Image compression had been extensively studied for reducing coding rate yet producing acceptable visual quality. However, there are many application scenarios where the compressed images are used for automatic recogni...
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ISBN:
(纸本)9781479973408
Image compression had been extensively studied for reducing coding rate yet producing acceptable visual quality. However, there are many application scenarios where the compressed images are used for automatic recognition rather than human viewing, thus the visual quality is no longer critical for compression. SIFT features have demonstrated their utility in many recognition scenarios and SIFT-preserving compression is developed recently. In this paper, we firstly study the SIFT-preserving compression of license plate images for recognition accuracy rather than visual quality. According to extracted SIFT features, each image is divided into SIFT coding-units and non-SIFT coding-units. Each coding-unit is assigned with a different quality parameter when using JPEG for compression. We compare our proposed scheme with the standard JPEG that uses a unified quality parameter. Experimental results with manually tuned parameters show that on average 14% bit-rate can be saved by our scheme, without any loss of recognition accuracy.
This system present a feasibility of computer-aided diagnosis, planning and simulation for orthodontic treatment. In the Visualization Toolkit (VTK) and Microsoft Foundation Classes (MFC) integrated environment, a fle...
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This system present a feasibility of computer-aided diagnosis, planning and simulation for orthodontic treatment. In the Visualization Toolkit (VTK) and Microsoft Foundation Classes (MFC) integrated environment, a flexible, friendly and functional interface for orthodontic treatment was designed. The methods of how to integrate VTK and MFC in different system are described, and the three-dimensional model of the dentition is reconstructed by using marching-cubes (MC) algorithms. Finally, the three-dimensional model for rendering and interaction is also introduced.
The ultra-weak luminescence (UWL) feature of plant seeds is investigated. Before UWL measurement, the maize seeds are moistened in distilled water for various periods, which are 2h, 4h, 6h and 8h. And then the seeds a...
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The relative rate of electrostatic discharge (ESD)-related failures or upsets is derived for various types of data centers based on different flooring systems and personal footwear. As the estimation of the actual num...
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In this paper, we study the existence, uniqueness and stability of periodic solution for a wide class of memristor-based neural networks with time-varying delays. By employing the topological degree theory in set-valu...
In this paper, we study the existence, uniqueness and stability of periodic solution for a wide class of memristor-based neural networks with time-varying delays. By employing the topological degree theory in set-valued analysis, differential inclusions theory and a new Lyapunov function method, we prove that the neural network has a unique periodic solution, which is globally exponentially stable. Moreover, we prove the existence, uniqueness and global exponential stability of equilibrium point for time-varying delayed memristor-based neural networks with constant coefficients. The obtained results improve and extend previous works on memristor-based or usual neural network dynamical systems with continuous or discontinuous right-hand side. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results.
This paper revisits the problem of estimating the domain of attraction for systems with saturation *** divide the input space into several regions. In one of these regions, none of the inputs saturate. In each of the ...
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ISBN:
(纸本)9781479947249
This paper revisits the problem of estimating the domain of attraction for systems with saturation *** divide the input space into several regions. In one of these regions, none of the inputs saturate. In each of the remaining regions, there is a unique input that saturates everywhere with the time-derivative of its saturated signal being zero. These special properties of the inputs in different regions of the input space are combined with an existing piecewise quadratic Lyapunov functions that contains the information of input saturation to arrive at a set of less conservative stability conditions, from which a larger level set of the piecewise quadratic Lyapunov function can be obtained as an estimate of the domain of *** results indicate that the proposed approach has the ability to obtain a significantly larger estimate of the domain of attraction than the existing methods.
Multiple scattering may render synthetic aperture radar (SAR) image interpretation difficult, particularly when it comes to imaging of man-made structures, which can be modeled as composite scatterers. To isolate diff...
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Multiple scattering may render synthetic aperture radar (SAR) image interpretation difficult, particularly when it comes to imaging of man-made structures, which can be modeled as composite scatterers. To isolate different scattering mechanism, we designed an airborne SAR experiment based on the high resolution, sub-metric to decimetric range, capabilities full-polarimetric SAR system, CARSS (Chinese Airborne Remote Sensing system), developing by IECAS. The imaging results are quite accord with the theoretical analysis. With polarimetric target decomposition, we can simply distinguish the different scattering mechanism. The idea to interpret the man-made targets as the combination of simple scattering mechanisms is supported by the experiment results.
According to the problem that conventional laminated paper counting algorithms have some unavoidable shortcomings such as high dependence on the quality of laminated paper and noise sensitivity, we propose a laminated...
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ISBN:
(纸本)9781479953004
According to the problem that conventional laminated paper counting algorithms have some unavoidable shortcomings such as high dependence on the quality of laminated paper and noise sensitivity, we propose a laminated paper counting algorithm based on compressive sensing (CS) and Hough transform (HT). In the proposed algorithm, the over-complete dictionary which is created by dispersing the Hough transform space of straight lines acts as the sparse matrix. Making use of high degree of sparse nature of the laminated paper image, we can obtain the accurate result through using CS theory. Experimental results on simulation images and laminated paper images have shown that our proposed algorithm can effectively restrain noise of the laminated paper image, and will get accurate experimental results with fewer CS measurements.
Communication bandwidth and network topology are two important factors that affect performance of distributed consensus in multi-agent *** available works about quantized average consensus assume that the adjacency ma...
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Communication bandwidth and network topology are two important factors that affect performance of distributed consensus in multi-agent *** available works about quantized average consensus assume that the adjacency matrices associated with the digraphs are doubly stochastic,which amounts to that the digital networks are ***,this assumption may be unrealistic in *** this paper,without assuming double stochasticity,the authors revisit an existing quantized average consensus protocol with the logarithmic quantization scheme,and investigate the quantized consensus problem in general directed digital networks that are strongly connected but not necessarily *** authors first derive an achievable upper bound of the quantization precision parameter to design suitable logarithmic quantizer,and this bound explicitly depends on network ***,by means of the matrix transformation and the Lyapunov techniques,the authors provide a testable condition under which the weighted average consensus can be achieved with the proposed quantized protocol.
In this article, we present a novel non-local video denoising scheme using low-rank representation and total variation regularization. The proposed scheme attempts to make full use of the intrinsic properties that the...
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ISBN:
(纸本)9781479934331
In this article, we present a novel non-local video denoising scheme using low-rank representation and total variation regularization. The proposed scheme attempts to make full use of the intrinsic properties that the grouping similar patches not only lie in a low-rank subspace but are also sparse in total variation (TV) domain. For a group of similar patches, we formulate video denoising problem into a concise model that combines nuclear norm, TV regularization and l_1 norm. The experiments demonstrate that the proposed scheme is capable of handling multi-type noise including dense Gaussian noise and random-valued sparse noise, while maintaining the texture information meantime. The results show that our scheme achieves noticeable performance improvement over the state-of-the-art video denoising methods.
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