30 resultados para WAVELET ANALYSIS

em Deakin Research Online - Australia


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The problem of dimensional defects in aluminum die- casting is widespread throughout the foundry industry and their detection is of paramount importance in maintaining product quality. Due to the unpredictable factory environment and metallic, with highly reflective, nature of aluminum die-castings, it is extremely hard to estimate true dimensionality of the die-casting, autonomously. In this work, we propose a novel robust 3D reconstruction algorithm capable of reconstructing dimensionally accurate 3D depth models of the aluminum die-castings. The developed system is very simple and cost effective as it consists of only a stereo cameras pair and a simple fluorescent light. The developed system is capable of estimating surface depths within the tolerance of 1.5 mm. Moreover, the system is invariant to illuminative variations and orientation of the objects in the input image space, which makes the developed system highly robust. Due to its hardware simplicity and robustness, it can be implemented in different factory environments without a significant change in the setup.

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A complete and highly robust 3D reconstruction algorithm based on stereo vision is presented. The developed system is capable of reconstructing dimensionally accurate 3D models of the objects and is very simple and cost effective due to its prominent software dependency and minimal hardware involvevment unlike existing systems.

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A number of methods for automated objective ratings of fabric pilling based on image analysis are described in the literature. The periodic structure of fabrics makes them suitable candidates for frequency domain analysis. We propose a new method of frequency domain analysis based on the two-dimensional discrete wavelet transform to objectively measure pilling intensity in sample images. We present a preliminary evaluation of the proposed method based on analysis of two series of standard pilling evaluation test images. The initial results suggest that the proposed method is feasible, and that the ability of the method to discriminate between levels of pilling intensity depends on the wavelet analysis scale being closely matched to the fabric interyarn pitch. We also present a heuristic method for optimal selection of an analysis wavelet and associated analysis scale.


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Fabric pilling is a serious problem for the apparel industry, causing an unsightly appearance and premature wear. Woolen products are particularly prone to pilling. Recently, a process for production of woolen nonwoven apparel fabrics has been commercialized in Australia, and may lead to new markets for Australian wool. However, the success of such nonwoven fabrics will partly rely on their propensity to pill. A key element in the control of fabric pilling is the evaluation of resistance to pilling by testing. Resistance to pilling is normally tested in the laboratory by processes that simulate accelerated wear, followed by a manual assessment of the degree of pilling by an expert based on a visual comparison of the sample to a set of test images. To bring more objectivity into the pilling rating process, a number of automated systems based on image analysis have been developed. The authors previously proposed a new method of image analysis based on the two-dimensional discrete wavelet transform to objectively measure the pilling intensity for woven fabrics. This paper presents preliminary work in extending this method to nonwoven fabrics.

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In this study, we have investigated the evidence of fetal heart rate asymmetry and how the fetal heart rate asymmetry changes before and after 35 weeks of gestation. Noninvasive fetal electrocardiogram (fECG) signals from 45 pregnant women at the gestational age from16 to 41 weeks with normal single pregnancies were analysed. A nonlinear parameter called heart rate asymmetry (HRA) index that measures time asymmetry of RR interval time-series signal was used to understand the changes of HRA in early and late fetus groups. Results indicate that fetal HRA measured by Porta's Index (PI) consistently increases after 35 weeks gestation compared to foetus before 32 weeks of gestation. It might be due to significant changes of sympatho-vagal balance towards delivery with more sympathetic surge. On the other hand, Guzik's Index (GI) showed a mixed effect i.e., increases at lower lags and decreases at higher lags. Finally, fHRA could potentially help identify normal and the pathological autonomic nervous system development.

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Previously, the authors proposed a new, simple method of frequency domain analysis based on the two-dimensional discrete wavelet transform to objectively measure the pilling intensity in sample fabric images. The method was further characterized, and the results obtained indicate that standard deviation and variance are the most appropriate measures of the dispersion of wavelet details coefficients for analysis, that the relationship between wavelet analysis scale and fabric inter-yarn pitch was empirically confirmed, and, that fabrics with random patterns do not appear to impact on the effectiveness of the analysis method.

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Background: Individual variations in the use of the species niche are an important component of diversity in trophic interactions. A challenge in testing consistency of individual foraging strategy is the repeated collection of information on the same individuals.

Methodology/Principal Findings: The foraging strategies of sympatric fur seals (Arctocephalus gazella and A. tropicalis) were examined using the stable isotope signature of serially sampled whiskers. Most whiskers exhibited synchronous delta C-13 and delta N-15 oscillations that correspond to the seal annual movements over the long term (up to 8 years). delta C-13 and delta N-15 values were spread over large ranges, with differences between species, sexes and individuals. The main segregating mechanism operates at the spatial scale. Most seals favored foraging in subantarctic waters (where the Crozet Islands are located) where they fed on myctophids. However, A. gazella dispersed in the Antarctic Zone and A. tropicalis more in the subtropics. Gender differences in annual time budget shape the seal movements. Males that do not perform any parental care exhibited large isotopic oscillations reflecting broad annual migrations, while isotopic values of females confined to a limited foraging range during lactation exhibited smaller changes. Limited inter-individual isotopic variations occurred in female seals and in male A. tropicalis. In contrast, male A. gazella showed large inter-individual variations, with some males migrating repeatedly to high-Antarctic waters where they fed on krill, thus meaning that individual specialization occurred over years.

Conclusions/Significance: Whisker isotopic signature yields unique long-term information on individual behaviour that integrates the spatial, trophic and temporal dimensions of the ecological niche. The method allows depicting the entire realized niche of the species, including some of its less well-known components such as age-, sex-, individual- and migration-related changes. It highlights intrapopulation heterogeneity in foraging strategies that could have important implications for likely demographic responses to environmental variability.

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Lemming population cycles in the Arctic have an important impact on the Arctic food web, indirectly also affecting breeding success in Arctic-nesting birds through shared predators. Over the last two decades lemming cycles have changed in amplitude and even disappeared in parts of the Arctic. To examine the large scale effect of these recent changes we re-analysed published data from the East Atlantic Flyway (EAF), where a relationship between lemming cycles and wader breeding success was earlier found, and new data on breeding success of waders in the East Asian-Australasian Flyway (EAAF). We found that 1) any long-term periodicities in wader breeding success existed only until the year 2000 in the EAAF and until the 1980s in the EAF; 2) studying these patterns at a smaller spatial scale, where the Siberian-Alaskan breeding grounds were divided into five geographical units largely based on landscape features, breeding success of waders from the EAAF was not correlated to an index of predation pressure, but positively correlated to Arctic summer temperatures in some species. We argue that fading out of lemming cycles in some parts of the Arctic is responsible for faltering periodicity in wader breeding success along both flyways. These changed conditions have not yet resulted in any marked changing trends in breeding success across years, and declining numbers of waders along the EAAF are therefore more likely a result of changing conditions at stop-over and wintering sites.

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A new objective fabric pilling grading method based on wavelet texture analysis was developed. The new method created a complex texture feature vector based on the wavelet detail coefficients from all decomposition levels and horizontal, vertical and diagonal orientations, permitting a much richer and more complete representation of pilling texture in the image to be used as a basis for classification. Standard multi-factor classification techniques of principal components analysis and discriminant analysis were then used to classify the pilling samples into five pilling degrees. The preliminary investigation of the method was performed using standard pilling image sets of knitted, woven and non-woven fabrics. The results showed that this method could successfully evaluate the pilling intensity of knitted, woven and non-woven fabrics by selecting the suitable wavelet and associated analysis scale.

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This paper presents the use of the wavelet transform to extract fibre surface texture features for classifying cashmere and superfine merino wool fibres. To extract features from brightness variations caused by the cuticular scale height, shape and interval provides an effective way for characterising different animal fibres and subsequently classifying them. This may enable the development of a completely automated and objective system for animal fibre
identification.

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This paper presents the use of the wavelet transform to extract fiber surface texture features for classifying cashmere and superfine merino wool fibers. Extracting features from brightness variations caused by the cuticular scale height, shape and interval provides an effective way for characterizing different animal fibers and subsequently classifying them. This may enable the development of a completely automated and objective system for animal fiber identification.