基于模糊随机广义霍夫变换的目标匹配

为了提高工业检测中图像匹配精度和速度,提出了一种用于二维目标匹配的新算法--模糊随机广义霍夫变换(FRGHT)。此算法结合了模糊推理系统(FIS)和随机广义霍夫变换(RGHT)。模糊推理系统引入模糊集合概念,计算待配准图像中边缘点对配准参数的投票,从而可以抑制噪声,解决扭曲问题,提高了匹配精度;随机抽取待配准图像中边缘点进行投票,实现了多对一的映射,从而减少了内存需求,提高计算速度。实验表明,该方法计算速度快,匹配精度高,不受噪声污染、扭曲、遮挡、混乱等情况的影响。     

局部PCA参数约束的Hough多椭圆分层检测算法

针对随机Hough变换(RHT)在复杂图像中检测圆及椭圆时随机采样所造成的大量无效采样、无效累积以及运算时间长等问题,提出基于局部PCA感兴趣参数约束Hough多椭圆分层检测思路。首先利用边缘检测算子获得边缘信息并去除边缘交叉点,在边缘图像中标记并提取出满足一定长度的连续曲线段;其次利用线段PCA方向分析确定是否属于有效曲线段;然后,对所有感兴趣曲线段按照标记顺序依次利用椭圆拟合办法初步得到感兴趣椭圆粗略参数,根据拟合结果进而模糊约束Hough变换参数搜索范围,得到精确椭圆参数;最后利用检测结果更新图像空间,删除已经检测到的椭圆,依次进行,直到所有椭圆检测完毕。实验结果表明,该算法在计算、存储消耗上均大大减少。     

Hough transform for feature detection in panoramic images

Omni-directional sensors are useful in obtaining a 360° field-of-view. With a radially symmetric mirror and conventional lens system this can be achieved with a single camera. There are several proposed profiles for the mirror, but most violate the single viewpoint (SVP) criteria necessary to allow functional equivalence to the standard perspective projection, posing challenges that have not yet been addressed in the literature. Such a imaging system with a non-SVP optical system do not benefit from the affine quality of straight line features being represented as collinear points in the image plane. To utilize these non-SVP mirrors, a new method to recognize such features is required. This work describes an approach to detecting features in panoramic non-SVP images using a modified Hough transform. A mathematical model for this feature extraction process is given. Experimental results are presented to validate this model and show robust performance in identifying line features with only estimated calibration.     

Analysis of textual images using the Hough transform

The analysis of images of printed pages of text is considered. Since printed text can be viewed as textured line, the use of the Hough transform for detecting straight lines is proposed as an analysis tool. Methods for handling several discretization problems that arise in mapping the rectangular image space to the (, ) accumulator array are described. Several applications of analyzing the accumulator array are proposed. They include detecting the text skew angle, determining the signature of a text line so as to accept or reject a block as containing only text, using profile analysis to segment text into lines, and determining whether a textual block is rightside-up or otherwise.     

检测井壁图像上平面地质特征的改进霍夫变换

为实现井壁图像上平面地质特征的自动提取,研究了图像中单周期正弦曲线的检测方法。提出一种改进的霍夫变换,该方法基于正弦曲线上的三个相关联点在二维累加器中进行投票,从而确定相位与基线深度;然后在一维累加器中投票,确定振幅。对模拟图像及井壁图像进行了处理,并与传统霍夫变换、快速霍夫变换进行了对比。结果表明,该方法不仅提高了检测速度,而且具有较高的准确率。     

Detection of circular geological features using the Hough transform

Abstract

The Hough transform is a technique commonly used in the field of computer vision for detecting linesand shapes in digital imagery. The application of this method to the detection of circular geological structures in Landsat MultispectralScannerimageryis described. The method wassuccessful in identifying most of those features apparent to the human analyst, in addition to a number of errors of commission. It is proposed that the error rate is tolerable for this particular application.     

一种基于Hough变换的文档图像倾斜纠正方法

在对文本扫描输入的过程中,文本图像不可避免地会发生倾斜,倾斜校正将为图文分割、文字识别等后续处理工作创造良好的条件。提出了一种基于Hough变换的检测图像倾斜度的方法,为了克服Hough变换计算量大的缺点,该方法首先选取局部代表性子区域并提取其图像水平边缘,然后对提取的水平边缘进行两级Hough变换,从而实现了准确性与快速性的很好结合。     

Accurate and efficient curve detection in images: the importance sampling Hough transform

The Hough transform is a well known technique for detecting parametric curves in images. We place a particular group of Hough transforms, the probabilistic Hough transforms, in the framework of importance sampling. This framework suggests a way in which probabilistic Hough transforms can be improved: by specifying a target distribution and weighting the sampled parameters accordingly to make identification of curves easier. We investigate the use of clustering techniques to simultaneously identify multiple curves in the image. We also use probabilistic arguments to develop stopping conditions for the algorithm. Results from applying our method and two popular versions of the Hough transform to both simulated and real data are shown.     

Tool wear monitoring using a fast Hough transform of images of machined surfaces

The texture of machined surfaces provides reliable information regarding the extent of tool wear. In this paper, we propose a structure-based approach to analyzing machined surfaces. The original surface images are first preprocessed by a Canny edge detector. A new connectivity-oriented fast Hough transform is then applied to the edge image to detect all the line segments. The distributions of the orientations and lengths of the line segments are used to determine tool wear. Through our experiments, we found a strong correlation between tool wear and features. The computational complexity of the fast Hough transform is also analyzed.Received: 6 November 2002, Accepted: 18 December 2003, Published online: 13 May 2004 Correspondence to: A.A. Kassim     

基于Hough圆卷积变换的孔组检测

为降低孔组测量的成本,提高测量的精确度,提出一种基于Hough国卷积的孔组检测方法.对孔组图像进行中值滤波、拉普拉斯锐化增强和边缘检测;根据孔组半径大小的变化范围,对Hough圆锥进行改进;在此基础上,利用改进的Hough圆锥与边缘检测后的图像进行三维卷积,得到Hough参数空间,计算出孔组的坐标和半径值;采用快速傅立叶变换法代替三维卷积,减少算法的计算时间.实验结果表明,该方法的检测精度高、实时性强,可以用于孔组的自动化检测.     

基于改进Hough变换的文本图像倾斜校正方法

文本图像在扫描输入时产生的倾斜现象会对后续的页面分割及光学字符识别（OCR）处理产生很大的影响，而传统的标准Hough变换虽然具有对噪声不敏感，不依赖于直线连续性的优点，但由于计算量偏大，速度慢，在实用时有较大的局限性。提出一种基于改进的Hough变换的文本图像倾斜校正方法，通过在变分辨率图像中采用不同的文本方向提取算法，及选择合理投票门限等改进Hough变换的措施，减小了由图像区域及文字笔画粗细所产生的对倾角判定的不利影响，并使用基于偏移值的方法实现页面倾斜的快速校正。实验结果表明，该算法实现了大范围高精度的文本图像倾角的快速检测，具有较强的实用性。     

Application of the Hough transform to correct for linear variation of background illumination in images

The Hough transform has been formulated to detect areas of linear brightness variation within an image. The formulation leads to significant computational advantage involving a restricted parameter search space. Two applications are included to demonstrate the efficacy of this technique.     

Optimising the application of the Hough transform for automatic feature extraction from geoscientific images

We have adapted the Hough transform to extract linear features successfully from geoscientific datasets. The Hough transform is used in an automatic technique, which makes use of a parameter space to describe features of interest in images. This method has been widely applied in machine vision for recognition of features in highly structured images. Geoscientific data is more demanding. Features of interest within scenes of natural environments exist on all scales, are often partially obscured and the images are usually noisy. Pre-processing of images before the HT is essential. Adaptations of the HT to cope with particular properties of geoscientific data include: optimising the dimensions of the discrete transform domain; using feature-modelling to cancel lines found; transforming multi-scale tiles of the original image and correcting amplitudes in the transformed domain to account for the position of features. These specific adaptations produce a method for automatic feature detection which requires the user to select only two parameters. Output of the procedure is rich in feature content and accurate, leaving a clean result for statistical analysis. This optimised HT is robust for natural scenes, coping in particular with short line-segments.     

Detection of linear and planar structures in 3D subsurface images by iterative dimension reduction

A unified framework for detecting both linear and planar structures in three-dimensional (3D) images is developed. The method uses an iterative detection and removal strategy. The dimension reduction scheme reduces the search space for lines by first finding 2D planes and then searching for lines in the selected planes only. Thus the computational time of the method is lower than the 3D Hough Transform (HT) for lines. The proposed method is tested using experimental Ground Penetrating Radar (GPR) data taken over buried pipes, however the method is general enough to be applied to any situation where linear or planar structures need to be identified in 3D data.     

Location of pupil contour by Hough transform of connectivity components

A method for determining the pupil boundary in the image of eye is proposed. The method is based on image binarization followed by a search of the pupil as one of the connectivity components. The pupil boundary is determined as a part of boundary of the connectivity component. Hough transform is used for separating pupil in the case of its merging in one connectivity component with other objects, as well as to verify the likelihood of solution.     

FFT和Hough变换在织物纹理方向检测上的应用

针对人工测量织物纹理方向的方法存在自动化程度低、精度不高的缺点,提出基于快速傅里叶变换和Hough变换的自动检测和识别织物经向、纬向、斜纹斜向的方法。对织物图像进行二值化处理,对二值化后的织物图像进行快速傅里叶变换得到功率谱图,对功率谱图的二值图像进行Hough变换,从而检测出织物纹理方向。通过对同一试样的不同放置方式进行测试,证明该方法对织物放置方式无特殊要求,仅需确保试样平摊在光滑台面上不受任何张力;将该方法与人工测试结果作对比,证明该方法具有高精度、高自动化的优点。     

随机噪声干扰下的迭代学习控制器设计

为解决迭代学习控制系统中随机噪声扰动问题,提出基于无限脉冲响应（ⅡR）数字滤波器的优化迭代学习控制器设计方法。该方法在首次迭代时对系统输出误差进行基于小波变换的两轮实验法滤波;其次根据小波滤波获得的输出误差确定部分及原误差信号作为输入输出辨识出等效ⅡR线性滤波器,并重构优化误差目标函数,进一步利用优化方法对迭代学习控制器优化设计;最后利用获得的线性滤波器及新学习律对系统进行后续批次迭代,直到满足收敛条件为止。仿真显示：在针对输出误差二范数这个性能指标,该方法与小波滤波相比,降低了近15%,并消除了由于小波滤波阈值选取过小产生的振铃现象;在批次间噪声累积上,降低了9%左右。仿真结果表明,提出的等效滤波器综合设计方法,有效抑制了随机噪声的影响,并提高了系统跟踪的准确性。     

Efficient pan-sharpening of satellite images with the contourlet transform

Recent studies show that hybrid panchromatic sharpening (pan-sharpening) methods using the non-sub-sampled contourlet transform (NSCT) and classical pan-sharpening methods such as intensity, hue and saturation (IHS), principal component analysis (PCA), and adaptive principal component analysis (APCA) reduce spectral distortion in pan-sharpened images. The NSCT is a shift-invariant multi-resolution decomposition. It is based on non-sub-sampled pyramid (NSP) decomposition and non-sub-sampled directional filter banks (NSDFBs). We compare the performance of the APCA–NSCT using different NSP filters, NSDFB filters, number of decomposition levels, and number of orientations in each level on SPOT 4 data with a spatial resolution ratio of 1:2, and Quickbird data with a spatial resolution ratio of 1:4. Experimental results show that the quality of pan-sharpening of remote-sensing images of different spatial resolution ratios using the APCA–NSCT method is affected by NSCT parameters. For the NSP, the ‘maxflat’ filters have the best quality, while the ‘sk’ filters give the best quality for the NSDFB. Changing the number of orientations at the same level of decomposition in the NSCT has a small effect on both the spectral and spatial qualities. The spectral and spatial qualities of pan-sharpened images mainly depend on the number of decomposition levels. Too few decomposition levels result in poor spatial quality, while excessive levels of decomposition result in poor spectral quality. Two levels of decomposition in the case of SPOT 4 data with a spatial resolution ratio of 1:2 achieve the best results. Also, three levels of decomposition in the case of QuickBird data with a spatial resolution ratio of 1:4 show the best results.     

Enclosing the solution set of linear systems with inaccurate data by iterative methods based on incomplete LU-decompositions

We present a class of iterative methods to enclose the solution set by an interval vector;A is varying in ann×n intervalH-Matrix andb is varying in an interval vector . The algorithm taken into consideration generalizes an iterative method of Meijerink/van der Vorst based on an incompleteLU-decomposition of anM-MatrixA. Theorems concerning the feasibility of the algorithm, its rate of convergence and its quality of enclosure are given. Since the original method of Meijerink/van der Vorst is a special case of our algorithm we have thus shown its applicability to the larger class ofH-matrices. Furthermore we relate theR ₁-factor (as defined in Ortega/Rheinboldt [9]) of the original method to the underlying setP of indices.