Linear Discriminant Analysis (LDA) is frequently used for dimension reduction and has been successfully utilized in many applications, especially face recognition. In classical LDA, however, the definition of the betw...
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Due to ear's complex structure, particular position, and preferable stability, ear biometrics has attracted increasingly attention recently. In this paper, we present a new multi-view based ear feature extraction ...
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Due to ear's complex structure, particular position, and preferable stability, ear biometrics has attracted increasingly attention recently. In this paper, we present a new multi-view based ear feature extraction strategy. We utilize not only front view ear image but backside view ear image to extract 2D ear shape four kinds of rich features for ear recognition. In addition, we utilize multi-view ear images to reconstruct 3D ear shape, and a neural network 3D ear registration method is introduced also. Experimental results and comparison analysis show our multi-view based strategy will be a promising approach for ear biometrics.
In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for im...
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ISBN:
(纸本)9780819469519
In this paper, a pixel-level image fusion algorithm based on Nonsubsampled Contourlet Transform (NSCT) has been proposed. Compared with Contourlet Transform, NSCT is redundant, shift-invariant and more suitable for image fusion. Each image from different sensors could be decomposed into a low frequency image and a series of high frequency images of different directions by multi-sacle NSCT. For low and high frequency images, they are fused based on local-contrast enhancement and definition respectively. Finally, fused image is reconstructed from low and high frequency fused images. Experiment demonstrates that NSCT could preserve edge significantly and the fusion rule based on region segmentation performances well in local-contrast enhancement.
Proposed is a novel theory for SAR (synthetic aperture radar) image de-noising based on ICA (independent component analysis) basis images. Firstly, the basis images and the code matrix of the original image are obtain...
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Proposed is a novel theory for SAR (synthetic aperture radar) image de-noising based on ICA (independent component analysis) basis images. Firstly, the basis images and the code matrix of the original image are obtained using ICA algorithm. Then, pointwise Holder exponent of each basis is computed as a cost criterion for basis enhancement, and then the enhanced basis images are classified into two sets according to a separation rule which means the clean basis can be separated from the original basis. These two procedures are the key points for speckle reduction. Finally, the clean image is obtained by reconstruction on the clean basis and original code matrix. As the results show, the reconstructed image achieves a better visual perception compared to those obtained by other traditional techniques, and a lower value of SD/M (ratio of standard deviation to mean) factor has been calculated demonstrating better image quality.
A computer aided reconstruction and motion analysis method of mitral annulus is presented in this paper. To begin with, the boundary points on mitral annulus are marked by doctors interactively. Since these points are...
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This paper presents uncertainty propagation in landmark based position estimation methods. Analysis of two methods has been carried out where robot position is estimated by detecting one or two globally distinct featu...
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ISBN:
(纸本)9784901122078
This paper presents uncertainty propagation in landmark based position estimation methods. Analysis of two methods has been carried out where robot position is estimated by detecting one or two globally distinct features using a pivoted stereo vision system. We make a basic assumption about error in estimating point features in camera images and propagate it into robot position estimate using first order approximation of non-linear functions. Simulation results illustrate the performance of the method.
The increasing use of color terminals for personal computers has raised a demand for video graphic adapter(VGA)-format panel displays. Since only monochrome(ZnS∶Mn) electroluminescence(EL) displays of suitable size a...
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The increasing use of color terminals for personal computers has raised a demand for video graphic adapter(VGA)-format panel displays. Since only monochrome(ZnS∶Mn) electroluminescence(EL) displays of suitable size and speed are available, lack of colors has to be replaced by grayscale in the first place. There are two basic driving methods to achieve grayscale in thin-film EL displays: pulse amplitude modulation(PAM) method and pulse width modulation(PWM) method. But there are serious disadvantages of the two traditional methods. For the former method, the high voltage PAM ICs are too expensive to produce the grayscale EL display in bulks and the driver integrated circuit(IC) is complex. Though the PWM method has good grayscale display quality, the hardware implementation is too complex. A new driving method with which the width and the amplitude of the pulse can be modulated and simultaneously the challenge can be solved efficaciously is presented.
The technologies of intra prediction and MBAFF were introduced, and a new intra prediction mode based on the characteristics of spatial distribution in interlaced video was proposed. The spatial correlation of five lu...
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The technologies of intra prediction and MBAFF were introduced, and a new intra prediction mode based on the characteristics of spatial distribution in interlaced video was proposed. The spatial correlation of five luma intra prediction modes in AVS-P2 and the new mode were analyzed. From the analysis result, it can be concluded that the new mode can exploit the spatial correlation better and predict the samples more precisely than the existed ones. The experimental results showed that the average gain in peak signal to noise ratio was above 0.12dB and the average reduction in bit-rate was above 1.77%, so the proposed mode is an effective prediction mode for improvement of coding performance.
Refinement is a necessary and effective step in some node localization schemes of wireless sensor networks (WSN). Suitable refinement procedure can improve the node localization accuracy and raise the robustness of th...
Refinement is a necessary and effective step in some node localization schemes of wireless sensor networks (WSN). Suitable refinement procedure can improve the node localization accuracy and raise the robustness of the localization algorithm. However, most existing refinement algorithms are costly duo to complex computation and frequent communication, and may induce serious coverage problem duo to nonconvergent iterations. In view of above facts, Steepest descent method is proposed to be used as the refinement algorithm in this paper, and corresponding simulation experiments are done to testify its feasibility and validity. The results show that steepest descent method can optimize the node positions to a fairish accuracy extent, and compared with existing refinement methods, it outperforms in communication cost, computation cost, and coverage rate.
This paper presents the research on stability for biped Walking-Chair robot with human-in-the-loop. The inherent properties of the biped system which is developed for the disable people to replace traditional wheelcha...
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