964 resultados para Binary Image Representation
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Multispectral images are becoming more common in the field of remote sensing, computer vision, and industrial applications. Due to the high accuracy of the multispectral information, it can be used as an important quality factor in the inspection of industrial products. Recently, the development on multispectral imaging systems and the computational analysis on the multispectral images have been the focus of a growing interest. In this thesis, three areas of multispectral image analysis are considered. First, a method for analyzing multispectral textured images was developed. The method is based on a spectral cooccurrence matrix, which contains information of the joint distribution of spectral classes in a spectral domain. Next, a procedure for estimating the illumination spectrum of the color images was developed. Proposed method can be used, for example, in color constancy, color correction, and in the content based search from color image databases. Finally, color filters for the optical pattern recognition were designed, and a prototype of a spectral vision system was constructed. The spectral vision system can be used to acquire a low dimensional component image set for the two dimensional spectral image reconstruction. The data obtained by the spectral vision system is small and therefore convenient for storing and transmitting a spectral image.
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Describes a method to code a decimated model of an isosurface on an octree representation while maintaining volume data if it is needed. The proposed technique is based on grouping the marching cubes (MC) patterns into five configurations according the topology and the number of planes of the surface that are contained in a cell. Moreover, the discrete number of planes on which the surface lays is fixed. Starting from a complete volume octree, with the isosurface codified at terminal nodes according to the new configuration, a bottom-up strategy is taken for merging cells. Such a strategy allows one to implicitly represent co-planar faces in the upper octree levels without introducing any error. At the end of this merging process, when it is required, a reconstruction strategy is applied to generate the surface contained in the octree intersected leaves. Some examples with medical data demonstrate that a reduction of up to 50% in the number of polygons can be achieved
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Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping
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Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.
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The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.
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A stability-indicating RP-HPLC method is presented for determination of gatifloxacin and flurbiprofen in binary combination. Gatifloxacin, flurbiprofen and their degradation products were detected at 254 nm using a BDS Hypersil C8 (250 X 4.6 mm, 5 µm) column and mixture of 20 mM phosphate buffer (pH 3.0) and methanol 30:70 v/v as mobile phase. Response was linear over the range of 15-105 mg mL-1 for gatifloxacin (r² > 0.998) and of 1.5-10.5 mg mL-1 for flurbiprofen (r² > 0.999). The developed method efficiently separated the analytical peaks from degradation products (peak purity index > 0.9999). The method developed can be applied successfully for determination of gatifloxacin and flurbiprofen in human serum, urine, pharmaceutical formulations, and their stability studies.
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Kirjallisuusarvostelu
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The main objective for this study was to explore certain organization’s product line rebranding process and its impact on product line’s perceived image. The case company is a global paper, packaging and forest products company, business segment paper board. The audience explored is one of the company’s major customers, merchant in Germany. The research was performed as a descriptive case study with a purpose to provide longitudinal insight into the product line image and its eventual alteration as a result of the case company’s rebranding process. Mainly qualitative methods were used for conducting the research. The data for the empirical part was collected with a web-based survey at two different points of time; before the rebranded products entered the market and after they had been available approximately six months. The results of this study reveal that the case company has performed well in its attempt to improve product line’s brand image through rebranding. It was found that between the two brand image measurements the product brand image seems to have improved in all of the areas which according to theoretical framework of this study contribute to formation of brand image; brand associations, marketing communications and interpersonal relationships, not forgetting the original platform that initiated the change; technical quality modifications. In other words it may be concluded that as technical quality was brought to a new level, also assessments about the brand image improved respectively.
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Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.
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Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.
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De förändrade ansatserna inom feministisk utvecklingsekonomi för med sig nya sätt att tala om kvinnor, män och utveckling. Genom att analysera texter skrivna inom området feministisk ekonomi från 1960-talet fram till början av 2000-talet dokumenterar den föreliggande studien på vilket sätt språket hos textproducenter inom utvecklingsekonomi konstituerar och är beroende av dessa skribenters inställning till utvecklingsfrågor och till kvinnor och män. Analysen fokuserar på hur aktiverings- och passiveringsprocesser används i representationen av de två huvuddeltagarna, kvinnor och män, hur begreppet genus introduceras och hur utvecklingsfrågor förändras genom ansatser, över tid och mellan genrer. Den teoretiska ramen sträcker sig över olika discipliner: systemisk funktionell grammatik och kritisk diskursanalys, men även organisatorisk diskursanalys och utvecklingsstudier. Texterna som valts för analysen härstammar från tre olika källor: planer från världskvinnokonferenserna organiserade av Förenta Nationerna, resolutioner om kvinnor och utveckling antagna av Förenta Nationernas generalförsamling samt handlingsplaner för kvinnor och utveckling författade av Förenta Nationernas livsmedels- och jordbruksorganisation FAO. Den lingvistiska analysmetoden bygger på det system av roller och sätt att representera deltagare som utvecklats av Halliday och Van Leeuwen. För varje årtionde och varje genre granskar studien förändringarna i processtyper och deltagarroller, samt förändringen av fokus på kvinnorelaterade frågor och konceptualiseringen av genus. Den kvantitativa analysen kompletteras och förstärks av en detaljerad analys av textfragment från olika tidpunkter och ansatser. Studiens resultat är av grammatisk och lexikal natur och de är relaterade till genus, genre och tid. Studien visar att aktiveringsprocesserna är betydligt talrikare än passiveringsprocesserna i representationen av kvinnor. En bättre förståelse av deltagarrepresentation uppnås dock via en omgruppering av de grammatiska processerna i identifierande, aktiverande och riktade processer. Skiftet från fokus på kvinnor till fokus på genus är inte så mycket en förändring av processerna som representerar deltagarna, utan mer en förändring av retoriken i ansatserna och deras fokus: från integration av kvinnor till kvinnors empowerment, från kvinnors situation till genusrelationer, från brådskande tillägg till social konflikt och samarbete.
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1897/10 (N11).
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1897/02 (N3).