Integrating JERS-1 imaging radar and elevation models for mapping tropical rainforest communities in far North Queensland, Australia

The Wet Tropics World Heritage Area in Far North Queens- land, Australia consists predominantly of tropical rainforest and wet sclerophyll forest in areas of variable relief. Previous maps of vegetation communities in the area were produced by a labor-intensive combination of field survey and air-photo interpretation. Thus,. the aim of this work was to develop a new vegetation mapping method based on imaging radar that incorporates topographical corrections, which could be repeated frequently, and which would reduce the need for detailed field assessments and associated costs. The method employed G topographic correction and mapping procedure that was developed to enable vegetation structural classes to be mapped from satellite imaging radar. Eight JERS-1 scenes covering the Wet Tropics area for 1996 were acquired from NASDA under the auspices of the Global Rainforest Mapping Project. JERS scenes were geometrically corrected for topographic distortion using an 80 m DEM and a combination of polynomial warping and radar viewing geometry modeling. An image mosaic was created to cover the Wet Tropics region, and a new technique for image smoothing was applied to the JERS texture bonds and DEM before a Maximum Likelihood classification was applied to identify major land-cover and vegetation communities. Despite these efforts, dominant vegetation community classes could only be classified to low levels of accuracy (57.5 percent) which were partly explained by the significantly larger pixel size of the DEM in comparison to the JERS image (12.5 m). In addition, the spatial and floristic detail contained in the classes of the original validation maps were much finer than the JERS classification product was able to distinguish. In comparison to field and aerial photo-based approaches for mapping the vegetation of the Wet Tropics, appropriately corrected SAR data provides a more regional scale, all-weather mapping technique for broader vegetation classes. Further work is required to establish an appropriate combination of imaging radar with elevation data and other environmental surrogates to accurately map vegetation communities across the entire Wet Tropics.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Fractal descriptors based on Fourier spectrum applied to texture analysis

This work proposes the development and study of a novel technique lot the generation of fractal descriptors used in texture analysis. The novel descriptors are obtained from a multiscale transform applied to the Fourier technique of fractal dimension calculus. The power spectrum of the Fourier transform of the image is plotted against the frequency in a log-log scale and a multiscale transform is applied to this curve. The obtained values are taken as the fractal descriptors of the image. The validation of the proposal is performed by the use of the descriptors for the classification of a dataset of texture images whose real classes are previously known. The classification precision is compared to other fractal descriptors known in the literature. The results confirm the efficiency of the proposed method. (C) 2012 Elsevier B.V. All rights reserved.

A comparative study on multiscale fractal dimension descriptors

Fractal theory presents a large number of applications to image and signal analysis. Although the fractal dimension can be used as an image object descriptor, a multiscale approach, such as multiscale fractal dimension (MFD), increases the amount of information extracted from an object. MFD provides a curve which describes object complexity along the scale. However, this curve presents much redundant information, which could be discarded without loss in performance. Thus, it is necessary the use of a descriptor technique to analyze this curve and also to reduce the dimensionality of these data by selecting its meaningful descriptors. This paper shows a comparative study among different techniques for MFD descriptors generation. It compares the use of well-known and state-of-the-art descriptors, such as Fourier, Wavelet, Polynomial Approximation (PA), Functional Data Analysis (FDA), Principal Component Analysis (PCA), Symbolic Aggregate Approximation (SAX), kernel PCA, Independent Component Analysis (ICA), geometrical and statistical features. The descriptors are evaluated in a classification experiment using Linear Discriminant Analysis over the descriptors computed from MFD curves from two data sets: generic shapes and rotated fish contours. Results indicate that PCA, FDA, PA and Wavelet Approximation provide the best MFD descriptors for recognition and classification tasks. (C) 2012 Elsevier B.V. All rights reserved.

Multidimensional, multislaces, and multiscale MRI for quality evaluation in food.

InsideFood explicitly aims at measuring food microstructure, the spatial distribution of food components within foods, with state of the art tomographic, spectroscopic and texture measurement techniques including X-ray micro-and nano CT, MRI,OCT, NMR, TRS and SRS, and acoustic emission. Nutritional quality (sugar and gluten free cereal products), sensory quality (texture of all foods) and safety (foreign material detection in cereal products) are considered. Online and inline techniques including NMR, MRI, TRS, SRS and X-ray imaging to visualise and monitor structure will be developed.

Combining Leaf Shape and Texture for Costa Rican Plant Species Identification

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

Laser Printer Attribution: Exploring New Features And Beyond.

With a huge amount of printed documents nowadays, identifying their source is useful for criminal investigations and also to authenticate digital copies of a document. In this paper, we propose novel techniques for laser printer attribution. Our solutions do not need very high resolution scanning of the investigated document and explore the multidirectional, multiscale and low-level gradient texture patterns yielded by printing devices. The main contributions of this work are: (1) the description of printed areas using multidirectional and multiscale co-occurring texture patterns; (2) description of texture on low-level gradient areas by a convolution texture gradient filter that emphasizes textures in specific transition areas and (3) the analysis of printer patterns in segments of interest, which we call frames, instead of whole documents or only printed letters. We show by experiments in a well documented dataset that the proposed methods outperform techniques described in the literature and present near-perfect classification accuracy being very promising for deployment in real-world forensic investigations.

Effect of glutamate and inosinate on sensory and instrumental texture of extruded products

Expanded products have been developed by extrusion of non-conventional highly nutritious raw materials such as amaranth and chickpea blended with bovine lung. As sensory acceptance of these snacks is restricted, this study aimed at improving their texture, through the addition of monosodium glutamate (MSG) and disodium inosinate (IMP) flavor enhancers to the feeding material, or to the flavor added after the extrusion. Sensory and mechanical analyses showed that both enhancers affected texture, assessed by sensory and instrumental methods. Addition of IMP together with MSG to the chickpea-based snacks presented the best results. This beneficial effect was not observed in the amaranth-based snack, suggesting that IMP and MSG can favorably impact texture of extruded products depending on the amount and type of protein present

Evolution of magnetic properties and crystallographic texture in electrical steel with large plastic deformation

Deformation leads to a hardening of steel due to an increase in the density of dislocations and a reduction in their mobility, giving rise to a state of elevated residual stresses in the crystal lattice. In the microstructure, one observes an increase in the contribution of crystalline orientations which are unfavorable to the magnetization, as seen, for example, by a decrease in B(50), the magnetic flux density at a field of 50 A/cm. The present study was carried out with longitudinal strips of fully processed non-oriented (NO) electrical steel, with deformations up to 70% resulting from cold rolling in the longitudinal direction. With increasing plastic deformation, the value of B(50) gradually decreases until it reaches a minimum value, where it remains even for larger deformations. On the other hand, the coercive field H(c) continually increases. Magnetometry results and electron backscatter diffraction results are compared and discussed. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3560895]

Composition and orientation effects on the final recrystallization texture of coarse-grained Nb-containing AISI 430 ferritic stainless steels

Composition and orientation effects on the final recrystallization texture of three coarse-grained Nb-containing AISI 430 ferritic stainless steels (FSSs) were investigated. Hot-bands of steels containing distinct amounts of niobium, carbon and nitrogen were annealed at 1250 degrees C for 2h to promote grain growth. In particular, the amounts of Nb in solid solution vary from one grade to another. For purposes of comparison, the texture evolution of a hot-band sheet annealed at 1030 degrees C for 1 min (finer grain structure) was also investigated. Subsequently, the four sheets were cold rolled up to 80% reduction and then annealed at 800 degrees C for 15 min. Texture was determined using X-ray diffraction and electron backscatter diffraction (EBSD). Noticeable differences regarding the final recrystallization texture and microstructure were observed in the four investigated grades. Results suggest that distinct nucleation mechanisms take place within these large grains leading to the development of different final recrystallization textures. (c) 2011 Elsevier B.V. All rights reserved.

Impact of transition oxides on growth stresses and texture of alumina scales formed during oxidation of iron aluminides

The internal stresses and crystallographic texture in alpha-Al(2)O(3) scales grown on iron aluminides at 1100 degrees C were determined in situ using synchrotron X-ray diffraction. In the first hour of oxidation, alpha-Al(2)O(3) was formed by direct nucleation and by conversion from transition oxides (either theta-Al(2)O(3) or a mixed Fe-Al oxide). A sharp texture develops connected with the direct nucleation of alpha-Al(2)O(3), in contrast to the weaker texture observed in alpha-Al(2)O(3) originated by previous transformations, which also yielded tensile stresses in early oxidation stages. (C) 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Microstructure and texture of duplex stainless steel after melt-spinning processing

The microstructure and texture of melt-spun UNS S31803 (DIN W. Nr. 1. 4462) duplex stainless steel were analyzed after casting and solution treatment. The cast ribbons contained austenite (gamma) and ferrite (alpha or delta) with roughly equal compositions. The alpha and gamma had < 100 > and < 110 > partial fiber textures, respectively. After solution treatment, the texture was maintained, the amount of gamma phase increased, and the alloying elements were partitioned as expected, according to whether they were ferrite or austenite stabilizers. (c) 2006 Elsevier Inc. All rights reserved.

Microstructure and texture assessment of Al-Mn-Fe-Si (3003) aluminum alloy produced by continuous and semicontinuous casting processes

Aluminum sheets are currently produced by the direct-chill process (DC). The need for low-cost aluminum sheets is a challenge for the development of new materials produced by the twin roll caster (TRC) process. It is expected that sheets produced from these different casting procedures will differ in their microstructure. These differences in microstructure and in the crystallographic texture have great impact on sheet mechanical properties and formability. The present study investigated microstructure and evaluated texture of two strips of Al-Mn-Fe-Si (3003) aluminum alloy produced by TRC and by hot-rolling processes. It was possible to notice that the microstructure, morphology, and grain size of the TRC sample were more homogenous than those found in hot-rolled samples. Both strips, obtained by the two processes, showed strong texture gradient across the thickness.

Texture and mechanical properties evolution of a deep drawing medium carbon steel during cold rolling and subsequent recrystallization

Medium carbon steels are mostly used for simple applications; however, new applications have been developed for which good sheet metal formability is required. These types of steels have an inherent low formability. A medium-carbon hot-rolled SAE 1050 steel was selected for this study. It has been cold rolled with thickness reductions varying between 7 and 80%. The samples obtained were used to evaluate the strain hardening curve. For samples with a 50 and 80% thickness reduction, an annealing heat treatment was performed to achieve recrystallization. The material was characterized in the ""as-received"", cold rolled and annealed conditions using several methods: optical metallography, X-ray diffraction (texture), Vickers hardness, and tensile testing. For large thickness reductions, the SAE 1050 steel presented low elongation, less than 2%, and yield strength (YS) and tensile strength (TS) around 1400 MPa. Texture in the ""as-received"" condition showed strong components on the {001} plane, in the < 100 >, < 210 > and (110) directions. After cold rolling, the texture did not present any significant changes for small thickness reductions, however. It changed completely for large ones, where gamma, < 111 >//ND, alpha, < 110 > HRD, and gamma prime, < 223 >//ND, fibres were strengthened. After annealing, the microstructure of the SAE 1050 steel was characterized by recrystallized ferrite and globular cementite. There was little change in the alpha fibre for the 50% reduction, whereas for the 80% reduction, its intensity increased. Both gamma and gamma prime fibres vanished upon annealing for 50 and 80% reductions alike. (c) 2008 Elsevier B.V. All rights reserved.

Medium carbon steel deep drawing: A study on the evolution of mechanical properties, texture and simulations, from cold rolling to the end product

Medium carbon steels are mostly used for simple applications; nevertheless new applications have been developed for which good sheet formability is required. This class of steels has an inherent low formability. A medium carbon hot rolled SAE 1050 steel has been selected for this study. It has been cold rolled with reductions in the 7-80% range. Samples have been used to assess the cold work hardening curve. For samples with a 50 and 80% thickness reduction, an annealing heat treatment has been performed to obtain recrystallization. The material has been characterized in the ""as received"", cold rolled and annealed conditions, using several methods: optical microscopy, X-ray diffraction (texture), Vickers hardness and tensile testing. The 50% cold rolled and recrystallized material has been further studied in terms of sheet metal formability and texture evolution during the actual stamping of a steel toecap that has been used to validate the finite element simulations. (C) 2008 Elsevier B.V. All rights reserved.