991 resultados para Digital Image Correlation
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Image segmentation is a process frequently used in several different areas including Cartography. Feature extraction is a very troublesome task, and successful results require more complex techniques and good quality data. The aims of this paper is to study Digital Image Processing techniques, with emphasis in Mathematical Morphology, to use Remote Sensing imagery, making image segmentation, using morphological operators, mainly the multi-scale morphological gradient operator. In the segmentation process, pre-processing operators of Mathematical Morphology were used, and the multi-scales gradient was implemented to create one of the images used as marker image. Orbital image of the Landsat satellite, sensor TM was used. The MATLAB software was used in the implementation of the routines. With the accomplishment of tests, the performance of the implemented operators was verified and carried through the analysis of the results. The extration of linear feature, using mathematical morphology techniques, can contribute in cartographic applications, as cartographic products updating. The comparison to the best result obtained was performed by means of the morphology with conventional techniques of features extraction. © Springer-Verlag 2004.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Objective: The purpose of this study was to analyse the use of digital tools for image enhancement of mandibular radiolucent lesions and the effects of this manipulation on the percentage of correct radiographic diagnoses. Methods: 24 panoramic radiographs exhibiting radiolucent lesions were selected, digitized and evaluated by non-experts (undergraduate and newly graduated practitioners) and by professional experts in oral diagnosis. The percentages of correct and incorrect diagnoses, according to the use of brightness/contrast, sharpness, inversion, highlight and zoom tools, were compared. All dental professionals made their evaluations without (T-1) and with (T-2) a list of radiographic diagnostic parameters. Results: Digital tools were used with low frequency mainly in T-2. The most preferred tool was sharpness (45.2%). In the expert group, the percentage of correct diagnoses did not change when any of the digital tools were used. For the non-expert group, there was an increase in the frequency of correct diagnoses when brightness/contrast was used in T-2 (p = 0.008) and when brightness/contrast and sharpness were not used in T-1 (p = 0.027). The use or non-use of brightness/contrast, zoom and sharpness showed moderate agreement in the group of experts [kappa agreement coefficient (kappa) = 0.514, 0.425 and 0.335, respectively]. For the non-expert group there was slight agreement for all the tools used (kappa <= 0.237). Conclusions: Consulting the list of radiographic parameters before image manipulation reduced the frequency of tool use in both groups of examiners. Consulting the radiographic parameters with the use of some digital tools was important for improving correct diagnosis only in the group of non-expert examiners. Dentomaxillofacial Radiology (2012) 41, 203-210. doi: 10.1259/dmfr/78567773
Resumo:
A laser scanning microscope collects information from a thin, focal plane and ignores out of focus information. During the past few years it has become the standard imaging method to characterise cellular morphology and structures in static as well as in living samples. Laser scanning microscopy combined with digital image restoration is an excellent tool for analysing the cellular cytoarchitecture, expression of specific proteins and interactions of various cell types, thus defining valid criteria for the optimisation of cell culture models. We have used this tool to establish and evaluate a three dimensional model of the human epithelial airway wall.
Resumo:
Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.
Resumo:
OBJECTIVE: To develop a novel application of a tool for semi-automatic volume segmentation and adapt it for analysis of fetal cardiac cavities and vessels from heart volume datasets. METHODS: We studied retrospectively virtual cardiac volume cycles obtained with spatiotemporal image correlation (STIC) from six fetuses with postnatally confirmed diagnoses: four with normal hearts between 19 and 29 completed gestational weeks, one with d-transposition of the great arteries and one with hypoplastic left heart syndrome. The volumes were analyzed offline using a commercially available segmentation algorithm designed for ovarian folliculometry. Using this software, individual 'cavities' in a static volume are selected and assigned individual colors in cross-sections and in 3D-rendered views, and their dimensions (diameters and volumes) can be calculated. RESULTS: Individual segments of fetal cardiac cavities could be separated, adjacent segments merged and the resulting electronic casts studied in their spatial context. Volume measurements could also be performed. Exemplary images and interactive videoclips showing the segmented digital casts were generated. CONCLUSION: The approach presented here is an important step towards an automated fetal volume echocardiogram. It has the potential both to help in obtaining a correct structural diagnosis, and to generate exemplary visual displays of cardiac anatomy in normal and structurally abnormal cases for consultation and teaching.
Resumo:
Quantifying belowground dynamics is critical to our understanding of plant and ecosystem function and belowground carbon cycling, yet currently available tools for complex belowground image analyses are insufficient. We introduce novel techniques combining digital image processing tools and geographic information systems (GIS) analysis to permit semi-automated analysis of complex root and soil dynamics. We illustrate methodologies with imagery from microcosms, minirhizotrons, and a rhizotron, in upland and peatland soils. We provide guidelines for correct image capture, a method that automatically stitches together numerous minirhizotron images into one seamless image, and image analysis using image segmentation and classification in SPRING or change analysis in ArcMap. These methods facilitate spatial and temporal root and soil interaction studies, providing a framework to expand a more comprehensive understanding of belowground dynamics.
Resumo:
The paper showcases the field- and lab-documentation system developed for Kinneret Regional Project, an international archaeological expedition to the Northwestern shore of the Sea of Galilee (Israel) under the auspices of the University of Bern, the University of Helsinki, Leiden University and Wofford College. The core of the data management system is a fully relational, server-based database framework, which also includes time-based and static GIS services, stratigraphic analysis tools and fully indexed document/digital image archives. Data collection in the field is based on mobile, hand-held devices equipped with a custom-tailored stand-alone application. Comprehensive three-dimensional documentation of all finds and findings is achieved by means of total stations and/or high-precision GPS devices. All archaeological information retrieved in the field – including tachymetric data – is synched with the core system on the fly and thus immediately available for further processing in the field lab (within the local network) or for post-excavation analysis at remote institutions (via the WWW). Besides a short demonstration of the main functionalities, the paper also presents some of the key technologies used and illustrates usability aspects of the system’s individual components.
Resumo:
Quantification of protein expression based on immunohistochemistry (IHC) is an important step in clinical diagnoses and translational tissue-based research. Manual scoring systems are used in order to evaluate protein expression based on staining intensities and distribution patterns. However, visual scoring remains an inherently subjective approach. The aim of our study was to explore whether digital image analysis proves to be an alternative or even superior tool to quantify expression of membrane-bound proteins. We analyzed five membrane-binding biomarkers (HER2, EGFR, pEGFR, β-catenin, and E-cadherin) and performed IHC on tumor tissue microarrays from 153 esophageal adenocarcinomas patients from a single center study. The tissue cores were scored visually applying an established routine scoring system as well as by using digital image analysis obtaining a continuous spectrum of average staining intensity. Subsequently, we compared both assessments by survival analysis as an end point. There were no significant correlations with patient survival using visual scoring of β-catenin, E-cadherin, pEGFR, or HER2. In contrast, the results for digital image analysis approach indicated that there were significant associations with disease-free survival for β-catenin, E-cadherin, pEGFR, and HER2 (P = 0.0125, P = 0.0014, P = 0.0299, and P = 0.0096, respectively). For EGFR, there was a greater association with patient survival when digital image analysis was used compared to when visual scoring was (visual: P = 0.0045, image analysis: P < 0.0001). The results of this study indicated that digital image analysis was superior to visual scoring. Digital image analysis is more sensitive and, therefore, better able to detect biological differences within the tissues with greater accuracy. This increased sensitivity improves the quality of quantification.
Resumo:
Se aplicó un nuevo método para la evaluación objetiva del color en aceitunas de mesa, basado en el análisis de la intensidad de reflexión de cada uno de los colores primarios que componen la luz blanca (rojo, verde y azul), según las longitudes de onda del Sistema RGB. Se trabajó con programas informáticos para el análisis de imágenes digitales color tipo BMP de 24 bits. Este trabajo proporciona mayor información sobre el pardeamiento de las aceitunas naturales en salmuera, lo que sería muy útil para incrementar la efectividad del proceso. El método propuesto es rápido y no destructivo, prometiendo ser muy práctico ya que permite que una misma muestra pueda ser evaluada en el tiempo. Se investigaron los cambios de color en aceitunas elaboradas naturalmente, con diferentes grados de madurez (pintas, rojas y negras) y a diferentes valores de pH (3,6 - 4,0 - 4,5), expuestas al aire durante períodos crecientes de tiempo. Se cuantificó el grado de oscurecimiento a través de Índices de Intensidad de Reflexión. La evolución del índice de reflexión en función del tiempo generó una curva polinomial de 4° grado que reveló el comportamiento sigmoidal del fenómeno de pardeamiento enzimático, con la máxima correlación a las 8 horas de aireación. Esta función permitiría predecir el fenómeno de pardeamiento en las aceitunas negras y representa una medición objetiva del grado relativo de pardeamiento. La evolución del color rojo (λ = 700,0 nm) exhibió la mayor correlación con el proceso de pardeamiento. Las aceitunas rojas naturales a pH 4,5 presentaron óptimo pardeamiento. El espectro de reflexión para el color azul (λ = 435,8 nm) se sugiere como medida de la actividad de la enzima PPO (polifenoloxidasa).
Resumo:
Se propone la producción y posterior análisis de obras digitales que presenta una elaboración teórica-práctica intrínseca como sustento de las nuevas categorías y neologismos surgidos dentro del ámbito artístico digital. Se estudian distintas aplicaciones, modalidades de creación, exposición y transferencia al medio como así también las posibilidades relacionales que surgen entre imagen digital, objeto artístico y diseño de productos traspasando las fronteras de campos disciplinares como Arte y Diseño. La metodología empleada se concentra en enfoques sociológicos y semiótico-pragmáticos que permiten realizar un análisis profundo de las obras digitales en sí mismas y en relación a los contextos de producción, circulación, exposición y consumo.
Resumo:
El objetivo fue determinar, durante dos años, el contenido de β-caroteno y su relación con el Índice de Color (IC), de ocho cultivares comerciales del tipo 'Flakkee' cultivadas en el INTA La Consulta. El diseño experimental a campo utilizado fue en bloques al azar con 3 repeticiones. Se evaluó β-caroteno (espectrofotometría a 450 nm) y se calculó el IC, mediante captación de imagen digital con PC y escáner, midiendo L, a y b del Sistema CIELAB. Los datos fueron analizados por ACP (análisis de componentes principales), la visualización de la variabilidad, por cartografiado de datos, análisis de varianza, pruebas de diferencia de medias y correlaciones. Los contenidos de β-carotenos y el IC de los cultivares se mantuvieron constantes durante los dos años estudiados, resultando las cultivares Natasha, Flakesse y Colmar las de mayor valor nutricional en cuanto a aporte de β-carotenos. En el rango de valores menores de 18 mg%g de β-carotenos, se observó una correlación positiva significativa en las cultivares Supreme, Spring y Laval. No se encontró una correlación alta lineal entre el IC y el contenido de β-carotenos. El uso del IC resulta adecuado para predecir, en un intervalo de valores, el contenido de β-carotenos en cultivares de zanahoria.
Resumo:
Technological and environmental problems related to ore processing are a serious limitation for sustainable development of mineral resources, particularly for countries / companies rich in ores, but with little access to sophisticated technology, e.g. in Latin America. Digital image analysis (DIA) can provide a simple, unexpensive and broadly applicable methodology to assess these problems, but this methodology has to be carefully defined, to produce reproducible and relevant information.
Resumo:
Determination of the soil coverage by crop residues after ploughing is a fundamental element of Conservation Agriculture. This paper presents the application of genetic algorithms employed during the fine tuning of the segmentation process of a digital image with the aim of automatically quantifying the residue coverage. In other words, the objective is to achieve a segmentation that would permit the discrimination of the texture of the residue so that the output of the segmentation process is a binary image in which residue zones are isolated from the rest. The RGB images used come from a sample of images in which sections of terrain were photographed with a conventional camera positioned in zenith orientation atop a tripod. The images were taken outdoors under uncontrolled lighting conditions. Up to 92% similarity was achieved between the images obtained by the segmentation process proposed in this paper and the templates made by an elaborate manual tracing process. In addition to the proposed segmentation procedure and the fine tuning procedure that was developed, a global quantification of the soil coverage by residues for the sampled area was achieved that differed by only 0.85% from the quantification obtained using template images. Moreover, the proposed method does not depend on the type of residue present in the image. The study was conducted at the experimental farm “El Encín” in Alcalá de Henares (Madrid, Spain).