955 resultados para multispectral image analysis
Resumo:
This work proposes an optimization of a semi-supervised Change Detection methodology based on a combination of Change Indices (CI) derived from an image multitemporal data set. For this purpose, SPOT 5 Panchromatic images with 2.5 m spatial resolution have been used, from which three Change Indices have been calculated. Two of them are usually known indices; however the third one has been derived considering the Kullbak-Leibler divergence. Then, these three indices have been combined forming a multiband image that has been used in as input for a Support Vector Machine (SVM) classifier where four different discriminant functions have been tested in order to differentiate between change and no_change categories. The performance of the suggested procedure has been assessed applying different quality measures, reaching in each case highly satisfactory values. These results have demonstrated that the simultaneous combination of basic change indices with others more sophisticated like the Kullback-Leibler distance, and the application of non-parametric discriminant functions like those employees in the SVM method, allows solving efficiently a change detection problem.
Resumo:
The main problem to study vertical drainage from the moisture distribution, on a vertisol profile, is searching for suitable methods using these procedures. Our aim was to design a digital image processing methodology and its analysis to characterize the moisture content distribution of a vertisol profile. In this research, twelve soil pits were excavated on a ba re Mazic Pellic Vertisols ix of them in May 13/2011 and the rest in May 19 /2011 after a moderate rainfall event. Digital RGB images were taken from each vertisol pit using a Kodak? camera selecting a size of 1600x945 pixels. Each soil image was processed to homogenized brightness and then a spatial filter with several window sizes was applied to select the optimum one. The RGB image obtained were divided in each matrix color selecting the best thresholds for each one, maximum and minimum, to be applied and get a digital binary pattern. This one was analyzed by estimating two fractal scaling exponents box counting dimension D BC) and interface fractal dimension (D) In addition, three pre-fractal scaling coefficients were determinate at maximum resolution: total number of boxes intercepting the foreground pattern (A), fractal lacunarity (?1) and Shannon entropy S1). For all the images processed the spatial filter 9x9 was the optimum based on entropy, cluster and histogram criteria. Thresholds for each color were selected based on bimodal histograms.
Resumo:
El estudio de la estructura del suelo es de vital importancia en diferentes campos de la ciencia y la tecnología. La estructura del suelo controla procesos físicos y biológicos importantes en los sistemas suelo-planta-microorganismos. Estos procesos están dominados por la geometría de la estructura del suelo, y una caracterización cuantitativa de la heterogeneidad de la geometría del espacio poroso es beneficiosa para la predicción de propiedades físicas del suelo. La tecnología de la tomografía computerizada de rayos-X (CT) nos permite obtener imágenes digitales tridimensionales del interior de una muestra de suelo, proporcionando información de la geometría de los poros del suelo y permitiendo el estudio de los poros sin destruir las muestras. Las técnicas de la geometría fractal y de la morfología matemática se han propuesto como una poderosa herramienta para analizar y cuantificar características geométricas. Las dimensiones fractales del espacio poroso, de la interfaz poro-sólido y de la distribución de tamaños de poros son indicadores de la complejidad de la estructura del suelo. Los funcionales de Minkowski y las funciones morfológicas proporcionan medios para medir características geométricas fundamentales de los objetos geométricos tridimensionales. Esto es, volumen, superficie, curvatura media de la superficie y conectividad. Las características del suelo como la distribución de tamaños de poros, el volumen del espacio poroso o la superficie poro-solido pueden ser alteradas por diferentes practicas de manejo de suelo. En este trabajo analizamos imágenes tomográficas de muestras de suelo de dos zonas cercanas con practicas de manejo diferentes. Obtenemos un conjunto de medidas geométricas, para evaluar y cuantificar posibles diferencias que el laboreo pueda haber causado en el suelo. ABSTRACT The study of soil structure is of vital importance in different fields of science and technology. Soil structure controls important physical and biological processes in soil-plant-microbial systems. Those processes are dominated by the geometry of soil pore structure, and a quantitative characterization of the spatial heterogeneity of the pore space geometry is beneficial for prediction of soil physical properties. The technology of X-ray computed tomography (CT) allows us to obtain three-dimensional digital images of the inside of a soil sample providing information on soil pore geometry and enabling the study of the pores without disturbing the samples. Fractal geometry and mathematical morphological techniques have been proposed as powerful tools to analyze and quantify geometrical features. Fractal dimensions of pore space, pore-solid interface and pore size distribution are indicators of soil structure complexity. Minkowski functionals and morphological functions provide means to measure fundamental geometrical features of three-dimensional geometrical objects, that is, volume, boundary surface, mean boundary surface curvature, and connectivity. Soil features such as pore-size distribution, pore space volume or pore-solid surface can be altered by different soil management practices. In this work we analyze CT images of soil samples from two nearby areas with contrasting management practices. We performed a set of geometrical measures, some of them from mathematical morphology, to assess and quantify any possible difference that tillage may have caused on the soil.
Resumo:
In this paper we discuss some main image processing techniques in order to propose a classification based upon the output these methods provide. Because despite a particular image analysis technique can be supervised or unsupervised, and can allow or not the existence of fuzzy information at some stage, each technique has been usually designed to focus on a specific objective, and their outputs are in fact different according to each objective. Thus, they are in fact different methods. But due to the essential relationship between them they are quite often confused. In particular, this paper pursues a clarification of the differences between image segmentation and edge detection, among other image processing techniques.
Resumo:
Drill cores are essential for the study of deep-sea sediments and on-land sites because often no suitable outcrop is available or accessible. These cores form the backbone of stratigraphical studies using and combining various dating techniques. Cyclostratigraphy is usually based on fast and inexpensive measurements of physical sediment properties. One indirect but highly valuable proxy for reconstructing the sediment composition and variability is sediment color. However, cracks and other disturbances in sediment cores may dramatically influence the quality of color data retrieved either directly from photospectrometry or derived from core image analysis. Here we present simple but powerful algorithms to extract color data from core images, and focus on routines to exclude cracks from these images. Results are discussed using the example of an ODP core from the Ceara Rise in the Central Atlantic. The crack correction approach presented highly improves the quality of color data and allows the easy incorporation of cracked cores into studies based on core images. This facilitates the quick and inexpensive generation of large color datasets directly from quantified core images, for cyclostratigraphy and other purposes.
Resumo:
"Report no. FHWA-IL-UI-278"--Technical report documentation page.
Resumo:
"September 1991."
Resumo:
The density of axons in the optic nerve, olfactory tract and corpus callosum was quantified in non-demented elderly subjects and in Alzheimer’s disease (AD) using an image analysis system. In each fibre tract, there was significant reduction in the density of axons in AD compared with non-demented subjects, the greatest reductions being observed in the olfactory tract and corpus callosum. Axonal loss in the optic nerve and olfactory tract was mainly of axons with smaller myelinated cross-sectional areas. In the corpus callosum, a reduction in the number of ‘thin’ and ‘thick’ fibres was observed in AD, but there was a proportionally greater loss of the ‘thick’ fibres. The data suggest significant degeneration of white matter fibre tracts in AD involving the smaller axons in the two sensory nerves and both large and small axons in the corpus callosum. Loss of axons in AD could reflect an associated white matter disorder and/or be secondary to neuronal degeneration.
Resumo:
The aim of this project was to carry out a fundamental study to assess the potential of colour image analysis for use in investigations of fire damaged concrete. This involved:(a) Quantification (rather than purely visual assessment) of colour change as an indicator of the thermal history of concrete.(b) Quantification of the nature and intensity of crack development as an indication of the thermal history of concrete, supporting and in addition to, colour change observations.(c) Further understanding of changes in the physical and chemical properties of aggregate and mortar matrix after heating.(d) An indication of the relationship between cracking and non-destructive methods of testing e.g. UPV or Schmidt hammer. Results showed that colour image analysis could be used to quantify the colour changes found when concrete is heated. Development of red colour coincided with significant reduction in compressive strength. Such measurements may be used to determine the thermal history of concrete by providing information regarding the temperature distribution that existed at the height of a fire. The actual colours observed depended on the types of cement and aggregate that were used to make the concrete. With some aggregates it may be more appropriate to only analyse the mortar matrix. Petrographic techniques may also be used to determine the nature and density of cracks developing at elevated temperatures and values of crack density correlate well with measurements of residual compressive strength. Small differences in crack density were observed with different cements and aggregates, although good correlations were always found with the residual compressive strength. Taken together these two techniques can provide further useful information for the evaluation of fire damaged concrete. This is especially so since petrographic analysis can also provide information on the quality of the original concrete such as cement content and water / cement ratio. Concretes made with blended cements tended to produce small differences in physical and chemical properties compared to those made with unblended cements. There is some evidence to suggest that a coarsening of pore structure in blended cements may lead to onset of cracking at lower temperatures. The use of DTA/TGA was of little use in assessing the thermal history of concrete made with blended cements. Corner spalling and sloughing off, as observed in columns, was effectively reproduced in tests on small scale specimens and the crack distributions measured. Relationships between compressive strength/cracking and non-destructive methods of testing are discussed and an outline procedure for site investigations of fire damaged concrete is described.
Resumo:
This study considers the application of image analysis in petrography and investigates the possibilities for advancing existing techniques by introducing feature extraction and analysis capabilities of a higher level than those currently employed. The aim is to construct relevant, useful descriptions of crystal form and inter-crystal relations in polycrystalline igneous rock sections. Such descriptions cannot be derived until the `ownership' of boundaries between adjacent crystals has been established: this is the fundamental problem of crystal boundary assignment. An analysis of this problem establishes key image features which reveal boundary ownership; a set of explicit analysis rules is presented. A petrographic image analysis scheme based on these principles is outlined and the implementation of key components of the scheme considered. An algorithm for the extraction and symbolic representation of image structural information is developed. A new multiscale analysis algorithm which produces a hierarchical description of the linear and near-linear structure on a contour is presented in detail. Novel techniques for symmetry analysis are developed. The analyses considered contribute both to the solution of the boundary assignment problem and to the construction of geologically useful descriptions of crystal form. The analysis scheme which is developed employs grouping principles such as collinearity, parallelism, symmetry and continuity, so providing a link between this study and more general work in perceptual grouping and intermediate level computer vision. Consequently, the techniques developed in this study may be expected to find wider application beyond the petrographic domain.