25 resultados para Digital image processing
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
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
Resumo:
This work presents the results of a survey in oil-producing region of the Macau City, northern coast of Rio Grande do Norte. All work was performed under the Project for Monitoring Environmental Change and the Influence of Hydrodynamic forcing on Morphology Beach Grass Fields, Serra Potiguar in Macau, with the support of the Laboratory of Geoprocessing, linked to PRH22 - Training Program in Geology Geophysics and Information Technology Oil and Gas - Department of Geology/CCET/UFRN and the Post-Graduation in Science and Engineering Oil/PPGCEP/UFRN. Within the economic-ecological context, this paper assesses the importance of mangrove ecosystem in the region of Macau and its surroundings as well as in the following investigative exploration of potential areas for projects involving reforestation and / or Environmental Restoration. At first it was confirmed the ecological potential of mangrove forests, with primary functions: (i) protection and stabilization of the shoreline, (ii) nursery of marine life, and (iii) source of organic matter to aquatic ecosystems, (iv) refuge of species, among others. In the second phase, using Landsat imagery and techniques of Digital Image Processing (DIP), I came across about 18,000 acres of land that can be worked on environmental projects, being inserted in the rules signed the Kyoto Protocol to the market carbon. The results also revealed a total area of 14,723.75 hectares of activity of shrimp production and salting that can be harnessed for the social, economic and environmental potential of the region, considering that over 60% of this area, ie, 8,800 acres, may be used in the planting of the genus Avicennia considered by the literature that the species best sequesters atmospheric carbon, reaching a mean value of 59.79 tons / ha of mangrove
Resumo:
In this work, spoke about the importance of image compression for the industry, it is known that processing and image storage is always a challenge in petrobrás to optimize the storage time and store a maximum number of images and data. We present an interactive system for processing and storing images in the wavelet domain and an interface for digital image processing. The proposal is based on the Peano function and wavelet transform in 1D. The storage system aims to optimize the computational space, both for storage and for transmission of images. Being necessary to the application of the Peano function to linearize the images and the 1D wavelet transform to decompose it. These applications allow you to extract relevant information for the storage of an image with a lower computational cost and with a very small margin of error when comparing the images, original and processed, ie, there is little loss of quality when applying the processing system presented . The results obtained from the information extracted from the images are displayed in a graphical interface. It is through the graphical user interface that the user uses the files to view and analyze the results of the programs directly on the computer screen without the worry of dealing with the source code. The graphical user interface, programs for image processing via Peano Function and Wavelet Transform 1D, were developed in Java language, allowing a direct exchange of information between them and the user
Resumo:
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
Resumo:
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
Resumo:
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
Resumo:
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 inteligente para detecção de manchas de óleo na superfície marinha através de imagens de SAR
Resumo:
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
Resumo:
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
Resumo:
The studied region, named Forquilha and localized in northwestern Central Ceará domain (northern portion of Borborema Province), presents a lithostratigraphic framework constituted by paleoproterozoic metaplutonics, metasedimentary sequences and neoproterozoic granitoids. The metasedimentary rocks of Ceará group occupy most part of the area. This group is subdivided in two distinct units: Canindé and Independência. Canindé unit is represented basically by biotite paragneisses and muscovite paragneisses, with minor metabasic rocks (amphibolite lens). Independência sequence is composed by garnetiferous paragneisses, sillimanite-garnet-quartz-muscovite schists and quartz-muscovite schists, pure or muscovite quartzites and rare marbles. At least three ductile deformation events were recognized in both units of Ceará group, named D1, D2 and D3. The former one is interpreted as related to a low angle tangential tectonics which mass transport is southward. D2 event is marked by the development of close/isoclinal folds with a N-S oriented axis. Refolding patterns generated by F1 and F2 superposition are found in several places. The latest event (D3) corresponds to a transcurrent tectonics, which led to development of mega-folds and several shear zones, under a transpressional regime. The mapped shear zones are Humberto Monte (ZCHM), Poço Cercado (ZCPC) and Forquilha (ZCF). Digital image processing of enhanced Landsat 7-ETM+ satellite images, combined with field data, demonstrate that these penetrative structures are associated with positive and negative geomorphologic patterns, distributed in linear and curvilinear arrangements with tonal banding, corresponding to the ductile fabric and to crests. Diverse color composites were tested and RGB-531 and RGB-752 provided the best results for lineament analysis of the most prominent shear zones. Spatial filtering techniques (3x3 and 5x5 filters) were also used and the application of Prewitt filters generated the best products. The integrated analysis of morphological and textural aspects from filtered images, variation of tonalities related to the distribution of geologic units in color composites and the superposition over a digital elevation model, contributed to a characterization of the structural framework of the study area. Kinematic compatibility of ZCHM, ZCPC, ZCF shear zones, as well as Sobral-Pedro II (ZCSPII) shear zone, situated to the west of the study area, was one of the goal of this work. Two of these shear zones (ZCHM, ZCPC) display sinistral movements, while the others (ZCSPII, ZCF) exhibit dextral kinematics. 40Ar/39Ar ages obtained in this thesis for ZCSPII and ZCPC, associated with other 40Ar/39Ar data of adjacent areas, indicate that all these shear zones are related to Brasiliano orogeny. The trend of the structures, the opposite shear senses and the similar metamorphic conditions are fitted in a model based on the development of conjugate shear zones in an unconfined transpression area. A WNW-ESE bulk shortening direction is infered. The geometry and kinematic of the studied structures suggest that shortening was largely accommodated by lateral extrusion, with only minor amounts of vertical stretch
Resumo:
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.
Resumo:
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
Resumo:
In the shallow continental shelf in Northeastern Rio Grande do Norte - Brazil, important underwater geomorphological features can be found 6km from the coastline. They are coral reefs, locally known as “parrachos”. The present study aims to characterize and analyze the geomorphological feature as well as the ones of the benthic surface, and the distribution of biogenic sediments found in parrachos at Rio do Fogo and associated shallow platforms, by using remote sensing products and in situ data collections. This was made possible due to sedimentological, bathymetric and geomorphological maps elaborated from composite bands of images from the satellite sensors ETM+/Landsat-7, OLI/Landsat-8, MS/GeoEye and PAN/WordView-1, and analysis of bottom sediments samples. These maps were analyzed, integrally interpreted and validated in fieldwork, thus permitting the generation of a new geomorphological zoning of the shallow shelf in study and a geoenvironmental map of the Parrachos in Rio do Fogo. The images used were subject to Digital Image Processing techniques. All obtained data and information were stored in a Geographic Information System (GIS) and can become available to the scientific community. This shallow platform has a carbonate bottom composed mostly by algae. Collected and analyzed sediment samples can be classified as biogenic carbonatic sands, as they are composed 75% by calcareous algae, according to the found samples. The most abundant classes are green algae, red algae, nonbiogenic sediments (mineral grains), ancient algae and molluscs. At the parrachos the following was mapped: Barreta Channel, intertidal reefs, submerged reefs, the spur and grooves, the pools, the sandy bank, the bank of algae, sea grass, submerged roads and Rio do Fogo Channel. This work presents new information about geomorphology and evolution in the study area, and will be guiding future decision making in the handling and environmental management of the region
Resumo:
Automatic detection of blood components is an important topic in the field of hematology. The segmentation is an important stage because it allows components to be grouped into common areas and processed separately and leukocyte differential classification enables them to be analyzed separately. With the auto-segmentation and differential classification, this work is contributing to the analysis process of blood components by providing tools that reduce the manual labor and increasing its accuracy and efficiency. Using techniques of digital image processing associated with a generic and automatic fuzzy approach, this work proposes two Fuzzy Inference Systems, defined as I and II, for autosegmentation of blood components and leukocyte differential classification, respectively, in microscopic images smears. Using the Fuzzy Inference System I, the proposed technique performs the segmentation of the image in four regions: the leukocyte’s nucleus and cytoplasm, erythrocyte and plasma area and using the Fuzzy Inference System II and the segmented leukocyte (nucleus and cytoplasm) classify them differentially in five types: basophils, eosinophils, lymphocytes, monocytes and neutrophils. Were used for testing 530 images containing microscopic samples of blood smears with different methods. The images were processed and its accuracy indices and Gold Standards were calculated and compared with the manual results and other results found at literature for the same problems. Regarding segmentation, a technique developed showed percentages of accuracy of 97.31% for leukocytes, 95.39% to erythrocytes and 95.06% for blood plasma. As for the differential classification, the percentage varied between 92.98% and 98.39% for the different leukocyte types. In addition to promoting auto-segmentation and differential classification, the proposed technique also contributes to the definition of new descriptors and the construction of an image database using various processes hematological staining
Resumo:
The understanding of the occurrence and flow of groundwater in the subsurface is of fundamental importance in the exploitation of water, just like knowledge of all associated hydrogeological context. These factors are primarily controlled by geometry of a certain pore system, given the nature of sedimentary aquifers. Thus, the microstructural characterization, as the interconnectivity of the system, it is essential to know the macro properties porosity and permeability of reservoir rock, in which can be done on a statistical characterization by twodimensional analysis. The latter is being held on a computing platform, using image thin sections of reservoir rock, allowing the prediction of the properties effective porosity and hydraulic conductivity. For Barreiras Aquifer to obtain such parameters derived primarily from the interpretation of tests of aquifers, a practice that usually involves a fairly complex logistics in terms of equipment and personnel required in addition to high cost of operation. Thus, the analysis and digital image processing is presented as an alternative tool for the characterization of hydraulic parameters, showing up as a practical and inexpensive method. This methodology is based on a flowchart work involving sampling, preparation of thin sections and their respective images, segmentation and geometric characterization, three-dimensional reconstruction and flow simulation. In this research, computational image analysis of thin sections of rocks has shown that aquifer storage coefficients ranging from 0,035 to 0,12 with an average of 0,076, while its hydrogeological substrate (associated with the top of the carbonate sequence outcropping not region) presents effective porosities of the order of 2%. For the transport regime, it is evidenced that the methodology presents results below of those found in the bibliographic data relating to hydraulic conductivity, mean values of 1,04 x10-6 m/s, with fluctuations between 2,94 x10-6 m/s and 3,61x10-8 m/s, probably due to the larger scale study and the heterogeneity of the medium studied.