964 resultados para texture analysis
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"Contract US AEC AT(11-1)2118."
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Mineralogical analysis is often used to assess the liberation properties of particles. A direct method of estimating liberation is to actually break particles and then directly obtain liberation information from applying mineralogical analysis to each size-class of the product. Another technique is to artificially apply random breakage to the feed particle sections to estimate the resultant distribution of product particle sections. This technique provides a useful alternative estimation method. Because this technique is applied to particle sections, the actual liberation properties for particles can only be estimated by applying stereological correction. A recent stereological technique has been developed that allows the discrepancy between the linear intercept composition distribution and the particle section composition distribution to be used as guide for estimating the particle composition distribution. The paper will show results validating this new technique using numerical simulation. (C) 2004 Elsevier Ltd. All rights reserved.
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The local image representation produced by early stages of visual analysis is uninformative regarding spatially extensive textures and surfaces. We know little about the cortical algorithm used to combine local information over space, and still less about the area over which it can operate. But such operations are vital to support perception of real-world objects and scenes. Here, we deploy a novel reverse-correlation technique to measure the extent of spatial pooling for target regions of different areas placed either in the central visual field, or more peripherally. Stimuli were large arrays of micropatterns, with their contrasts perturbed individually on an interval-by-interval basis. By comparing trial-by-trial observer responses with the predictions of computational models, we show that substantial regions (up to 13 carrier cycles) of a stimulus can be monitored in parallel by summing contrast over area. This summing strategy is very different from the more widely assumed signal selection strategy (a MAX operation), and suggests that neural mechanisms representing extensive visual textures can be recruited by attention. We also demonstrate that template resolution is much less precise in the parafovea than in the fovea, consistent with recent accounts of crowding. © 2014 The Authors.
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We present results of an inorganic geochemical pore water and sediment study conducted on Quaternary sediments from the western Arctic Ocean. The sediment cores were recovered in 2008 from the southern Mendeleev Ridge during RV Polarstern Expedition ARK-XXIII/3. With respect to sediment sources and depositional processes, peaks in Ca/Al, Mg/Al, Sr/Al and Sr/Mg indicate enhanced input of both ice-rafted (mainly dolomite) and biogenic carbonate during deglacial warming phases. Distinct and repetitive brown layers enriched in Mn (oxyhydr)oxides occur mostly in association with these carbonate-rich intervals. For the first time, we show that the brown layers are also consistently enriched in scavenged trace metals Co, Cu, Mo and Ni. The bioturbation patterns of the brown layers, specifically well-defined brown burrows into the underlying sediments, support formation close to the sediment-water interface. The Mn and trace metal enrichments were probably initiated under warmer climate conditions. Both river runoff and melting sea ice delivered trace metals to the Arctic Ocean, but also enhanced seasonal productivity and organic matter export to the sea floor. As Mn (oxyhydr)oxides and scavenged trace metals were deposited at the sea floor, a co-occurring organic matter "pulse" triggered intense diagenetic Mn cycling at the sediment-water interface. These processes resulted in the formation of Mn and trace metal enrichments, but almost complete organic matter degradation. As warmer conditions ceased, reduced riverine runoff and/or a solid sea ice cover terminated the input of riverine trace metal and fresh organic matter, and greyish-yellowish sediments poor in Mn and trace metals were deposited. Oxygen depletion of Arctic bottom waters as potential cause for the lack of Mn enrichments during glacial intervals is highly improbable. While the original composition and texture of the brown layers resulted from specific climatic conditions (including transient Mn redox cycling at the sediment-water interface), pore water data show that early diagenetic Mn redistribution is still affecting the organic-poor sediments in several meters depth. Given persistent steady state diagenetic conditions, purely authigenic Mn-rich brown layers may form, while others may completely vanish. The degree of diagenetic Mn redistribution largely depends on the depositional environment within the Arctic Ocean, the availability of Mn and organic matter, and seems to be recorded by the Co/Mo ratios of single Mn-rich layers. We conclude that brown Arctic sediment layers are not necessarily synchronous features, and correlating them across different parts of the Arctic Ocean without additional age control is not recommended.
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Laminated sediments spanning the last 20,000 years (though not continuously) in the Shaban Deep, a brine-filled basin in the northern Red Sea, were analyzed microscopically and with backscattered electron imagery in order to determine laminae composition with emphasis on the diatomaceous component. Based on this detailed study, we present schematic models to propose paleoflux scenarios for laminae formation at different time-slices. The investigated core (GeoB 5836-2; 26°12.61'N, 35°21.56'E; water depth 1475 m) shows light and dark alternating laminae that are easily distinguishable in the mid-Holocene and at the end of the deglaciation (13-15 ka) period. Light layers are mainly composed of coccoliths, terrigenous material and diatom fragments, while dark layers consist almost exclusively of diatom frustules (monospecific or mixed assemblages). The regularity in the occurrence of coccolith/diatom couplets points to an annual deposition cycle where contrasting seasons and associated plankton blooms are represented (diatoms-fall/winter deposition, coccoliths-summer signal). We propose that, for the past ~15,000 years, the laminations represent two-season annual varves. Strong dissolution of carbonate, with the concomitant loss of the coccolith-rich layer in sediments older than 15 ka, prevents us from presenting a schematic model of annual deposition. However, the diatomaceous component reveals a marked switch in species composition between Last Glacial Maximum (LGM) sediments (dominated by Chaetoceros resting spores) and sediments somewhat younger (18-19 ka; dominated by Rhizosolenia). We propose that different diatom assemblages reflect changing conditions in stratification in the northern Red Sea: Strong stratification conditions, such as during two meltwater pulses at 14.5 and 11.4 ka, are reflected in the sediment by Rhizosolenia layers, while Chaetoceros-dominated assemblages represent deep convection conditions.
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The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.
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In the last decade, research in Computer Vision has developed several algorithms to help botanists and non-experts to classify plants based on images of their leaves. LeafSnap is a mobile application that uses a multiscale curvature model of the leaf margin to classify leaf images into species. It has achieved high levels of accuracy on 184 tree species from Northeast US. We extend the research that led to the development of LeafSnap along two lines. First, LeafSnap’s underlying algorithms are applied to a set of 66 tree species from Costa Rica. Then, texture is used as an additional criterion to measure the level of improvement achieved in the automatic identification of Costa Rica tree species. A 25.6% improvement was achieved for a Costa Rican clean image dataset and 42.5% for a Costa Rican noisy image dataset. In both cases, our results show this increment as statistically significant. Further statistical analysis of visual noise impact, best algorithm combinations per species, and best value of , the minimal cardinality of the set of candidate species that the tested algorithms render as best matches is also presented in this research
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The importance of the gastronomic heritage of any people is unquestionable and Portugal is particularly rich when it comes to sweets. Hence, the objective of this work was to give a contribution colour and texture, due to their importance for consumer acceptance. The samples were bought from a pastry in Viseu and produced according to the traditional recipe. Colour evaluation was made by a colorimeter and textural analysis by a texturometer. The results obtained allowed concluding that there were differences between the top burned area and the non-burned areas, as well as when comparing the ruffled with unruffled samples either regarding colour and also texture. The burned area was darker, with a more intense red and less yellow. As to texture, the ruffles samples were harder than the unruffled samples.
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The objective of this study was to evaluate the chemical, color, textural, and sensorial characteristics of Serra da Estrela cheese and also to identity the factors affecting these properties, namely thistle ecotype, place of production, dairy and maturation. The results demon- strated that the cheeses lost weight mostly during the first stage of maturation, which was negatively correlated with moisture content, being this also observed for fat and protein contents. During maturation the cheeses became darker and with a yellowish coloration. A strong corre- lation was found between ash and chlorides contents, being the last directly related to the added salt in the manufacturing process. The flesh firmness showed a strong positive correlation with the rind harness and the firmness of inner paste. Stickiness was strongly related with all the other textural properties being indicative of the creamy nature of the paste. Adhesiveness was posi- tively correlated with moisture content and negatively correlated with maturation time. The trained panelists liked the cheeses, giving high overall assessment scores, but these were not significantly correlated with the physicochemical properties. The salt differences between cheeses were not evident for the panelists, which was corroborated by the absence of correlation between the perception of saltiness and the analyzed chlorides con- tents. The Factorial Analysis of the chemical and physical properties evidenced that they could be explained by two factors, one associated to the texture and the color and the other associated with the chemical properties. Finally, there was a clear influence of the thistle ecotype, place of production and dairy factors in the analyzed properties.
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Beach sands from the Rosa Marina locality (Adriatic coast, southern Italy) were analysed mainly microscopically in order to trace the source areas of their lithoclastic and bioclastic components. The main cropping out sedimentary units were also studied with the objective to identify the potential source areas of lithoclasts. This allowed to establish how the various rock units contribute to the formation of beach sands. The analysis of the bioclastic components allows to estimate the actual role of organisms regarding the supply of this material to the beach. Identification of taxa that are present in the beach sands as shell fragments or other remains was carried out at the genus or family level. Ecologi- cal investigation of the same beach and the recognition of sub-environments (mainly distinguished on the basis of the nature of the substrate and of the water depth) was the key topic that allowed to establish the actual source areas of bioclasts in the Rosa Marina beach sands. The sedimentological analysis (including a physical study of the beach and the calculation of some statistical parameters concerning the grain-size curves) shows that the Rosa Marina beach is nowadays subject to erosion.
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Phenotypic variation in plants can be evaluated by morphological characterization using visual attributes. Fruits have been the major descriptors for identification of different varieties of fruit crops. However, even in their absence, farmers, breeders and interested stakeholders require to distinguish between different mango varieties. This study aimed at determining diversity in mango germplasm from the Upper Athi River (UAR) and providing useful alternative descriptors for the identification of different mango varieties in the absence of fruits. A total of 20 International Plant Genetic Resources Institute (IPGRI) descriptors for mango were selected for use in the visual assessment of 98 mango accessions from 15 sites of the UAR region of eastern Kenya. Purposive sampling was used to identify farmers growing diverse varieties of mangoes. Evaluation of the descriptors was performed on-site and the data collected were then subjected to multivariate analysis including Principal Component Analysis (PCA) and Cluster analysis, one- way analysis of variance (ANOVA) and Chi square tests. Results classified the accessions into two major groups corresponding to indigenous and exotic varieties. The PCA showed the first six principal components accounting for 75.12% of the total variance. A strong and highly significant correlation was observed between the color of fully grown leaves, leaf blade width, leaf blade length and petiole length and also between the leaf attitude, color of young leaf, stem circumference, tree height, leaf margin, growth habit and fragrance. Useful descriptors for morphological evaluation were 14 out of the selected 20; however, ANOVA and Chi square test revealed that diversity in the accessions was majorly as a result of variations in color of young leaves, leaf attitude, leaf texture, growth habit, leaf blade length, leaf blade width and petiole length traits. These results reveal that mango germplasm in the UAR has significant diversity and that other morphological traits apart from fruits can be useful in morphological characterization of mango.
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Résumé : La texture dispose d’un bon potentiel discriminant qui complète celui des paramètres radiométriques dans le processus de classification d’image. L’indice Compact Texture Unit (CTU) multibande, récemment mis au point par Safia et He (2014), permet d’extraire la texture sur plusieurs bandes à la fois, donc de tirer parti d’un surcroît d’informations ignorées jusqu’ici dans les analyses texturales traditionnelles : l’interdépendance entre les bandes. Toutefois, ce nouvel outil n’a pas encore été testé sur des images multisources, usage qui peut se révéler d’un grand intérêt quand on considère par exemple toute la richesse texturale que le radar peut apporter en supplément à l’optique, par combinaison de données. Cette étude permet donc de compléter la validation initiée par Safia (2014) en appliquant le CTU sur un couple d’images optique-radar. L’analyse texturale de ce jeu de données a permis de générer une image en « texture couleur ». Ces bandes texturales créées sont à nouveau combinées avec les bandes initiales de l’optique, avant d’être intégrées dans un processus de classification de l’occupation du sol sous eCognition. Le même procédé de classification (mais sans CTU) est appliqué respectivement sur : la donnée Optique, puis le Radar, et enfin la combinaison Optique-Radar. Par ailleurs le CTU généré sur l’Optique uniquement (monosource) est comparé à celui dérivant du couple Optique-Radar (multisources). L’analyse du pouvoir séparateur de ces différentes bandes à partir d’histogrammes, ainsi que l’outil matrice de confusion, permet de confronter la performance de ces différents cas de figure et paramètres utilisés. Ces éléments de comparaison présentent le CTU, et notamment le CTU multisources, comme le critère le plus discriminant ; sa présence rajoute de la variabilité dans l’image permettant ainsi une segmentation plus nette, une classification à la fois plus détaillée et plus performante. En effet, la précision passe de 0.5 avec l’image Optique à 0.74 pour l’image CTU, alors que la confusion diminue en passant de 0.30 (dans l’Optique) à 0.02 (dans le CTU).
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Meat industry needs to reduce salt in their products due to health issues. The present study evaluated the effect of salt reduction from 6% to 3% in two Portuguese traditional blood dry-cured sausages. Physicochemical and microbiological parameters, biogenic amines, fatty acids and texture profiles and sensory panel evaluations were considered. Differences due to salt reduction were perceptible in a faint decline of water activity, which slightly favoured microbial growth. Total biogenic amines content ranged from 88.86 to 796.68 mg kg 1 fresh matter, with higher amounts, particularly of cadaverine, histamine and tyramine, in low-salt products. Still, histamine and other vasoactive amines remained at low levels, thus not affecting consumers’ health. Regarding fatty acids, no significant differences were observed due to salt. However, texture profile analysis revealed lower resilience and cohesiveness in low-salt products, although no textural changes were observed by the sensory panel. Nevertheless, low-salt sausages were clearly preferred by panellists.
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The study and preservation of museum collections requires complete knowledge and understanding of constituent materials that can be natural, synthetic, or semi-synthetic polymers. In former times, objects were incorporated in museum collections and classified solely by their appearance. New studies, prompted by severe degradation processes or conservation-restoration actions, help shed light on the materiality of objects that can contradict the original information or assumptions. The selected case study presented here is of a box dating from the beginning of the 20th century that belongs to the Portuguese National Ancient Art Museum. Museum curators classified it as a tortoiseshell box decorated with gold applications solely on the basis of visual inspection and the information provided by the donor. This box has visible signs of degradation with white veils, initially assumed to be the result of biological degradation of a proteinaceous matrix. This paper presents the methodological rationale behind this study and proposes a totally non-invasive methodology for the identification of polymeric materials in museum artifacts. The analysis of surface leachates using 1H and 13C nuclear magnetic resonance (NMR) complemented by in situ attenuated total reflection infrared spectroscopy (ATR FT-IR) allowed for full characterization of the object s substratum. The NMR technique unequivocally identified a great number of additives and ATR FT-IR provided information about the polymer structure and while also confirming the presence of additives. The pressure applied during ATR FT-IR spectroscopy did not cause any physical change in the structure of the material at the level of the surface (e.g., color, texture, brightness, etc.). In this study, variable pressure scanning electron microscopy (VP-SEM-EDS) was also used to obtain the elemental composition of the metallic decorations. Additionally, microbiologic and enzymatic assays were performed in order to identify the possible biofilm composition and understand the role of microorganisms in the biodeterioration process. Using these methodologies, the box was correctly identified as being made of cellulose acetate plastic with brass decorations and the white film was identified as being composed mainly of polymer exudates, namely sulphonamides and triphenyl phosphate.