基于Hough变换的圆检测方法

总结了圆检测的几种常用方法,如经典HT、随机HT和广义HT.结合几种方法的优缺点,提出了一种基于经典HT的改进Hough变换圆检测方法.该方法先对图像进行预处理,如灰度化、去噪滤波、边缘检测以及运用数学形态学等,然后进行Hough变换.其主要思想是用多维数组来代替经典的循环过程.把Hough变换应用到织物防水性能自动测试的真实图像中,通过对经典Hough变换与改进后的Hough变换的比较,可以看出检测速度有所提高,检测精度也达到了令人满意的程度.     

Randomized or probabilistic Hough transform: unified performance evaluation

Rapid computation of the Hough transform is necessary in very many computer vision applications. One of the major approaches for fast Hough transform computation is based on the use of a small random sample of the data set rather than the full set. Two different algorithms within this family are the randomized Hough transform (RHT) and the probabilistic Hough transform (PHT). There have been contradictory views on the relative merits and drawbacks of the RHT and the PHT. In this paper, a unified theoretical framework for analyzing the RHT and the PHT is established. The performance of the two algorithms is characterized both theoretically and experimentally. Clear guidelines for selecting the algorithm that is most suitable for a given application are provided. We show that, when considering the basic algorithms, the RHT is better suited for the analysis of high quality low noise edge images, while for the analysis of noisy low quality images the PHT should be selected.     

The 3-D Hough shape transform

The 3-D Hough shape transform is described which is used for the localization in space of 3-D objects defined in terms of the spatial organization of their features.     

An unsupervised generalized Hough transform for natural shapes

The Hough transform was originally designed to recognize artifical objects in images. A Hough transform for natural shapes (HTNS) was subsequently proposed, but necessitates the supervised learning of the class of shapes. Here, we extend HTNS to unsupervised pattern recognition, the variability of the object class being coded with tools originating from mathematical morphology (erosion, dilation and distance functions).     

用两步Hough变换检测圆

Hough变换在图像处理中占有重要地位,是一种检测曲线的有效方法。但使用传统的Hough变换来检测圆,具有存储空间大计算时间长的缺点。为此提出了采用两步Hough变换的圆检测方法,利用圆的斜率特性,降低了Hough参数空间的维度,提高了运算效率,并推广到椭圆的检测之中。     

Lead-lag compensator design by the Hough transform

The frequency response of a compensator can be expressed as a curve in the complex plane. The Hough transform is very useful in finding a mathematical model which matches the curve in a plane very well. We combine these concepts to generate a new method of compensator design. Two examples are illustrated to explain the design procedure and results.     

Discretization errors in the Hough transform

Straight line-segments in a two-dimensional image can be detected with the Hough transform by searching peaks in a parameter space. The influence on the Hough transform of the quantization of the parameter space, the quantization of the image and the width of the line-segment is investigated in this paper.

The Hough transform was improved by O'Gorman and Clowes by taking into account the gradient direction. The resulting scatter of the peaks can be reduced by using a weighting function in the transform. Examples of asbestos preparations are given.     

基于Hough变换的煤岩界面识别方案

根据煤层与岩石层分界明显且呈线状的煤岩图像特征,提出一种基于Hough变换的煤岩界面识别方案。首先对煤岩图像进行去噪与增强预处理,然后去除煤与岩石边缘的孤立点与虚假边缘,最后采用Hough变换识别煤岩分界线。实验结果表明,该方案能够较快、较准确地检测出煤岩分界线。     

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.     

Extended Hough transform for linear feature detection

Improving the accuracy of line segment detection reduces the complexity of subsequent high-level processing common in cartographic feature detection. We developed a new extension to the Hough transform and reported on its application to building extraction. We expanded the Hough space by a third parameter, the horizontal or vertical coordinate of the image space, to provide incremental information as to the length of the lineal feature being sought. Using this extended HT transform allowed us to more accurately detect the true length of a line segment. In addition, we used a Bayesian probabilistic approach to process our extended Hough space that further increased the accuracy of our extended Hough transform.     

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.     

Estimation of complex multimodal motion: an approach based on robust statistics and Hough transform

An application of robust statistics in a Hough transform based motion estimation approach is presented. The algorithm is developed and experiments are performed, proving its superior performance in terms of estimate accuracy, convergence, robustness and better segmentation. Comparative results with standard methods are also included.     

基于HPF和Hough变换的人眼精确定位

眼睛定位是人脸识别的非常重要的一个环节,常采用基于Hough变换的方法,但这种方法计算量大、运算速度慢,对存储空间需求大。提出一种人眼快速定位的新方法。首先用混合投影法检测到眼睛瞳孔的大致位置,再利用基于圆的Hough变换快速定位出人眼,实验证明此方法大大提高了人眼定位的效率。     

并行Hough变换快速航迹起始

Hough变换在航迹起始领域得到广泛应用,但在扫描次数较少时起始效果不佳。通过转变Hough变换处理结构和改变计数器累加方式,提出了一种并行Hough变换快速航迹起始算法。利用Hough变换将不同时刻的量测集合分别映射到参数空间,继而将空间中具有相同索引的各次累加结果构成累加向量,统计其非零元素的个数,如大于预先设定的门限,则用向量各元素求和作为累加结果,否则置零。将利用该方法获得最终的累加结果进行门限检测来确定是否起始航迹。仿真实验表明,该算法可在密集环境下快速准确地起始航迹。     

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.     

一种面向FPGA的快速Hough变换

在FPGA上设计并实现了一种用于直线检测的快速Hough变换方法。使用分类滤波器把直线目标分成多个方向,使多个方向上的运算在空间上实现了并行处理;在每个方向上,设计实现了一种用于Hough变换的流水线处理结构;提出了一种基于直方图统计的两阶段搜索算法。大量的实验验证了提出的Hough变换实现方法的可行性,结果证明该方法占用空间少,实时性高。     

Geometrically invariant watermarking: synchronization through circular Hough transform

This paper addresses a geometrically invariant watermarking method for digital images. Most previous watermarking algorithms perform weakly against geometric distortions, which desynchronize the location for the inserted watermark. Watermark synchronization, which is a process for finding the location for watermark insertion and detection, is crucial for robust watermarking. In this paper, we propose a watermarking method that is robust to geometric distortions. In order to synchronize the location for watermark insertion and detection, we use circular Hough transform, which extracts circular features that are invariant to geometric distortions. The circular features are then watermarked using additive way on the spatial domain. Our method belongs to the category of blind watermarking techniques, because we do not need the original image during detection. Experimental results support the contention that our method is useful and considerably robust against both geometric distortion attacks and signal processing attacks as listed in Stirmark 3.1.

A New Definition of the Hough Transform

This paper‘s main contributions are three-fold.Firstly,it is shown that the two existing template matching-like definitions of the Hough transform in the literature are inadequate.Secondly,an inherent probabilistic aspect of the Hough transform embedded in the transformation process from image space to parameter space is clarified.Thirdly,a new definition of the Hough transform is proposed which takes into account both the intersection scheme between the mapping curve(or mapping surface) and accumulator cells and the inherent probabilistic characteristics.     

基于骨骼特征Hough变换的行为识别研究

为有效地表征人体行为的时空特征,将骨骼特征通过Hough变换后建立人体的动作表示.具体来说,采用OpenPose获取视频帧人体骨骼关键点,之后构建骨骼关节并映射到Hough空间,将骨骼关节轨迹转换为点迹,然后角度和轨迹特征的FV(Fisher vector)编码融合作为线性SVM分类器的输入.在经典公共数据集KTH、Weizmann、KARD和Drone-Action上,实验结果表明Hough变换提升了特征的鲁棒性,提高了人体行为识别的性能.     

基于Hough变换的时频盲源分离算法

1998年,Belouchrani,A和Amin,M.G基于时频分布提出了一种经典的时频盲源算法,不足是当有噪声存在时,性能会下降。主要考虑源噪声的盲源分离问题,以Wigner分布计算观测信号的时频阵并将其看做图像,利用Hough变换将信号检测转换为在参数空间寻找局部极大值的问题,运用自项点理论选择合适的矩阵进行联合近似对角化估计源信号。该方法扩展了盲源分离的限制条件,且通过把噪声能量扩展到整个参数平面而只选择信号能量占主导的时频点,对噪声具有一定的抑制能力。