几种自适应IIR陷波器的复数算法及其应用

在自适应IIR陷波器实数算法的基础上,本文提出了三种基于梯度的自适应IIR陷波器的复数算法,并进行了仿真比较。结果表明,这三种复数算法均可检测复信号,并估计信号频率,其中"改进的"简化格型IIR陷波器复数算法收敛速度快、低信噪比下稳定性能好。湖上试验表明该算法不仅实时性好,而且在低信噪比下的检测效果令人满意。     

基于切比雪夫多项式描述子的复杂背景下输电线路提取算法

在电力系统中,利用计算机视觉和图像处理技术对输电线路的进行检测,在保障电力系统的安全运行方面具有非常重要的作用；针对复杂背景下的输电线路,提出了一种基于切比雪夫多项式描述子输电线路提取算法,该算法首先对输入图像进行预处理,其次利用随机Hough 变换提取图像中的直线和曲线,然后利用切比雪夫多项式描述子的曲线描述优势,对所提取的对象进行特征描述,为了提高提取的精确度,通过K-means聚类分析方法来训练视觉字典,通过视觉字典的比对,最终确定图像中的输电线路；实验结果说明了所提出的算法可以精确地提取复杂背景下的输电线路。     

无人机对地目标自动检测与跟踪技术

针对无人机图像帧序列具有平台高速运动,视角旋转强烈,需要实时处理等特点,提出一种基于双级旋转不变特征空间检测（粗匹配-精细匹配）与并行特征提取跟踪的无人机对地目标图像帧序列自动快速目标检测与跟踪算法。采用图像子块的平均灰度值、灰度值方差、灰度值梯度构建特征空间。通过构造图像特征空间的方法来快速筛选待匹配图像的可疑区域,删除大量的背景区域,检测算法使用全局初步匹配加局部精细匹配的方法来规避算法复杂度的缺陷。理论及实验分析表明:该算法实时性强,对图像的旋转畸变具有抵消作用,对异常情况可以恰当处理,且全局初步匹配流程具有可移植性,可以在其他图像匹配跟踪算法中充当预处理器。实验结果表明:该算法在无人机对地的情况下可以保证对地面目标的稳定跟踪,配套检测算法具有较好的实时性,满足无人机图像目标检测跟踪实时处理的需要。     

基于脉冲耦合神经网络的弹簧卡箍缺陷检测

传统的弹簧卡箍缺陷多为产后人工全检,存在漏检与缺陷率上升等现象,这不但会使成本上升、也对人力资源提出了考验。为此实现自动实时在线全检就成为急需解决的课题,设计了基于机器视觉的弹簧卡箍在线自动检测系统,该系统安装在弹簧卡箍流水线两侧,搭建特定光源,通过激光传感器外部触发工业相机对其表面进行图像捕获,送上位机进行缺陷判定与定位,最后通过RS485将判定结果送下位机来控制剔除机制。实验结果显示：该系统采用改进的脉冲神经网络(PCNN)能准确提取目标缺陷区域并对缺陷进行判定,可在0.348 s每个零件的速度下,检测出弹簧卡箍表面大于10像素的缺陷。通过对不同弹簧卡箍进行检测验证实验,证明了PCNN算法对缺陷分割的准确性和有效性。     

Efficient Algorithm for Generating Maxwell Random Variables

A fast, easily implemented and high efficiency algorithm is derived for sampling from the Maxwell distribution. The algorithm is derived from the rejection-acceptance sampling method using the simple exponential decay function as an envelope function for the Maxwell distribution. The derived algorithm requires less number of random numbers per iteration, consumes less number of random numbers per sample and requires less expensive computation functions than the direct and Johnk’s algorithms. The speed of the proposed algorithm is about 1.6 times that of the direct algorithm and is about 1.5 times that of Johnk’s algorithm. Since the proposed algorithm for sampling from Maxwell distribution verified high efficiency and speed, Watt random variables can be generated by transforming Maxwell random variables generated by the proposed algorithm. The speed of generating Watt random variables using the proposed algorithm is about 1.1 times that generated from Kalos’s algorithm.     

Advanced iterative algorithm for phase extraction of randomly phase-shifted interferograms

An advanced random phase-shifting algorithm to extract phase distributions from randomly phase-shifted interferograms is proposed. The algorithm is based on a least-squares iterative procedure, but it copes with the limitation of the existing iterative algorithms by separating a frame-to-frame iteration from a pixel-to-pixel iteration. The algorithm provides stable convergence and accurate phase extraction with as few as three interferograms, even when the phase shifts are completely random. The algorithm is simple, fast, and fully automatic. A computer simulation is conducted to prove the concept.     

适合于生物图像的图像融合算法研究

图像融合作为一种有效的信息融合的技术,已广泛用于军事、遥感、机器视觉和医学图像等领域。本文讨论了三种基于像素级的图像融合算法：Ｐ加权平均,Ｔｏｅｔ算法和基于小波变换的算法;采用四种评价融合效果的量化判据：标准偏差,平均误差,峰值信噪比（ｓ／Ｎ）ｐ和熵差,将三种图像融合算法用于生物图像中细胞荧光图像和透射图像的融合,量化评价结果和视觉判断均说明,对于以细胞荧光图像和透射图像研究对象,需突出荧光图像的     

Parallel computing for fringe pattern processing: A multicore CPU approach in MATLAB environment

In the process of measurements such as optical interferometry and fringe projection, an important stage is fringe pattern analysis. Many advanced fringe analysis algorithms have been proposed including regularized phase tracking (RPT), partial differential equation based methods, wavelet transform, Wigner–Ville distribution, and windowed Fourier transform. However, most of those algorithms are computationally expensive. MATLAB^® is a general algorithm development environment with powerful image processing and other supporting toolboxes. It is also commonly used in photomechanical data analysis. With rapid development of multicore CPU technique, using multicore computer and MATLAB^® is an intuitive and simple way to speed up the algorithms for fringe pattern analysis. The paper introduces two acceleration approaches for fringe pattern processing. The first approach is task parallelism using multicore computer and MATLAB^® parallel computing toolbox. Since some algorithms are embarrassing problems, our first approach makes use of this characteristic to parallelize these algorithms. For this approach, parallelized windowed Fourier filtering (WFF) algorithm serves as an example to show how parallel computing toolbox accelerates the algorithm. Second, data parallelism using multicore computer and MATLAB^® parallel computing toolbox is proposed. A high level parallel wrapping structure is designed, which can be used for speeding up any local processing algorithms. WFF, windowed Fourier ridges (WFR), and median filter are used as examples to illustrate the speedup. At last, the results show that the parallel versions of former sequential algorithm with simple modifications achieve the speedup up to 6.6 times.     

二分法优化计算LED光源相关色温

色温和相关色温是LED光源的重要参量.从原始光谱数据到色品坐标(u,v)再到色温和相关色温的计算过程相当复杂,需要一种优化算法来简化计算量.因此,从色温的色度学定义出发,简要分析了直接内插法、逐点法和甬数曲线拟合法三种色温计算的经典算法,并分别指出了它们的优缺点,在此基础上提出了二分法这种新的色温优化算法.详细介绍了二分法的基本思想、程序流程等.利用软件编程实现这几种算法,通过普朗克黑体辐射公式计算得到一系列色温的理论光谱和白光LED仪器实际测试光谱,对比二分法和各种经典算法的速度和结果,证明了二分法是一种适合于计算机程序化实现的高精度高速度的色温算法.     

三目自适应权值立体匹配和视差校准算法

立体匹配是计算机视觉研究中的关键问题.相比于双目视觉,三目视觉能够获得更多的信息和额外的极线约束消除立体匹配的歧义性.为了提高三目立体匹配的精度,提出一种基于自适应权值和视差校准的三日立体匹配方法.将双目视觉中有效的自适应权值窗选择算法应用到三目视觉中,进行匹配窗的选择;提出一种新的目标图像选择算法,能够合理利用平行基线三目立体视觉系统中不同目标图像提供的信息,有效地消除遮挡,提高匹配的精度;提出一种适用于三目视觉的视差校准算法,利用三目图像像素间的色彩相似性和距离约束将初始匹配的视差结果进行校准,得到最终的视差图.实验结果表明,本文算法结构简单,能够生成浓密、高精度的视差图.     

A universal algorithm to generate pseudo-random numbers based on uniform mapping as homeomorphism

A specific uniform map is constructed as a homeomorphism mapping chaotic time series into [0,1] to obtain sequences of standard uniform distribution. With the uniform map, a chaotic orbit and a sequence orbit obtained are topologically equivalent to each other so the map can preserve the most dynamic properties of chaotic systems such as permutation entropy. Based on the uniform map, a universal algorithm to generate pseudo random numbers is proposed and the pseudo random series is tested to follow the standard 0-1 random distribution both theoretically and experimentally. The algorithm is not complex, which does not impose high requirement on computer hard ware and thus computation speed is fast. The method not only extends the parameter spaces but also avoids the drawback of small function space caused by constraints on chaotic maps used to generate pseudo random numbers. The algorithm can be applied to any chaotic system and can produce pseudo random sequence of high quality, thus can be a good universal pseudo random number generator.     

基于特征面片的复杂型面轮廓视觉测量方法

提出一种基于特征面片的复杂型面轮廓三维视觉测量方法.该方法包括多模式局部特征检测与匹配、特征面片集初始化、膨胀、滤波等重构过程,其输入是已标定的立体图像,输出是覆盖表面的可视稠密面片集.该方法不需要目标和场景的任何初始边界信息,能够自动检测和抛弃外部点和缺失部分;不需要对邻域特征进行任何平滑处理,仅需通过局部单演特征一...     

A Hybrid Quantum Image-Matching Algorithm

Image matching is an important research topic in computer vision and image processing. However, existing quantum algorithms mainly focus on accurate matching between template pixels, and are not robust to changes in image location and scale. In addition, the similarity calculation of the matching process is a fundamentally important issue. Therefore, this paper proposes a hybrid quantum algorithm, which uses the robustness of SIFT (scale-invariant feature transform) to extract image features, and combines the advantages of quantum exponential storage and parallel computing to represent data and calculate feature similarity. Finally, the quantum amplitude estimation is used to extract the measurement results and realize the quadratic acceleration of calculation. The experimental results show that the matching effect of this algorithm is better than the existing classical architecture. Our hybrid algorithm broadens the application scope and field of quantum computing in image processing.     

光学小波变换在视觉系统的应用研究

为了提高图像信息处理速度,利用光电混合实现的方法,将光学小波变换应用于视觉系统设计.依据4f相关器光学信息处理的原理,在频域内通过计算机编码,在电寻址空间光调制器上,构建不同类型的小波函数滤波器库,对目标的图像特征进行提取与辨识.研究结果表明,基于光学小波变换视觉系统正确可行.在图像特征提取中,以光波传递信息可以提高视觉信息处理的速度.     

一种应用于大范围视觉测量的二维卷积光重心法

机器视觉由于具有非接触、可视化好、自动化和智能性高等优点,在航空航天、国防、工业现场等重要领域得到广泛的应用,其特征点的检测精度会大大影响视觉测量的精度。在研究视觉测量的光点中心提取技术的过程中,提出二维卷积光重心法,可有效地抑制光点边缘对光点中心位置的影响,大大地提高了光点中心的提取精度,既可以应用于发光特征点的提取,也可以应用于反光特征点的提取。利用该方法提取空间特征点进行三维重构的精度也比其他方法要高,能达到10^-4左右,基本满足工程测量的要求。     

基于序列图像的运动目标实时检测方法

运动目标检测是当前进行图像分析和理解以及在计算机视觉领域研究的热点,它被广泛地应用于靶场测量、目标监视、视频压缩、车辆跟踪和航空航天等领域。在参考大量文献资料的基础上,系统研究了近年来国内外已经比较成熟的一些算法,并把它们分成了7类。     

Static and dynamic routing and wavelength assignment algorithms for future transport networks

In this paper, two static and three dynamic routing algorithms have been proposed and compared to some of the existing algorithms on the basis of blocking probability. The two proposed static routing and wavelength assignment (RWA) algorithms reduce the blocking probability to maximize the utilization of network. For dynamic algorithms, first a model with no weights assignments is presented and then three algorithms are proposed and analysed with weight assignment resulting in reduction of blocking probability. All these algorithms are analysed and compared with four wavelength assignment schemes which are first-fit, random, most used and least used. It is shown that our proposed static algorithms give the best performance for first-fit wavelength assignment and most used wavelength assignment strategies with reduced complexity. For least used wavelength assignment and random wavelength assignment, 1 fixed and 2 alternate routing algorithm gives the lowest blocking probability. For dynamic routing, it has been shown that our proposed algorithm “less weight to maximum empty and nearest” gives the least blocking probability as compared to the other dynamic routing algorithms for random, most used and least used wavelength assignment strategies.     

Efficient randomized Hough transform for circle detection using novel probability sampling and feature points

This paper presents an efficient randomized Hough transform algorithm for circle detection. It optimizes the methods for determining sample points and finding candidate circles. Due to these two optimizations, sampling validity is improved and many false circles are prevented from being regarded as candidate circles. Experimental results demonstrate that the proposed algorithm, which features a strong robustness and high resolution, can dramatically speed up circle detection as compared to other algorithms. It can also be applied to detect ellipses.     

近邻点一致性的随机抽样一致性算法

 随机抽样一致性算法是计算机视觉领域中应用广泛的多视几何图像参数估计方法之一。为提高在高噪声条件下原算法计算效率,提出基于匹配点对邻近点集合一致性的过滤方法,可提高原初始匹配点对集合的内点比例,减少使用RANSAC时寻找参数时的抽样次数。宽基线图像极线几何计算的多组实验表明：提出的算法能够保持与原RANSAC一致的结果,并有效地提高计算速度。     

Image segmentation using adaptive loopy belief propagation

Loopy belief propagation (LBP) algorithm over pairwise-connected Markov random fields (MRFs) has become widely used for low-level vision problems. However, Pairwise MRF is often insufficient to capture the statistics of natural images well, and LBP is still extremely slow for application on an MRF with large discrete label space. To solve these problems, the present study proposes a new segmentation algorithm based on adaptive LBP. The proposed algorithm utilizes local region information to construct a local region model, as well as a local interaction region MRF model for image segmentation. The adaptive LBP algorithm maximizes the global probability of the proposed MRF model, which employs two very important strategies, namely, “message self-convergence” and “adaptive label pruning”. Message self-convergence can improve the reliability of a pixel in choosing a label in local region, and label pruning can dismiss impossible labels for every pixel. Thus, the most reliable information messages transfer through the LBP algorithm. The experimental results show that the proposed algorithm not only obtains more accurate segmentation results but also greater speed.