992 resultados para Integral Transform
Resumo:
A multi-resolution image matching technique based on multiwavelets followed by a coarse to fine strategy is presented. The technique addresses the estimation of optimal corresponding points and the corresponding disparity maps in the presence of occlusion, ambiguity and illuminative variations in the two perspective views taken by two different cameras or at different lighting conditions. The problem of occlusion and ambiguity is addressed by a geometric topological refining approach along with the uniqueness constraint whereas the illuminative variation is dealt by using windowed normalized correlation.
Resumo:
A multi-resolution image matching technique based on translation invariant discrete multi-wavelet transform followed by a coarse to fine matching strategy is presented. The technique addresses the estimation of optimal corresponding points and the corresponding disparity maps in the presence of occlusion, ambiguity and illuminative variations in the two perspective views taken by two different cameras or at different lighting conditions. The problem of occlusion and ambiguity is addressed explicitly by a geometric optimization approach along with the uniqueness constraint whereas the illuminative variation is dealt with by using windowed normalized correlation on the discrete multi-wavelet coefficients.
Resumo:
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.
Resumo:
This paper describes a potentially faster and cheaper method of determining fibre scale frequencies. The method uses the single fibre analyser (SIFAN) to determine the along the fibre diameter profile. This information is then analysed by the Fast Fourier Transform technique using computer software. The paper shows the close association between the mean scale frequencies determined by this method and the traditional approach using SEM.
Resumo:
Protein kinase C (PKC) is a family of serine/threonine protein kinases that are pivotal in cellular regulation. Since its discovery in 1977, PKCs have been known as cytosolic and peripheral membrane proteins. However, there are reports that PKC can insert into phospholipids vesicles in vitro. Given the intimate relationship between the plasma membrane and the activation of PKC, it is important to determine whether such “membrane-inserted” form of PKC exists in mammalian cells or tissues. Here, we report the identification of an integral plasma membrane pool for all the 10 PKC isozymes in vivo by their ability to partition into the detergent-rich phase in Triton X-114 phase partitioning, and by their resistance to extractions with 0.2 M sodium carbonate (pH 11.5), 2 M urea and 2 M sodium chloride. The endogenous integral membrane pool of PKC in mouse fibroblasts is found to be acutely regulated by phorbol ester or diacylglycerol, suggesting that this pool of PKC may participate in cellular processes known to be regulated by PKC. At least for PKCα, the C2–V3 region at the regulatory domain of the kinase is responsible for membrane integration. Further exploration of the function of this novel integral plasma membrane pool of PKC will not only shed new light on molecular mechanisms underlying its cellular functions but also provide new strategies for pharmaceutical modulation of this important group of kinases.
Resumo:
In this paper, the stability and convergence properties of the class of transform-domain least mean square (LMS) adaptive filters with second-order autoregressive (AR) process are investigated. It is well known that this class of adaptive filters improve convergence property of the standard LMS adaptive filters by applying the fixed data-independent orthogonal transforms and power normalization. However, the convergence performance of this class of adaptive filters can be quite different for various input processes, and it has not been fully explored. In this paper, we first discuss the mean-square stability and steady-state performance of this class of adaptive filters. We then analyze the effects of the transforms and power normalization performed in the various adaptive filters for both first-order and second-order AR processes. We derive the input asymptotic eigenvalue distributions and make comparisons on their convergence performance. Finally, computer simulations on AR process as well as moving-average (MA) process and autoregressive-moving-average (ARMA) process are demonstrated for the support of the analytical results.
Resumo:
This paper studies the integral terminal sliding mode cooperative control of multi-robot networks. Here, we first propose an integral terminal sliding mode surface for a class of first order systems. Then, we prove that finite time consensus tracking of multi-robot networks can be achieved on this integral terminal sliding mode surface. Simulation results are presented to validate the analysis.
Resumo:
In this paper, the analysis for the performance of the discrete Fourier transform LMS adaptive filter (DFT-LMS) and the discrete cosine transform LMS adaptive filter (DCT-LMS) for the Markov-2 inputs is presented. To improve the convergence property of the least mean squares (LMS) adaptive filter, the DFT-LMS and DCT-LMS preprocess the inputs with the fixed orthogonal transforms and power normalization. We derive the asymptotic results for the eigenvalues and eigenvalue distributions of the preprocessed input autocorrelation matrices with DFT-LMS and DCT-LMS for Markov-2 inputs. These results explicitly show the superior decorrelation property of DCT-LMS over that of DFT-LMS, and also provide the upper bounds for the eigenvalue spreads of the finite-length DFT-LMS and DCT-LMS adaptive filters. Simulation results are demonstrated to support the analytic results.
Resumo:
In the present work, the carbon diffusion in steel, where the carbon diffusivity varies with the carbon content, was solved with the integral methods under the third boundary condition. The variation of carbon diffusivity in steel with the carbon content was described with two different functions ie. linear dependence and exponential dependence. The integral approximation for both cases was improved with the numerical computation to more accurately predict the carbon profiles. The integral solution is more accurate than the formulation based on the assumption of a constant diffusivity or those based on the assumption of a constant diffusivity and/or constant carbon content at part surface. It is also more easily used in practice than the numerical method to describe the carburising process and predict the carbon content at steel surface and carbon profiles in treated layer.