237 resultados para Infrared spectral
Resumo:
The near-infrared (NIR) and infrared (IR) spectroscopy has been applied for characterisation of three complex Cu-Zn sulphate/phosphate minerals, namely ktenasite, orthoserpierite and kipushite. The spectral signatures of the three minerals are quite distinct in relation to their composition and structure. The effect of structural cations substitution (Zn2+ and Cu2+) on band shifts is significant both in the electronic and vibrational spectra of these Cu-Zn minerals. The variable Cu:Zn ratio between Zn-rich and Cu-rich compositions shows a strong effect on Cu(II) bands in the electronic spectra. The Cu(II) spectrum is most significant in kipushite (Cu-rich) with bands displayed at high wavenumbers at11390 and 7545 cm-1. The isomorphic substitution of Cu2+ for Zn2+ is reflected in the NIR and IR spectroscopic signatures. The multiple bands for 3 and 4 (SO4)2- stretching vibrations in ktenasite and orthoserpierite are attributed to the reduction of symmetry to the sulphate ion from Td to C2V. The IR spectrum of kipushite is characterised by strong (PO4)3- vibrational modes at 1090 and 990 cm-1. The range of IR absorption is higher in Ktenasite than in kipushite while it is intermediate in orthoserpierite.
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Robust image hashing seeks to transform a given input image into a shorter hashed version using a key-dependent non-invertible transform. These image hashes can be used for watermarking, image integrity authentication or image indexing for fast retrieval. This paper introduces a new method of generating image hashes based on extracting Higher Order Spectral features from the Radon projection of an input image. The feature extraction process is non-invertible, non-linear and different hashes can be produced from the same image through the use of random permutations of the input. We show that the transform is robust to typical image transformations such as JPEG compression, noise, scaling, rotation, smoothing and cropping. We evaluate our system using a verification-style framework based on calculating false match, false non-match likelihoods using the publicly available Uncompressed Colour Image database (UCID) of 1320 images. We also compare our results to Swaminathan’s Fourier-Mellin based hashing method with at least 1% EER improvement under noise, scaling and sharpening.
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This thesis investigates aspects of encoding the speech spectrum at low bit rates, with extensions to the effect of such coding on automatic speaker identification. Vector quantization (VQ) is a technique for jointly quantizing a block of samples at once, in order to reduce the bit rate of a coding system. The major drawback in using VQ is the complexity of the encoder. Recent research has indicated the potential applicability of the VQ method to speech when product code vector quantization (PCVQ) techniques are utilized. The focus of this research is the efficient representation, calculation and utilization of the speech model as stored in the PCVQ codebook. In this thesis, several VQ approaches are evaluated, and the efficacy of two training algorithms is compared experimentally. It is then shown that these productcode vector quantization algorithms may be augmented with lossless compression algorithms, thus yielding an improved overall compression rate. An approach using a statistical model for the vector codebook indices for subsequent lossless compression is introduced. This coupling of lossy compression and lossless compression enables further compression gain. It is demonstrated that this approach is able to reduce the bit rate requirement from the current 24 bits per 20 millisecond frame to below 20, using a standard spectral distortion metric for comparison. Several fast-search VQ methods for use in speech spectrum coding have been evaluated. The usefulness of fast-search algorithms is highly dependent upon the source characteristics and, although previous research has been undertaken for coding of images using VQ codebooks trained with the source samples directly, the product-code structured codebooks for speech spectrum quantization place new constraints on the search methodology. The second major focus of the research is an investigation of the effect of lowrate spectral compression methods on the task of automatic speaker identification. The motivation for this aspect of the research arose from a need to simultaneously preserve the speech quality and intelligibility and to provide for machine-based automatic speaker recognition using the compressed speech. This is important because there are several emerging applications of speaker identification where compressed speech is involved. Examples include mobile communications where the speech has been highly compressed, or where a database of speech material has been assembled and stored in compressed form. Although these two application areas have the same objective - that of maximizing the identification rate - the starting points are quite different. On the one hand, the speech material used for training the identification algorithm may or may not be available in compressed form. On the other hand, the new test material on which identification is to be based may only be available in compressed form. Using the spectral parameters which have been stored in compressed form, two main classes of speaker identification algorithm are examined. Some studies have been conducted in the past on bandwidth-limited speaker identification, but the use of short-term spectral compression deserves separate investigation. Combining the major aspects of the research, some important design guidelines for the construction of an identification model when based on the use of compressed speech are put forward.
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Fourier transfonn (FT) Raman, Raman microspectroscopy and Fourier transform infrared (FTIR) spectroscopy have been used for the structural analysis and characterisation of untreated and chemically treated wool fibres. For FT -Raman spectroscopy novel methods of sample presentation have been developed and optimised for the analysis of wool. No significant fluorescence was observed and the spectra could be obtained routinely. The stability of wool keratin to the laser source was investigated and the visual and spectroscopic signs of sample damage were established. Wool keratin was found to be extremely robust with no signs of sample degradation observed for laser powers of up to 600 m W and for exposure times of up to seven and half hours. Due to improvements in band resolution and signal-to-noise ratio, several previously unobserved spectral features have become apparent. The assignment of the Raman active vibrational modes of wool have been reviewed and updated to include these features. The infrared spectroscopic techniques of attenuated total reflectance (ATR) and photoacoustic (P A) have been used to examine shrinkproofed and mothproofed wool samples. Shrinkproofing is an oxidative chemical treatment used to selectively modifY the surface of a wool fibre. Mothproofing is a chemical treatment applied to wool for the prevention of insect attack. The ability of PAS and A TR to vary the penetration depth by varying certain instrumental parameters was used to obtain spectra of the near surface regions of these chemically treated samples. These spectra were compared with those taken with a greater penetration depth, which therefore represent more of the bulk wool sample. The PA and ATR spectra demonstrated that oxidation was restricted to the near-surface layer of wool. Extensive curve fitting of ATR spectra of untreated wool indicated that cuticle was composed of a mixed protein conformation, but was predominately that of an a.-helix. The cortex was proposed to be a mixture of both a.helical and ~-pleated sheet protein conformations. These findings were supported by PAS depth profiling results. Raman microspectroscopy was used in an extensive investigation of the molecular structure of the wool fibre. This included determining the orientation of certain functional groups within the wool fibre and the symmetry of particular vibrations. The orientation ofbonds within the wool fibre was investigated by orientating the wool fibre axis parallel and then perpendicular to the plane of polarisation of the electric vector of the incident radiation. It was experimentally determined that the majority of C=O and N-H bonds of the peptide bond of wool lie parallel to the fibre axis. Additionally, a number of the important vibrations associated with the a-helix were also found to lie parallel to the fibre axis. Further investigation into the molecular structure of wool involved determining what effect stretching the wool fibre had on bond orientation. Raman spectra of stretched and unstretched wool fibres indicated that extension altered the orientation ofthe aromatic rings, the CH2 and CH3 groups of the amino acids. Curve fitting results revealed that extension resulted in significant destruction of the a-helix structure a substantial increase in the P-pleated sheet structure. Finally, depolarisation ratios were calculated for Raman spectra. The vibrations associated with the aromatic rings of amino acids had very low ratios which indicated that the vibrations were highly symmetrical.
Resumo:
Mid-infrared (MIR) and near-infrared (NIR) spectroscopy have been compared and evaluated for differentiating kaolinite, coal bearing kaolinite and halloysite. Kaolinite, coal bearing kaolinite and halloysite are the three relative abundant mineral of the kaolin group, especially in China. In the MIR spectra, the differences are shown in the 3000-3600 cm-1 between kaolinite and halloysite. It can not be obviously differentiated the kaolinite and halloysite, let alone kaolinite and coal bearing kaolinite. However, NIR, together with MIR, give us the sufficient evidence to differentiate the kaolinite and halloysite, especially kaolinite and coal bearing kaolinite. There are obvious differences between kaolinite and halloysite in the all range of their spectra, and it also show some difference between kaolinite and coal bearing kaolinite. Therefore, the reproducibility of measurement, signal to noise ratio and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for mineral analysis.
Resumo:
The structure and thermal stability between typical China kaolinite and halloysite were analysed by X-ray diffraction (XRD), infrared spectroscopy, infrared emission spectroscopy (IES) and Raman spectroscopy. Infrared emission spectroscopy over the temperature range of 300 to 700 °C has been used to characterise the thermal decomposition of both kaolinite and halloysite. Halloysite is characterised by two bands in the water bending region at 1629 and 1648 cm-1, attributed to structure water and coordinated water in the interlayer. Well defined hydroxyl stretching bands at around 3695, 3679, 3652 and 3625 cm-1 are observed for both kaolinite and halloysite. In the 550 °C infrared emission spectrum of halloysite is similar to that of kaolinite in 650-1350 cm-1 region. The infrared emission spectra of halloysite were found to be considerably different to that of kaolinite at lower temperatures. This difference is attributed to the fundamental difference in the structure of the two minerals.
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The thermal decomposition of halloysite-potassium acetate intercalation compound was investigated by thermogravimetric analysis and infrared emission spectroscopy. The X-ray diffraction patterns indicated that intercalation of potassium acetate into halloysite caused an increase of the basal spacing from 1.00 to 1.41 nm. The thermogravimetry results show that the mass losses of intercalation the compound occur in main three main steps, which correspond to (a) the loss of adsorbed water (b) the loss of coordination water and (c) the loss of potassium acetate and dehydroxylation. The temperature of dehydroxylation and dehydration of halloysite is decreased about 100 °C. The infrared emission spectra clearly show the decomposition and dehydroxylation of the halloysite intercalation compound when the temperature is raised. The dehydration of the intercalation compound is followed by the loss of intensity of the stretching vibration bands at region 3600-3200 cm-1. Dehydroxylation is followed by the decrease in intensity in the bands between 3695 and 3620 cm-1. Dehydration was completed by 300 °C and partial dehydroxylation by 350 °C. The inner hydroxyl group remained until around 500 °C.
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The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.
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Cubic indium hydroxide nanomaterials were obtained by a low temperature soft-chemical method without any surfactants. The transition of nano-cubic indium hydroxide to cubic indium oxide during dehydroxylation has been studied by infrared emission spectroscopy. The spectra are related to the structure of the materials and the changes in the structure upon thermal treatment. The infrared absorption spectrum of In(OH)3 is characterised by an intense OH deformation band at 1150 cm-1 and two O-H stretching bands at 3107 and 3221 cm-1. In the infrared emission spectra, the hydroxyl-stretching and hydroxyl-bending bands diminish dramatically upon heating, and no intensity remains after 200 °C. However, new low intensity bands are found in the OH deformation region at 915 cm-1 and in OH stretching region at 3437 cm-1. These bands are attributed to the vibrations of newly formed InOH bonds because of the release and transfer of protons during calcination of the nanomaterial. The use of infrared emission spectroscopy enables the low-temperature phase transition brought about through dehydration of In(OH)3 nanocubes to be studied.
Resumo:
The concept of non-destructive testing (NDT) of materials and structures is of immense importance in engineering and medicine. Several NDT methods including electromagnetic (EM)-based e.g. X-ray and Infrared; ultrasound; and S-waves have been proposed for medical applications. This paper evaluates the viability of near infrared (NIR) spectroscopy, an EM method for rapid non-destructive evaluation of articular cartilage. Specifically, we tested the hypothesis that there is a correlation between the NIR spectrum and the physical and mechanical characteristics of articular cartilage such as thickness, stress and stiffness. Intact, visually normal cartilage-on-bone plugs from 2-3yr old bovine patellae were exposed to NIR light from a diffuse reflectance fibre-optic probe and tested mechanically to obtain their thickness, stress, and stiffness. Multivariate statistical analysis-based predictive models relating articular cartilage NIR spectra to these characterising parameters were developed. Our results show that there is a varying degree of correlation between the different parameters and the NIR spectra of the samples with R2 varying between 65 and 93%. We therefore conclude that NIR can be used to determine, nondestructively, the physical and functional characteristics of articular cartilage.
Resumo:
Raman spectroscopy has enabled insights into the molecular structure of the richelsdorfite Ca2Cu5Sb[Cl|(OH)6|(AsO4)4]·6H2O. This mineral is based upon the incorporation of arsenate or phosphate with chloride anion into the structure and as a consequence the spectra reflect the bands attributable to these anions, namely arsenate or phosphate and chloride. The richelsdorfite Raman spectrum reflects the spectrum of the arsenate anion and consists of ν1 at 849, ν2 at 344 cm−1, ν3 at 835 and ν4 at 546 and 498 cm−1. A band at 268 cm−1 is attributed to CuO stretching vibration. Low wavenumber bands at 185 and 144 cm−1 may be assigned to CuCl TO/LO optic vibrations.