21 resultados para Digital Images

em Universidade Federal do Rio Grande do Norte(UFRN)


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The North Paraíba River Estuary, located in the eastern portion of the Paraíba State, Northeast Brazil, on coordinates 34º50 00 -34º57 30 S and 6º55 00 -7º7 30 W, constitutes a fluvio-marine plain formed by the North Paraíba River and its tributaries Sanhauá, Paroeira, Mandacaru, Tiriri, Tambiá, Ribeira and Guia. This estuary comprises an area of about 260 km2. Increasing human demands on the estuary area and inadequate environment managing have generated conflicts. The present work main purpose is to evaluate the geodynamic evolution of the North Paraíba River Estuary in the period from 1969 to 2001, using digital image processing techniques, thematic digital cartography and multitemporal data integration, combined to geological-geophysical field surveys. The SUDENE cartographic database, converted to digital format were, used to obtain occupation and topographic maps from 1969 and to generate a Digital Elevation Model (DEM). Digital Landsat 7 ETM+ and Spot HRVIR-PAN satellite images interpretation allowed the environmental characterization of the estuary. The most important digital processing results were achieved color composites RGB 5-4-3, 5-3-1, 5-2-NDWI and band ratio 7/4-5/3-4/2, 5/7-3/1-5/4). In addition the fusion image technique RGBI was used by the inclusion of the Spot HRVRI and Landsat 7 ETM+ panchromatic band on I layer with RGB triplets 5-4-3, 5-3-1 and 5/7-3/1-5/4. The DEM and digital images integration allowed the identification of seven geomorphological units: coastal tableland, flowing tray, tide plain, fluvial terrace, submerged dune, beach plain and beach). Both Side Scan Sonar and Echosound were used to analyse underwater surface and bedforms of the estuarine channel, sand predominance (fine to very fine) and 2D dune features 5 m wide and 0.5 m height. This investigation characterized the estuary as an environment dominated by regimen of average flow. The channel depth varies between 1 m and 11 m, being this last quota reached in the area of Porto de Cabedelo. The chanel estuary is relatively shallow, with erosion evidences mainly on its superior portion, attested by sand banks exposed during the low tide. Multitemporal digital maps from 1969 and 2001 integration were obtained through geoprocessing techniques, resulting the geodynamic evolution of the estuary based on landuse, DEM geomorphology and bathymetric maps

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Since centuries ago, the Asians use seaweed as an important source of feeding and are their greatest world-wide consumers. The migration of these peoples for other countries, made the demand for seaweed to increase. This increasing demand prompted an industry with annual values of around US$ 6 billion. The algal biomass used for the industry is collected in natural reservoirs or cultivated. The market necessity for products of the seaweed base promotes an unsustainable exploration of the natural banks, compromising its associated biological balance. In this context, seaweed culture appears as a viable alternative to prevent the depletion of these natural supplies. Geographic Information Systems (GIS) provide space and produce information that can facilitate the evaluation of important physical and socio-economic characteristics for the planning of seaweed culture. This objective of this study is to identify potential coastal areas for seaweed culture in the state of Rio Grande do Norte, from the integration of social-environmental data in the SIG. In order to achieve this objective, a geo-referred database composed of geographical maps, nautical maps and orbital digital images was assembled; and a bank of attributes including physical and oceanographical variables (winds, chains, bathymetry, operational distance from the culture) and social and environmental factors (main income, experience with seaweed harvesting, demographic density, proximity of the sheltered coast and distance of the banks) was produced. In the modeling of the data, the integration of the space database with the bank of attributes for the attainment of the map of potentiality of seaweed culture was carried out. Of a total of 2,011 ha analyzed by the GIS for the culture of seaweed, around 34% or 682 ha were indicated as high potential, 55% or 1,101 ha as medium potential, and 11% or 228 ha as low potential. The good indices of potentiality obtained in the localities studied demonstrate that there are adequate conditions for the installation of seaweed culture in the state of Rio Grande do Norte

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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

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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

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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

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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

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In this work, we propose a multi agent system for digital image steganalysis, based on the poliginic bees model. Such approach aims to solve the problem of automatic steganalysis for digital media, with a case study on digital images. The system architecture was designed not only to detect if a file is suspicious of covering a hidden message, as well to extract the hidden message or information regarding it. Several experiments were performed whose results confirm a substantial enhancement (from 67% to 82% success rate) by using the multi-agent approach, fact not observed in traditional systems. An ongoing application using the technique is the detection of anomalies in digital data produced by sensors that capture brain emissions in little animals. The detection of such anomalies can be used to prove theories and evidences of imagery completion during sleep provided by the brain in visual cortex areas

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The aim of this study is to investigate the eco-environmental vulnerability, its changes, and its causes to develop a management system for application of eco-environmental vulnerability and risk assessment in the Apodi-Mossory estuary, Northeast Brazil. This analysis is focused on the interference of the landscape conditions, and its changes, due to the following factors: the oil and natural gas industry, tropical fruits industry, shrimp farms, marine salt industry, occupation of the sensitive areas; demand for land, vegetation degradation, siltation in rivers, severe flooding, sea level rise (SLR), coastal dynamics, low and flat topography, high ecological value and tourism in the region and the rapid growth of urbanization. Conventional and remote sensing data were analyzed using modeling techniques based on ArcGIS, ER-Mapper, ERDAS Imagine and ENVI software. Digital images were initially processed by Principal Component Analysis and transformation of the maximum fraction of noise, and then all bands were normalized to reduce errors caused by bands of different sizes. They were integrated in a Geographic Information System analysis to detect changes, to generate digital elevation models, geomorphic indices and other variables of the study area. A three band color combination of multispectral bands was used to monitor changes of land and vegetation cover from 1986 to 2009. This task also included the analysis of various secondary data, such as field data, socioeconomic data, environmental data and prospects growth. The main objective of this study was to improve our understanding of eco-environmental vulnerability and risk assessment; it´s causes basically show the intensity, its distribution and human-environment effect on the ecosystem, and identify the high and low sensitive areas and area of inundation due to future SLR, and the loss of land due to coastal erosion in the Apodi-Mossoró estuary in order to establish a strategy for sustainable land use. The developed model includes some basic factors such as geology, geomorphology, soils, land use / land cover, vegetation cover, slope, topography and hydrology. The numerical results indicate that 9.86% of total study area was under very high vulnerability, 29.12% high vulnerability, 52.90% moderate vulnerability and 2.23% were in the category of very low vulnerability. The analysis indicates that 216.1 km² and 362.8 km² area flooded on 1m and 10m in sea levels respectively. The sectors most affected were residential, industrial and recreational areas, agricultural land, and ecosystems of high environmental sensitivity. The results showed that changes in eco-environmental vulnerability have a significant impact on the sustainable development of the RN state, since the indicator is a function of sensitivity, exposure and status in relation to a level of damage. The model were presented as a tool to assist in indexing vulnerability in order to optimize actions and assess the implications of decisions makers and policies regarding the management of coastal and estuarine areas. In this context aspects such as population growth, degradation of vegetation, land use / land cover, amount and type of industrialization, SLR and government policies for environmental protection were considered the main factors that affect the eco-environmental changes over the last three decades in the Apodi-Mossoró estuary.

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Image segmentation is the process of labeling pixels on di erent objects, an important step in many image processing systems. This work proposes a clustering method for the segmentation of color digital images with textural features. This is done by reducing the dimensionality of histograms of color images and using the Skew Divergence to calculate the fuzzy a nity functions. This approach is appropriate for segmenting images that have colorful textural features such as geological, dermoscopic and other natural images, as images containing mountains, grass or forests. Furthermore, experimental results of colored texture clustering using images of aquifers' sedimentary porous rocks are presented and analyzed in terms of precision to verify its e ectiveness.

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The study area islocated in the northern cost of Rio Grande do Norte State, preciselyin a west zone of Apodi-Mossoró River, inclunding Tibau City, Grossos City and part of Mossoró City. Geologicaly, this area is composed by rokcs of Potiguar basin, represented by Cretaceous, Tertiary and Quaternary sediments. This area is characterizer by the intense action of cosatal processes (eolic and costal tranports, generalized erosion, alteration in the sediments balance and coast modification), reponsable for it´s morfological instability, also the antropic interference, where the iol industry is located, next Mossoró City, and also the salt exploration industry and the tendency of expantion of shrimp cultivation. This report had as objective the multitemporalgeoenvorimentalmonitoring of the region by recognizingin the field and analizingimages of orbital sensors of diferents years of last four decades. This analisys was achieved by Digital Images Procesing (DIP) thecnics, com subsidized, in a GIS, the preparion of Thematic Maps of natural resources (Geology, Geomorphology and Use & Ocupatios of Earth) and the Envorimental Sensivity to Oil Spilling, main objective os this project. Such technics constitute important tools of envoriment monitoring and maneging, indicating tendencies of antropic of natural growing, making possible the apropiated planning of development of the region, where the steps can be indicated minimized possibles envorimental impacts caused by antropics interferencies on the region, mainly those related to industrial activities, and oil industry above all. Researchs of this nature are very important to the analisys and ordered manegements of use and ocupation of coastal places

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This work embraces the application of Landsat 5-TM digital images, comprising August 2 1989 and September 22 1998, for temporal mapping and geoenvironmental analysis of the dynamic of Piranhas-Açu river mouth, situated in the Macau (RN) region. After treatment using several digital processing techniques (e.g. colour composition in RGB, ratio of bands, principal component analysis, index methods, among others), it was possible to generate several image products and multitemporal maps of the coastal morphodynamics of the studied area. Using the image products it was possible the identification and characterization of the principal elements of interest (vegetation, soil, geology and water) in the surface of the studied area, associating the spectral characteristics of these elements to that presented by the image products resulting of the digital processing. Thus, it was possible to define different types of soils: Amd, AQd6, SK1 and LVe4; vegetation grouping: open arboreal-shrubby caatinga, closed arborealshrubby caatinga, closed arboreal caatinga, mangrove vegetation, dune vegetation and areas predominately constituted by juremas; geological units: quaternary units beach sediments, sand banks, dune flats, barrier island, mobile dunes, fixed dunes, alluvium, tidal and inundation flats, and sandy facies of the Potengi Formation; tertiary-quaternary units Barreiras Formation grouped to the clayey facies of the Potengi Formation, Macau Formation grouped to the sediments of the Tibau Formation; Cretaceous units Jandaíra Formation; moreover it was to identify the sea/land limit, shallow submersed areas and suspended sediments. The multitemporal maps of the coastal morphodynamics allowed the identification and a semi-quantitative evoluation of regions which were submitted to erosive and constructive processes in the last decade. This semi-quantitative evoluation in association with an geoenvironmental characterization of the studied area are important data to the elaboration of actions that may minimize the possible/probable impacts caused by the implantation of the Polo Gas/Sal and to the monitoring of areas explorated by the petroleum and salt industries

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This study had to aimed to characterize the sediments of shallow continental shelf and realize the mapping of features visible for satellite images by using remote sensing techniques, digital image processing and analysis of bathymetry between Maxaranguape and Touros - RN. The study s area is located in the continental shallow shelf of Rio Grande do Norte, Brazil, and is part of the Environmental Protection Area (APA) of Coral Reefs. A total of 1186 sediment samples were collected using a dredge type van veen and positioning of the vessel was made out with the aid of a Garmin 520s. The samples were treated In the laboratory to analyze particle size of the sediment, concentration of calcium carbonate and biogenic composition. The digital images from the Landsat-5 TM were used to mapping of features. This stage was used the band 1 (0,45-1,52 μm) where the image were georeferenced, and then adjusting the histogram, giving a better view of feature bottom and contacts between different types of bottom. The results obtained from analysis of the sediment showed that the sediments of the continental shelf east of RN have a dominance of carbonate facies and a sand-gravelly bottom because the region is dominated by biogenic sediments, that are made mainly of calcareous algae. The bedform types identified and morphological features found were validated by bathymetric data and sediment samples examined. From the results obtained a division for the shelf under study is suggested, these regions being subdivided, in well characterized: (1) Turbid Zone, (2) Coral Patch Reefs Zone, (3) Mixed Sediments Carbonates Zone, ( 4) Algae Fouling Zone, (5) Alignment Rocky Zone, (6) Sand Waves Field (7) Deposit siliciclastic sands

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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

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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

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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.