基于数学形态学的复子波语音谱图特征提取与分析

从语音信号的复子波谱图着手,采用形态学图像处理方法提取语谱图中的语音形态。仿真实验取得了良好的效果,谱图中的语音形态较稳健地表征了汉语音节的韵音特征。语音形态的提取对于进一步的语音识别提供了一种新的途径。

Fluid sensitivity study of elastic parameters in lowmedium porosity and permeability reservoir rocks

In this article,based on the acoustic measurements of core samples obtained from the low to medium porosity and permeability reservoirs in the WXS Depression,the densities and P and S wave velocities of these core samples were obtained.Then based on these data,a series of elastic parameters were computed.From the basic theory and previous pore fluid research results,we derived a new fluid identification factor（F）.Using the relative variations,Ag/w and Ao/w,of the elastic parameters between gas and water saturated samples and between oil and water saturated samples,λρ,σHSFIF,Kρ,λρ-2μρ,and F as quantitative indicators,we evaluate the sensitivity of the different fluid identification factors to identify reservoir fluids and validate the effects by crossplots.These confirm that the new fluid identification factor（F） is more sensitive for distinguishing oil and water than the traditional method and is more favorable for fliud identification in low to medium porosity and permeability reservoirs.

气枪震源信号的产生及其对海洋哺乳动物的影响(二)

本文从单支气枪、气枪阵列、点震源响应、非点震源响应、气枪阵列方向性等方面说明海洋地震勘探中的震源信号的产生过程,并简要说明了海洋哺乳动物的声学反应过程,同时分析了这两者之间的关系,最终得出结论:地震信号对任何种类海洋哺乳动物的听觉几乎没有物理伤害。

The FDTD Full Wave Analysis of Fractal Antennas

The full wave FDTD method was used to analyze the Hilbert and H fractal curves antennas. The computational results of the input impedance of Hilbert fractal antenna are in good agreement with the experiments in the documents. The results also show that the self-similarity of the fractal structure leads to the multiplicity of resonances over some predetermined operating bandwidths of the antenna. Fractal geometries of Hilbert and H curves can be implemented to miniaturize the antenna, too. The results also show that the higher order fractal antenna leads to the more efficient reduction of the antenna size than the lower order one. Furthermore, the far field patterns remain almost the same as those of the dipole at their own resonant frequencies.

IMAGE WAVELET DENOISING USING THE ROBUST LOCAL THRESHOLD

This paper suggests a scheme of image denoising based on two-dimensional discrete wavelet transform. The denoising algorithm is described with some operators. By thresholding the wavelet transform coefficients of noisy images, the original image can be reconstructed correctly. Different threshold selections and thresholding methods are discussed. A new robust local threshold scheme is proposed. Quantifying the performance of image denoising schemes by using the mean square error, the performance of the robust local threshold scheme is demonstrated and is compared with the universal threshold scheme. The experiment shows that image denoising using the robust local threshold performs better than that using the universal threshold.

Detecting and Tracking Moving Targets on Omnidirectional Vision

A method was presented to implement the detecting and tracking of moving targets through omnidirec-tional vision. The method combined optical flow with particle filter arithmetic, in which optical flow field was used to detect and locate moving targets and particle filter was used to track the detected moving objects. According to the circular image character of omnidirectional vision, the calculation equation of optical flow field and the tracking arithmetic of particle filter were improved based on the polar coordinates at the omnidirectional center. The edge of a randomly moving object could be detected by optical flow field and was surrounded by a reference region in the particle filter. A dynamic motion model was established to predict particle state. Histograms were used as the fea-tures in the reference region and candidate regions. The mutual information (MI) and Gaussian function were com-bined to calculate particle weights. Finally, the state of tracked object was computed by the total particle states with weights. Experiment results show that the proposed method could detect and track moving objects with better real-time performance and accuracy.

Study on Internal Waves Generated by Tidal Flow over Critical Topography

Resonance due to critical slope makes the internal wave generation more effectively than that due to supercritical or subcritical slopes(Zhang et al., 2008). Submarine ridges make a greater contribution to ocean mixing than continental margins in global oceans(Müller, 1977; Bell, 1975; Baines, 1982; Morozov, 1995). In this paper, internal wave generation driven by tidal flow over critical topography is examined in laboratory using Particle Image Velocimetry(PIV) and synthetic schlieren methods in synchrony. Non-tidal baroclinic velocities and vertical isopycnal displacements are observed in three representative regions, i.e., critical, outward-propagating, and reflection regions. Temporal and spatial distributions of internal wave rays are analyzed using the time variations of baroclinic velocities and vertical isopycnal displacement, and the results are consistent with those by the linear internal wave theory. Besides, the width of wave beam changes with the outward propagation of internal waves. Finally, through monitoring the uniformly-spaced 14 vertical profiles in the x-z plane, the internal wave fields of density and velocity fields are constructed. Thus, available potential energy, kinetic energy and energy fluxes are determined quantitatively. The distributions of baroclinic energy and energy fluxes are confined along the internal wave rays. The total depth averaged energy and energy flux of vertical profiles away from a ridge are both larger than those near the ridge.

Contrast enhancement in retinal image via multi-scale geometrical analysis

We present a new multi-scale geometrical analysis method for ophthalmic image contrast enhancement based on the contourlet transform. The contourlet transform has better performance in representing edges than wavelets due to its anisotropy and directionality,and is therefore well-suited for multiscale edge enhancement. We modify the contourlet coefficients in corresponding subband and take the noise into account for mere precise reconstruction and better visualization. We compare this approach with enhancement based on the ourvelet transform,and the traditional Histogram Stretching （HS）. Our findings are that contourlet based enhancement out-performs other enhancement methods on low contrast and dynamic range images,and can clearly identify the vessels and nerves in an ophthalmic image.

Electrocardiogram Feature Extraction Technique Based on Wavelet Domain Lorentz Differential Deconvolution

In order to extract the cardiac characteristics in electrocardiogram (ECG), a feature extraction technique was developed based on wavelet domain Lorentz differential deconvolution. During the feature extraction of QRS complex, baseline drifts were firstly removed from raw ECG records by a mathematical morphology method and the feature sub-band of QRS complex was separated by using wavelet transform. Then an evolving Lorentz differential deconvolution technique was applied to estimating the local features of QRS complex from this sub-band. During the feature extraction of P and T waves, the above steps were similarly employed and, before wavelet transform, QRS complex was eliminated through locating their positions to avoid relevant disturbance. The proposed technique achieved a recognition of 99.37% for QRS recognition and a detection rate of 98.62% for P waves detection when tested with the MIT/BIH Database. And validated with the QT Database, the results of QT intervals detection also showed an obvious improvement (85.26% when target domain less than 14 ms and 95.34% when target domain less than 28 ms separately on average).

FAST TEXT LOCATION BASED ON DISCRETE WAVELET TRANSFORM

The paper describes a texture-based fast text location scheme which operates directly in the Discrete Wavelet Transform (DWT) domain. By the distinguishing texture characteristics encoded in wavelet transform domain, the text is fast detected from complex background images stored in the compressed format such as JPEG2000 without full decompress. Compared with some traditional character location methods, the proposed scheme has the advantages of low computational cost, robust to size and font of characters and high accuracy. Preliminary experimental results show that the proposed scheme is efficient and effective.

Dominant Correlogram Based Particle Filter Tracking

A novel dominant correlogram based particle filter was proposed for an object tracking in visual surveillance. Particle filter outperforms the Kalman filter in non-linear and non-Gaussian estimation problem. This paper proposed incorporating spatial information into visual feature, and yields a reliable likelihood description of the observation and prediction. A similarity-ratio is defined to evaluate the effectivity of different similarity measurements in weighing samples. The experimental results demonstrate the effective and robust performance compared with the histogram based tracking in traffic scenes.

SPATIALLY SCALABLE RESOLUTION IMAGE CODING METHOD WITH MEMORY OPTIMIZATION BASED ON WAVELET TRANSFORM

This letter exploits fundamental characteristics of a wavelet transform image to form a progressive octave-based spatial resolution. Each wavelet subband is coded based on zeroblock and quardtree partitioning ordering scheme with memory optimization technique. The method proposed in this letter is of low complexity and efficient for Internet plug-in software.

Mobile robot simultaneous localization and map building based on improved particle filter

We present an investigation into the use of pan tilt zoom camera and sonar sensors for simuhaneous localization and mapping with artificial colored landmarks. An improved particle filter is applied to estimate a posterior of the pose of the robot, in which each particle has associated it with an entire map. The distributions of landmarks are also represented by particle sets, where separate particles are used to represent the robot and the landmarks. Hough transform is used to extract line segments from sonar observations and build map simultaneously. The key advantage of our method is that the full posterior over robot poses and landmarks can be nonlinearly approximated at every point in time by particles. Especially the landmarks are affixed on the moving robots, which can reduce the impact of the depletion problem and the impoverishment problem produced by basic particle filter. Experimental results show that this approach has advantages over the basic particle filter and the extended Kalman filter.

Blind and readable image watermarking using wavelet tree quantization

A blind and readable image watermarking scheme using wavelet tree quantization is proposed. In order to increase the algorithm robustness and ensure the watermark integrity,error correction coding techniques are used to encode the embedded watermark. In the watermark embedding process, the wavelet coefficients of the host image are grouped into wavelet trees and each watermark bit is embedded by using two trees. The trees are so quantized that they exhibit a large enough statistical difference, which will later be used for watermark extraction. The experimental results show that the proposed algorithm is effective and robust to common image processing operations and some geometric operations such as JPEG compression, JPEG2000 compression, filtering, Gaussian noise attack, and row-column removal. It is demonstrated that the proposed technique is practical.

Embedding ensemble tracking in a stochastic framework for robust object tracking

We propose an algorithm of embedding ensemble tracking in a stochastic framework to achieve robust tracking performance under partial occlusion,illumination changes,and abrupt motion.It operates on likelihood images generated by the ensemble method,and combines mean shift and particle filtering in a principled way,where a better proposal distribution is de-signed by first propagating particles via a motion model,and then running mean shift to move towards their local peaks in the likelihood image.An observation model in the particle filter incorporates global and local information within a region,and an adaptive motion model is adopted to depict the evolution of the object state.The algorithm needs fewer particles to manage the tracking task compared with the general particle filter,and recaptures the object quickly after occlusion occurs.Experiments on two image sequences demonstrate the effectiveness and robustness of the proposed algorithm.

Parton physics from large-momentum effective field theory

Parton physics,when formulated as light-front correlations,are difficult to study non-perturbatively,despite the promise of lightfront quantization.Recently an alternative approach to partons have been proposed by re-visiting original Feynman picture of a hadron moving at asymptotically large momentum.Here I formulate the approach in the language of an effective field theory for a large hadron momentum P in lattice QCD,LaMET for short.I show that using this new effective theory,parton properties,including light-front parton wave functions,can be extracted from lattice observables in a systematic expansion of 1/P,much like that the parton distributions can be extracted from the hard scattering data at momentum scales of a few GeV.