墙地砖边缘检测中的小波去噪

在墙地砖的边缘检测过程中,噪声的引入是不可避免的,有效地消除噪声而不影响检测结果是检测过程中需要解决的关键问题。本文采用了小波去噪方法—对图像进行去噪后再进行边缘检测的方法,其检测结果较好地满足了检测要求。     

Classification of cardiac sound signals using constrained tunable-Q wavelet transform

The features extracted from the cardiac sound signals are commonly used for detection and identification of heart valve disorders. In this paper, we present a new method for classification of cardiac sound signals using constrained tunable-Q wavelet transform (TQWT). The proposed method begins with a constrained TQWT based segmentation of cardiac sound signals into heart beat cycles. The features obtained from heart beat cycles of separately reconstructed heart sounds and murmur can better represent the various types of cardiac sound signals than that from containing both. Therefore, heart sounds and murmur have been separated using constrained TQWT. Then the proposed novel raw feature set has been created by the parameters that have been optimized while constraining the output of TQWT together with that of extracted by using time-domain representation and Fourier–Bessel (FB) expansion of separated heart sounds and murmur. However, the adaptively selected features have been used to obtain the final feature set for subsequent classification of cardiac sound signals using least squares support vector machine (LS-SVM) with various kernel functions. The performance of the proposed method has been validated with publicly available datasets and the results have been compared with the existing short-time Fourier transform (STFT) based method. The proposed method shows higher percentage classification accuracy of 94.01 as compared to 93.53 of STFT based method. In comparison with STFT based method, it is noteworthy that the proposed method uses well defined and lower dimensionality of feature vector that can reduce the computational complexity.     

Contraction stress build‐up of anisotropic conductive films (ACFs) for flip‐chip interconnection: Effect of thermal and mechanical properties of ACFs

The important mechanical mechanism for the electrical conduction of anisotropic conductive films (ACFs) is the joint clamping force after the curing and cooling processes of ACFs. In this study, the mechanism of shrinkage and contraction stress and the relationship between these mechanisms and the thermomechanical properties of ACFs were investigated in detail. Both thickness shrinkages and modulus changes of four kinds of ACFs with different thermomechanical properties were experimentally investigated with thermomechanical and dynamic mechanical analysis. Based on the incremental approach to linear elasticity, contraction stresses of ACFs developed along the thickness direction were estimated. Contraction stresses in ACFs were found to be significantly developed by the cooling process from the glass‐transition temperature to room temperature. Moreover, electrical characteristics of ACF contact during the cooling process indicate that the electrical conduction of ACF joint is robustly maintained by substantial contraction stress below T_g. The increasing rate of contraction stresses below T_g was strongly dependent on both thermal expansion coefficient (CTE) and elastic modulus (E) of ACFs. A linear relationship between the experimental increasing rate and E × CTE reveals that the build‐up behavior of contraction stress is closely correlated with the ACF material properties: thermal expansion coefficient, glassy modulus, and T_g. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 93: 2634–2641, 2004     

基于改进小波去噪和EMD方法的轴承故障诊断

将改进的小波阈值去噪与EMD分解相结合应用于轴承故障诊断中。该方法首先利用改进的小波阈值去噪法对原始信号进行去噪,然后采用EMD方法将去噪后的信号自适应地分解成一系列IMF分量之和,通过能量-相关系数法选取能够反映故障特征的IMF分量进行包络谱分析提取故障频率。实验结果表明该方法能够有效识别故障特征频率。     

结合小波变换的梯度场图像渐进融合算法

基于梯度场的图像融合算法只适用于尺度差异不大于1∶4的多光谱图像与全色图像。针对尺度差异为1∶8的北京一号卫星多光谱图像及高分辨率全色图像的融合问题,提出一种结合小波变换的梯度场图像尺度渐进融合算法。利用小波变换方法将多光谱图像与高分辨率全色图像尺度差异倍数缩小,得到基于小波变换的初级融合,再进行基于梯度场的Poisson图像融合。实验结果表明,渐进融合图像与多光谱图像的平均颜色差异值为23.5,与高分辨率全色图像的平均梯度差异值为2.1,多尺度纹理特征值差异值分别为3.98、10.2、18.9,渐进融合图像与高分辨率全色图像的空间细节和纹理细节吻合程度更好。     

环氧丙烯酸树脂的合成研究

研究合成了一种环氧丙烯酸树脂,该树脂既具有环氧树脂优良的黏结性能、收缩率低等特点,又克服了其抗冲击性差的缺点,还可以室温固化,应用广泛.     

基于轮廓波变换的织物疵点图像消噪新方法

为了实现织物疵点图像的有效消噪,使其更有利于特征提取和疵点检测,提出了基于轮廓波变换的织物疵点图像消噪新方法。综合考虑轮廓波方向子带能量的大小与织物疵点图像轮廓细节之间的关系,对Donoho多尺度分解阈值进行修正,改进了Donoho多尺度分解阈值对图像细节"过扼杀"的缺点。实验结果表明,对织物疵点图像进行基于轮廓波变换改进阈值消噪时,该方法更好地保留了织物疵点图像的轮廓细节,峰值信噪比显著提高。采用改进的轮廓波Donoho多尺度分解阈值消噪后的图像,可以更好地应用于织物疵点图像的特征提取和疵点识别。     

基于Hilbert曲线和位置自调节法的图像版权保护算法

以小波的相关理论为基础,先把水印图像预置乱处理,对宿主图像直接进行小波包分解,之后将水印的低频部分和中高频部分分别采用Hilbert曲线扫描和位置自调节法嵌入到宿主图像中,嵌入强度可根据图像的内容自适应调节。通过实验观察,新算法在抗压缩和抗剪切性能有所提升,同时隐蔽性和抗噪能力也得到了较大改观,结果充分说明该算法是一种性能较为优良的图像版权保护算法。     

基于退化四元小波变换的纸币识别

针对如何提取纸币图像特征和提高识别率的问题,综合利用退化四元小波变换具有的相位特性,提出一种基于退化四元小波变换的纸币识别方法.该方法首先对采集的纸币图像进行倾斜校正和边缘检测,然后运用退化四元小波对纸币图像进行分解操作,并对分解系数进行统计分析,将每个分解子带系数的能量和标准差作为该纸币图像的特征向量,最后将支持向量机作为分类器对纸币图像进行识别.本文方法在资源约束的嵌入式清分系统上实现,实验结果表明采用本文提出的算法突破了传统纸币识别系统识别率很难再提高的瓶颈,同时能够满足清分系统的实时性要求.     

复合材料RTM模具的制备

根据树脂传递模塑(RTM)模具对基体树脂的基本要求,选用双酚A环氧乙烯基酯树脂为基体,聚乙酸乙烯酯为低收缩添加剂,玻璃纤维经编织物为增强材料,并加入相应的助剂,制备了复合材料RTM模具。该模具具有成本较低、开发周期短、精度较高等优点,但表面强度和热效率较低。