch after 8 hours of imbibition at 15 ° C according to the germination and vigor tests

Classificação de imagens de ambientes coralinos: uma abordagem empregando uma combinação de classificadores e máquina de vetor de suporte

The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column

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 neuronais de agrupamentos aplicadas à detecção de anomalias em mamogramas digitais

This work proposes the development of an intelligent system for analysis of digital mammograms, capable to detect and to classify masses and microcalcifications. The digital mammograms will be pre-processed through techniques of digital processing of images with the purpose of adapting the image to the detection system and automatic classification of the existent calcifications in the suckles. The model adopted for the detection and classification of the mammograms uses the neural network of Kohonen by the algorithm Self Organization Map - SOM. The algorithm of Vector quantization, Kmeans it is also used with the same purpose of the SOM. An analysis of the performance of the two algorithms in the automatic classification of digital mammograms is developed. The developed system will aid the radiologist in the diagnosis and accompaniment of the development of abnormalities

Sistema auxiliar na análise de mamogramas digitais

This work proposes the development of a Computer System for Analysis of Mammograms SCAM, that aids the doctor specialist in the identification and analysis of existent lesions in digital mammograms. The computer system for digital mammograms processing will make use of a group of techniques of Digital Image Processing (DIP), with the purpose of aiding the medical professional to extract the information contained in the mammogram. This system possesses an interface of easy use for the user, allowing, starting from the supplied mammogram, a group of processing operations, such as, the enrich of the images through filtering techniques, the segmentation of areas of the mammogram, the calculation the area of the lesions, thresholding the lesion, and other important tools for the medical professional's diagnosis. The Wavelet Transform will used and integrated into the computer system, with the objective of allowing a multiresolution analysis, thus supplying a method for identifying and analyzing microcalcifications

Posicionamento e movimentação de um robô humanóide utilizando imagens de uma câmera móvel externa

This work proposes a method to localize a simple humanoid robot, without embedded sensors, using images taken from an extern camera and image processing techniques. Once the robot is localized relative to the camera, supposing we know the position of the camera relative to the world, we can compute the position of the robot relative to the world. To make the camera move in the work space, we will use another mobile robot with wheels, which has a precise locating system, and will place the camera on it. Once the humanoid is localized in the work space, we can take the necessary actions to move it. Simultaneously, we will move the camera robot, so it will take good images of the humanoid. The mainly contributions of this work are: the idea of using another mobile robot to aid the navigation of a humanoid robot without and advanced embedded electronics; chosing of the intrinsic and extrinsic calibration methods appropriated to the task, especially in the real time part; and the collaborative algorithm of simultaneous navigation of the robots

Odometria visual baseada em técnicas de structure from motion

Visual Odometry is the process that estimates camera position and orientation based solely on images and in features (projections of visual landmarks present in the scene) extraced from them. With the increasing advance of Computer Vision algorithms and computer processing power, the subarea known as Structure from Motion (SFM) started to supply mathematical tools composing localization systems for robotics and Augmented Reality applications, in contrast with its initial purpose of being used in inherently offline solutions aiming 3D reconstruction and image based modelling. In that way, this work proposes a pipeline to obtain relative position featuring a previously calibrated camera as positional sensor and based entirely on models and algorithms from SFM. Techniques usually applied in camera localization systems such as Kalman filters and particle filters are not used, making unnecessary additional information like probabilistic models for camera state transition. Experiments assessing both 3D reconstruction quality and camera position estimated by the system were performed, in which image sequences captured in reallistic scenarios were processed and compared to localization data gathered from a mobile robotic platform

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

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

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

Geoprocessamento aplicado a gestão de informações territoriais do município de Grossos-RN :estudo multitemporal do uso e ocupação do solo

The present work was carried through in the Grossos city - RN and had as main objectives the elaboration of an physicist-ambient, socioeconomic survey and execution a multisecular evaluation of 11 years, between 1986 and 1996, using remote sensing products, to evaluate the modifications of the land use, aiming at the generation of an information database to implementation a geographical information system (GIS) to management the this city. For they had been in such a way raised given referring the two Demographic Censuses carried through by the IBGE (1991 and 2000) and compared, of this form was possible to the accomplishment of an evaluation on the demographic aspects (degree of urbanization, etária structure, educational level) and economic (income, habitation, vulnerability, human development). For the ambient physical survey the maps of the natural resources had been confectioned (simplified geology, hydrography, geomorphologi, veget covering, ground association, use and occupation), based in comments of field and orbital products of remote sensoriamento (images Spot-HRVIR, Landsat 5-TM and IKONOS - II), using itself of techniques of digital picture processing. The survey of these data and important in the identification of the potentialities and fragilities of found ecosystems, therefore allows an adequate planning of the partner-economic development by means of an efficient management. The project was part of a partnership between the Grossos city hall the municipal City hall of Grossos - RN and the Geoscience post-graduate program of the UFRN, more specifically the Geomatica laboratory LAGEOMA

Uso de técnicas de Geoprocessamento e Sensoriamento Remoto no levantamento e integração de dados necessários a gestão ambiental dos campos de extração de óleo e gás do Canto do Amaro e Alto da Pedra no município de Mossoró - RN

The objective of this work is to identify, to chart and to explain the evolution of the soil occupation and the envirionment vulnerability of the areas of Canto do Amaro and Alto da Pedra, in the city of Mossoró-RN, having as base analyzes it multiweather of images of orbital remote sensors, the accomplishment of extensive integrated works of field to a Geographic Information System (GIS). With the use of inserted techniques of it analyzes space inserted in a (GIS), and related with the interpretation and analyzes of products that comes from the Remote Sensoriamento (RS.), make possible resulted significant to reach the objectives of this works. Having as support for the management of the information, the data set gotten of the most varied sources and stored in digital environment, it comes to constitute the geographic data base of this research. The previous knowledge of the spectral behavior of the natural or artificial targets, and the use of algorithms of Processing of Digital images (DIP), it facilitates the interpretation task sufficiently and searchs of new information on the spectral level. Use as background these data, was generated a varied thematic cartography was: Maps of Geology, Geomorfológicals Units soils, Vegetation and Use and Occupation of the soil. The crossing in environment SIG, of the above-mentioned maps, generated the maps of Natural and Vulnerability envirionmental of the petroliferous fields of I Canto do Amaro and Alto da Pedra-RN, working in an ambient centered in the management of waters and solid residuos, as well as the analysis of the spatial data, making possible then a more complex analysis of the studied area

Renderizações não fotorealísticas para estilização de imagens e vídeos usando areia colorida

Non-Photorealisitc Rendering (NPR) is a class of techniques that aims to reproduce artistic techniques, trying to express feelings and moods on the rendered scenes, giving an aspect of that they had been made "by hand". Another way of defining NPR is that it is the processing of scenes, images or videos into artwork, generating scenes, images or videos that can have the visual appeal of pieces of art, expressing the visual and emotional characteristics of artistic styles. This dissertation presents a new method of NPR for stylization of images and videos, based on a typical artistic expression of the Northeast region of Brazil, that uses colored sand to compose landscape images on the inner surface of glass bottles. This method is comprised by one technique for generating 2D procedural textures of sand, and two techniques that mimic effects created by the artists using their tools. It also presents a method for generating 21 2D animations in sandbox from the stylized video. The temporal coherence within these stylized videos can be enforced on individual objects with the aid of a video segmentation algorithm. The present techniques in this work were used on stylization of synthetic and real videos, something close to impossible to be produced by artist in real life