一种基于Gabor滤波器的超声图像边缘检测方法

针对检测超声图像的边缘问题，介绍了一种基于Gabor奇部滤波器进行边缘检测的综合方法。为了去除图像噪声，首先进行基于小波变换和中值滤波的降噪处理，然后利用高斯函数平滑图像。在边缘检测过程中，使用Gabor奇部滤波器检测边缘。最后，使用非最大值抑制得到最终结果。结果表明该方法是对超声图像进行边缘检测的一种有用方法。当然，该方法也具有普遍性，可以应用到其他图像。     

Super-resolution video generation algorithm for surveillance applications

Video surveillance is one of the major applications where high-resolution (HR) images are crucial. Since the video camera has limited spatial and temporal resolution, there is a need for super resolution video generation algorithms. In this paper, we have presented a novel technique for activity detection in the surveillance video. To achieve this goal, we have proposed and investigated efficient algorithms for Video Object Plane (VOP) generation, shadow removal from VOP and super-resolved VOP generation, for activity detection from surveillance video. The proposed VOP generation algorithm is computationally efficient and works for both dynamic and static backgrounds. The novel shadow removal algorithm for the VOP is based on texture and its performance has been studied based on average shadow detection and discrimination rates. The proposed super-resolution video generation algorithm has been designed using edge models. The performance of this algorithm has been evaluated using a numerical analysis technique and is found to be better than bi-cubic and bi-linear interpolation techniques.     

基于不同加工工艺的微小型结构件边缘识别

针对不同加工工艺微小型结构件的不同边缘特征,提出了一种基于工艺匹配思想的微小型结构件边缘识别算法．该算法通过计算有效平均梯度,提取不同加工工艺微小型结构件的边缘过渡区,建立边缘过渡区的多项式回归模型,求导确定边缘点精确位置．通过对4种常用微细加工工艺建模分析可以看出,加工工艺对微小型结构件边缘区域影响较大,边缘精确识别时应加入工艺匹配的思想．该算法考虑了实际加工工艺的影响,算法上加入统计学方法,通过建立过渡区数学模型,使边缘检测结果达到亚像素级．     

Sparse deconvolution of B-scan images

In this paper, a new computationally efficient sparse deconvolution algorithm for the use on B-scan images from objects with relatively few scattering targets is presented. It is based on a linear image formation model that has been used earlier in connection with linear minimum mean squared error (MMSE) two-dimensional (2-D) deconvolution. The MMSE deconvolution results have shown improved resolution compared to synthetic aperture focusing technique (SAFT), but at the cost of increased computation time. The proposed algorithm uses the sparsity of the image, reducing the degrees of freedom in the reconstruction problem, to reduce the computation time and to improve the resolution. The dominating task in the algorithm consists in detecting the set of active scattering targets, which is done by iterating between one up-dating pass that detects new points to include in the set, and a down-dating pass that removes redundant points. In the up-date, a spatiotemporal matched filter is used to isolate potential candidates. A subset of those are chosen using a detection criterion. The amplitudes of the detected scatterers are found by MMSE. The algorithm properties are illustrated using synthetic and real B-scan. The results show excellent resolution enhancement- and noise-suppression capabilities. The involved computation times are analyzed.     

A third-order active-R filter with feedforward input signal

A realization of voltage-mode transfer functions with feedforward input signal for third-order active-R filter using an oprational amplifier has been presented. This filter is useful for high frequency operation, monolithic IC implementation and is easy to design. The single circuit gives three filter functions, low pass, high pass and band pass. This filter circuit can be used for differentQ and _f0 with high passband gain. This gives better stop band attenuation and sharper cut-off at the edge of the passband.     

基于FIR 数字滤波器的扫描图像去网

针对扫描图像,提出了一种基于FIR 数字低通滤波器的去网方法,该方法是将图像从空间域转换到频率域,对频率域图像进行FIR 低通滤波处理,结合图像评价指标PSNR,选择最优的滤波器参数。用该去网算法与常用的去网算法进行了比较,结果表明,该去网算法在达到去网效果的同时能够更好地保留边缘信息。     

基于二维小波变换的爆堆矿岩边缘检测

根据爆堆图像灰度分布的特点,并结合小波变换应用于边缘检测的基本原理,采用能够检测局部突变能力的B样条小波用于爆堆岩石的边缘检测。通过推导,给出B样条小波滤波器,并根据滤波器设计出了基于二维小波边缘检测算法。在小波边缘分割中自主设计了自适应阈值检测算法,该算法能很好地去除图像的噪声,并保留了图像的边缘。     

矿山爆破质量定量评价系统研究

爆破块度是衡量爆破质量的重要指标,快速准确的评价系统建立是现代化矿山爆破精细管理的基本要求。对爆堆块度评价涉及的抽样、图像识别、质量转换、误差修正及分布函数等进行了系统地分析论证,形成了建立爆破块度定量评价体系的系统方法,并结合具体矿山爆破进行了验证。     

自然环境下路面裂缝的识别

论文提出了一种基于分数阶微分和图像形态学的路面裂缝检测算法。分数阶微分能有效增强信号中、高频部分,非线性保留信号的低频部分,通过构建分数阶微分掩模算子,增强裂缝信息特别是平滑区域中弱信号信息。利用图像形态学算子提取裂缝,通过组合中值滤波去除孤立噪声点。实验结果表明,该算法比传统算法能更有效地检测出细小裂缝信息,是一种具有较强鲁棒性且高效实用算法。     

基于核滤波器实时运动目标的抗遮挡再跟踪

相关滤波算法是通过模板与检测目标的相似性来确定目标位置,自从将相关滤波概念用于目标跟踪起便一直受到广泛的关注,而核相关滤波算法的提出更是将这一理念推到了一个新的高度。核相关滤波算法以其高速度、高精度以及高鲁棒性的特点迅速成为研究热点,但核相关滤波算法在抗遮挡性能上有着严重的缺陷。本文针对核相关滤波在抗遮挡性能上的缺陷对此算法进行改进,提出了一种融合Sobel边缘二元模式算法的改进KCF算法,通过Sobel边缘二元模式算法加权融合目标特征,然后计算目标的峰值响应强度旁瓣值比检测目标是否丢失,最后将Kalman算法作为目标遮挡后搜索目标的策略。结果显示,本文方法不仅对抗遮挡有较好的鲁棒性,而且能够满足实时要求,准确地对目标进行再跟踪。     

多阈值选取与边缘连接的边缘检测算法

论文针对Kirsch边缘检测算子的缺点,提出一种多阈值选取与改进的边缘连接算法相结合的方法,对图像,尤其是医学图像进行边缘检测。该方法首先用高斯滤波器对原始图像去噪,使用传统Kirsch算子计算梯度,然后设定低阈值和自适应阈值来保护图像弱边缘和提取真正边缘,最后通过改进的边缘连接算法连接边缘。实验结果表明,论文的方法具有保持弱边缘、连接性好的边缘检测效果。     

基于小波变换和形态学的织物疵点边缘检测

为了精确确定织物疵点边缘,提出了一种基于小波变换和形态学的织物疵点边缘检测方法.在利用形态学实现疵点检测后,对其进行小波分解,用小波模极大值法和基于数学形态学的算法分别提取高低频子图像的疵点边缘,采用合理的融合规则将两个边缘图像进行融合.实验结果表明,该算法能有效地抑制噪声,且边缘清晰、准确,效果优于经典的边缘检测算法,具有可行性和有效性.     

工程表面分数阶样条滤波分析法

将分数阶样条滤波器作为表面轮廓滤波器以获取表面中线。首先将分数阶样条函数与变分公式相结合,推导出分数阶样条滤波器系统函数。分析了该滤波器的幅度传输特性,其具有截止幅度可调性质。当样条阶次逐渐升高时,截止特性可接近理想低通滤波器,而当阶次r=1.51时,截止特性又可逼近于高斯滤波器,该特性极大地方便了样条滤波器的使用。给出了分数阶样条滤波器的快速FFT算法,由于该滤波算法只涉及频域内乘积,且运算数量有限,所以计算效率很高。最后对FFT算法产生边缘效应的原因进行了分析,并对边缘效应进行了修正。实验结果表明:该滤波器算法不但具有灵活可调的截止特性,而且计算速度快, 在通用计算机上完成一次11 200点表面中线的提取只需4 ms,同时有效抑制了样条滤波器的边缘效应。     

Fuzzy-rule-based image reconstruction for positron emission tomography

Positron emission tomography (PET) and single-photon emission computed tomography have revolutionized the field of medicine and biology. Penalized iterative algorithms based on maximum a posteriori (MAP) estimation eliminate noisy artifacts by utilizing available prior information in the reconstruction process but often result in a blurring effect. MAP-based algorithms fail to determine the density class in the reconstructed image and hence penalize the pixels irrespective of the density class. Reconstruction with better edge information is often difficult because prior knowledge is not taken into account. The recently introduced median-root-prior (MRP)-based algorithm preserves the edges, but a steplike streaking effect is observed in the reconstructed image, which is undesirable. A fuzzy approach is proposed for modeling the nature of interpixel interaction in order to build an artifact-free edge-preserving reconstruction. The proposed algorithm consists of two elementary steps: (1) edge detection, in which fuzzy-rule-based derivatives are used for the detection of edges in the nearest neighborhood window (which is equivalent to recognizing nearby density classes), and (2) fuzzy smoothing, in which penalization is performed only for those pixels for which no edge is detected in the nearest neighborhood. Both of these operations are carried out iteratively until the image converges. Analysis shows that the proposed fuzzy-rule-based reconstruction algorithm is capable of producing qualitatively better reconstructed images than those reconstructed by MAP and MR P algorithms. The reconstructed images a resharper, with small features being better resolved owing to the nature of the fuzzy potential function.     

A 3D Measurement Method Based on Coded Image

The binocular stereo vision system is often used to reconstruct 3D point clouds of an object. However, it is challenging to find effective matching points in two object images with similar color or less texture. This will lead to mismatching by using the stereo matching algorithm to calculate the disparity map. In this context, the object can’t be reconstructed precisely. As a countermeasure, this study proposes to combine the Gray code fringe projection with the binocular camera as well as to generate denser point clouds by projecting an active light source to increase the texture of the object, which greatly reduces the reconstruction error caused by the lack of texture. Due to the limitation of the camera viewing angle, a one-perspective binocular camera can only reconstruct the 2.5D model of an object. To obtain the 3D model of an object, point clouds obtained from multiple-view images are processed by coarse registration using the coarse SAC-IA algorithm and fine registration using the ICP algorithm, which is followed by voxel filtering fusion of the point cloud. To improve the reconstruction quality, a polarizer is mounted in front of the cameras to filter out the redundant reflected light. Eventually, the 3D model and the dimension of a vase are obtained after calibration.     

Parameter optimal determination for canny edge detection

Abstract

The Canny edge detection algorithm contains a number of adjustable parameters, which can affect the computation time and effectiveness of the algorithm. To overcome the shortages, this paper proposes a new way to determine the adjustable parameters and constructs a modified Canny edge detection algorithm. In the algorithm, an image is firstly smoothed by an adaptive filter that is selected based on the properties of the image, instead of a fixed sized Gaussian filter, and then, the high and low thresholds for the gradient magnitude image are determined based on maximum cross-entropy between inter-classes and Bayesian judgment theory, without any manual operation; finally, if it needs, the object closing procedure is carried out. To test and evaluate the algorithm, a number of different images are tested and analysed, and the test results are discussed. The experiments show that the studied algorithm can achieve the better edge detection results in most of the cases, and it is also useful for object boundary closing as a pre-segmentation step.     

基于频谱滤波的多纹理提取算法

研究了一种在有多种纹理叠加的复杂图像中进行单一纹理提取的算法.首先采用极坐标方法分析纹理频谱的环型和楔型特征并求出纹理分布的周期和方向特征;然后根据这些特征在频域中构建环型和楔型Gauss带通滤波器对纹理频谱进行滤波;再将滤波后的频谱图像转换到时域中就得到了只保留相应纹理成分的图像;最后经过纹理区域矫正处理后就可以提取出真实的纹理.实验结果表明,该方法可以准确提取出图像中叠加的多种纹理,并能完整保留每种纹理的基本特征,在纹理分布不均匀的区域也能提取出纹理的骨架.     

PSO-Gabor-CNN算法在印刷品套印缺陷的检测

目的二维Gabor滤波器含有多个参数,在印刷品套印缺陷检测中,二维Gabor滤波器使用不同参数增强图像特征的效果差别较大,为了获得二维Gabor在某印刷品套印缺陷检测下的优化参数。方法在印刷品套印缺陷检测中,提出一种PSO-Gabor-CNN算法,采用Sobel算子对印刷品图像进行边缘检测,以粒子群算法(PSO)对二维Gabor滤波器的中心最大频率kmax、带宽σ、模板窗口window进行参数寻优,处理后的图像与模板图像采用加权欧式距离进行评价。然后用优化后的Gabor滤波器对图像进行滤波,最后采用卷积神经网络(CNN)对印刷品套印缺陷进行检测和分类。结果通过粒子群算法,确定了二维Gabor中心最大频率kmax为6.0476、带宽σ为0.1444、模板窗口window为27×27取得最佳效果,此时加权欧式距离为1.1927×10-33。卷积神经网络经过70次训练的均方误差为0.0035,测试样本正确率为96.93%。该方法与无数据预处理的BP神经网络(BPNN)、Sobel预处理的BP神经网络(Sobel-BPNN)、无数据预处理的卷积神经网络(CNN)、Sobel预处理的卷积神经网络(Sobel-CNN)对比,表现出了较好的识别效果。结论该方法可以获取二维Gabor滤波器的较优参数,从而获得较好的滤波效果,将其应用于套印缺陷检测,具有一定的应用价值。     

基于Gabor滤波器的指纹图像增强

通过对传统指纹图像增强算法的研究,提出一种基于Gabor滤波的指纹图像增强算法。根据指纹纹线间距均匀且局部平行的特点,建立了用于指纹图像增强的Gabor滤波函数的物理模型,并利用二维Gabor滤波器可分解为正交方向的一维高斯带通滤波器和一维高斯低通滤波器的特点,将二维滤波分解为两次一维滤波,从而解决了计算量过大的问题,降低了算法的复杂度。实验表明该算法具有良好的增强指纹图像的脊线和抑制噪声的作用。