A MODIFIED DYNAMIC GENERALIZED HOUGHTRANSFORM FOR LINE DETECTING

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基于ZAM-GTFR和Hough Transform的LFM信号检测

对于诸如电子对抗、电子情报等领域,噪声环境下的未知参量信号检测是一个关键问题。本文提出了ZAM-GTFR结合霍夫变换对线性调频信号的一种新的检测方法。对于特定的复高斯白噪声环境下的线性调频信号,检测的过程等效于对ZAM-GTFR沿瞬时频率直线作积分,再用积分值与门限做比较。仿真结果证实了此检测方法的有效性。

基于改进随机Hough变换的圆形目标检测算法

圆形目标检测在各个领域得到了广泛应用.为了提高规则圆的检出效率、降低不规则圆的漏检率,文章提出了一种改进随机Hough变换的圆形目标检测算法.算法首先用区域增长和RGB二值分割等算法对不同背景的图像进行二值分割和去噪处理,接着对连通域分割的特征区域用具有圆形性特征的边缘点进行候选圆的检测和验证.实验对比结果表明,本文算法可以显著提高规则圆的检出效率、降低不规则圆的漏检率,算法计算量小、运行速度快、鲁棒性强.

基于优化Hough变换的铆接高度差亚像素检测方法研究

针对飞机铆接高度差的检测问题,提出了一种优化的Hough变换铆接高度差亚像素检测方法。该方法首先通过空间域点运算的灰度变换法对采集的铆接孔图像进行增强处理,然后利用局部阈值分割法进行图像分割,采用Canny算法进行边缘粗提取,再利用优化的Hough变换进行亚像素级的边缘精细提取,提取出铆接孔和铆钉钉头的圆环区域,最后结合RANSAC算法进行圆拟合,利用开发算子get_current_region_z()分别提取内外圆环区域的高度平均值,再通过函数height_Z()将所得的高度平均值作差即可得到铆接表面的高度差。经试验证明,该检测方法亚像素精确定位能力强,检测结果准确率高、稳定性好,重复测量精度可达到±10μm。

多角度探测模式下结合Hough变换与SVR的墙后目标定位算法

多普勒穿墙雷达在定位墙后目标时,存在以下两个难点:(1)准确获取频率混叠区域目标瞬时频率;(2)通过获取精确的墙体参数来减小墙体对定位造成的影响。针对以上问题该文提出了一种结合Hough变换和支持向量回归-BP神经网络的目标定位算法。该文首先设计了一种多视角融合穿墙目标探测模型框架,通过获取不同视角下的目标位置来提供辅助估计墙体参数信息;其次,结合差分进化算法和切比雪夫插值多项式提出了一种目标瞬时频率曲线的高精度提取和估计算法;最后,利用估计的墙体参数信息,提出了一种基于BP神经网络的目标运动轨迹补偿算法,抑制了障碍物对目标定位结果的扭曲影响,实现了对墙后目标的精确定位。实验结果表明,相较于传统的短时傅里叶方法,该文所述方法可以准确提取时频混叠区域的目标瞬时频率曲线并减小墙体造成的影响,从而实现墙后多目标的准确定位,整体定位精度提升了约85%。

基于改进HT-LCNN线段检测模型的隧洞施工活动时间信息智能提取方法

施工活动时间信息的有效提取是隧洞施工进度分析与决策的重要前提,目前常采用的一种隧洞施工活动时间记录方式是绘制横道图线段。针对传统依赖于人工统计的方式存在效率低、易出错等问题,提出基于改进深度霍夫线条先验网络(Hough Transform-Line Convolutional Neural Network,HT-LCNN)线段检测模型的隧洞施工活动时间信息智能提取方法。首先,采用单应性变换手段进行施工日志图像预处理,解决原始图像存在的倾斜、旋转、扭曲等问题;其次,利用全局上下文注意力模块(Global Context Network,GCNet)改进HT-LCNN模型的残差模块,通过建立和共享全局注意力图,获得目标线段在特征图和通道间的长距离依赖关系,提高模型对目标手绘线段的注意力,克服原有HT-LCNN方法容易受到表格线段和文字干扰的不足,实现手绘线段的高精度智能检测;进一步地,建立施工时刻-活动坐标系,根据所检测的手绘横道图线段的端点坐标位置特征,将其自动转化为施工活动时间信息。将该方法应用于某长距离引水隧洞TBM施工日志活动时间提取,本文提出的改进HT-LCNN模型的检测精度AP_(5)、AP_(10)、AP_(15)值分别为94.7%、95.0%、95.1%,均高于HT-LCNN和LCNN;基于本文方法自动提取的施工活动时间与人工提取结果相比,平均绝对误差仅为1.82 min。本研究为隧洞施工活动时间信息准确高效提取提供了新思路。

Lane Recognition Algorithm Using the Hough Transform Based on Complicated Conditions

At present, most lane line detection methods are aimed at simple road surface. There is still no good solution for the situation that the lane line contains arrow, text and other signs. The edge left by markers such as arrow and text will interfere with the detection of lane lines. In view of the situation of arrow mark and text mark interference between lane lines, the paper proposes a new processing algorithm. The algorithm consists of four parts, Gaussian blur, image graying processing, DLD-threshold (Dark-Light-Dark-threshold) algorithm, correlation filter edge extraction and Hough transform. Among them, the DLD-threshold algorithm and related filters are mainly used to remove the identification interference between lane lines. The test results on the Caltech Lanes dataset are given at the end of the article. The result of verification of this algorithm showed a max recognition rate of 97.2%.

Adaptive modified hough transform track initiator forHFSWR tracking of fast and small targets

High frequency surface wave radar (HFSWR) is well proved to have over the horizon (OTH) detection capability to weak aerial targets, such as concealed airplanes or cruise missiles. The most important problem of detection of fast and small targets using HFSWR is earlier warning, i.e. enlargement of detection range oftargets. Therefore, the detection threshold should be decreased as low as possible, but numerous false alarms are brought about at the same time. On this condition, conventional track initiation techniques, which normally require the probability of false alarm to be at the level of 10-6, will initiate enormous false tracks and lead to abnormal operation of tracking system. An adaptive modified hough transform (AMHT) track initiator is proposed accordingly and the relation of detection range to the performance of track initiator is analyzed in this paper. Simulations are performed to confirm the capability of track initiation to fast and small targets in dense clutter by AMHT track initiator. The tolerable probability of false alarm of detector can reach the level of 10 -3 . And it performs better than track initiator based on modified hough transform (MHT).

Detection of weak target for MIMO radar based on Hough transform

An effective method of multiple input multiple output （MIMO） radar weak target detection is proposed based on the Hough transform. The detection time duration is divided into multiple coherent processing intervals （CPIs）. Within each CPI, conventional methods such as fast Fourier transform （FFT） is exploit to coherent inte- grating in same range cell. Furthermore, noncoherent integration through several range cells can be implemented by Hough transform among all CPIs. Thus, higher integration gain can be obtained. Simulation results are also given to demonstrate that the detection performance of weak moving target can be dramatically improved.

Weld extraction from real-time radiograph based on bidirectional accumulator Hough Transform

An effective approach is presented to extract welds from real-time radiographs, Firstly an algorithm based on an adaptive bidirectional threshold was proposed to segment the gradient image into ternary image, and then the bidirectional accumulator Hough Transform was developed to extract weld edges from the ternary image. Different values of the coefficient proposed in the threshold algorithm were tested, and the proposed approach was applied to extract welds from real-time radiographic images of different types of welds with defects. Results show that the proposed method is adaptive and effective to extract welds from real-time radiographs of linear welds.

Machine vision inspection of rice seed based on Hough transform

A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.

Ensemble-based optimization of hydraulically fractured horizontal well placement in shale gas reservoir through Hough transform parameterization

Shale gas reservoirs have been successfully developed due to the advancement of the horizontal well drilling and multistage hydraulic fracturing techniques.However,the optimization design of the horizontal well drilling,hydraulic fracturing,and operational schedule is a challenging problem.An ensemble-based optimization method(EnOpt)is proposed here to optimize the design of the hydraulically fractured horizontal well in the shale gas reservoir.The objective is to maximize the net present value(NPV)which requires a simulation model to predict the cumulative shale gas production.To accurately describe the geometry of the hydraulic fractures,the embedded discrete fracture modeling method(EDFM)is used to construct the shale gas simulation model.The efects of gas absorption,Knudsen difusion,natural and hydraulic fractures,and gas-water two phase fow are considered in the shale gas production system.To improve the parameter continuity and Gaussianity required by the EnOpt method,the Hough transformation parameterization is used to characterize the horizontal well.The results show that the proposed method can efectively optimize the design parameters of the hydraulically fractured horizontal well,and the NPV can be improved greatly after optimization so that the design parameters can approach to their optimal values.

Feature Extraction of Symmetrical Triangular LFMCW Signal Using Wigner-Hough Transform

Feature extraction of symmetrical triangular linear frequency modulation continuous wave （LFM- CW） signal is studied. Combined with its peculiar charaeteristics, a novel algorithm based on Wigner-Hough transform （WHT） is presented for the deteetion and parameter estimation of this type of waveform. The initial frequency and chirp rate of each segment of this wave are estimated, and the peak-value searching steps in the parameter spaee is given. Compared with Wigner-Ville distribution （WVD）, Pseudo-Wigner-Ville distri- bution （PWD） and Smoothed-Peseudo-Wigner-Ville distribution （SPWD）, WHT has proven itself to be the best method for feature extraetion of symmetrical triangular LFMCW signal. In the end, Monte-Carlo simulations under different SNRs are earried out, with validating results on this method.

TRIPLET CIRCULAR HOUGH TRANSFORM FOR CIRCLE DETECTION

A new method, triplet circular Hough transform, is proposed for circle detection in image processing and pattern recognition. In the method, a curve in an image is first detected. Next, a sequence of three points on the curve are selected, a sequence of parameters (a,b,r) corresponding to the three points are calculated by solving the circle equation of the curve, and two 2-D accumulators A(a,b) and R(a,b) are accumulated with 1 and r, respectively. Then the parameters {(a, b, r)} of the circles fitting the curve are determined from A(a,b) and R(a,b) by searching for the local maximum over A(a,b). Because no computation loops over center (a, 6) and/or radius r are needed, the method is faster than the basic and directional gradient methods. It needs also much smaller memory for accumulation.

Local Spiral Curves Simulating Based on Hough Transformation and Center Auto-Locating of Developing Typhoon

In the developing phase of typhoon formation, the spiral belt partly emerges in satellite cloud images. This research starts from images and moves on to graphics and then to representation and recognition. Following this route, local spiral cloud belt is segmented from the raw images using image segmentation, the spiral information is extracted using mathematic morphology, and local spiral curves are detected using Hough transformation. The problem of center locating of developing typhoon has finally been solved through a search algorithm of spiral curve. For No. 99082008 cloud image, the result produced by the algorithm in this paper is at 122..3 degree west longitude, 117.5 degree north latitude. The real typhoon center location was at 122.4 degree west longitude, 18 degree north latitude.

Structural plane recognition from three-dimensional laser scanning points using an improved region-growing algorithm based on the robust randomized Hough transform

The staggered distribution of joints and fissures in space constitutes the weak part of any rock mass.The identification of rock mass structural planes and the extraction of characteristic parameters are the basis of rock-mass integrity evaluation,which is very important for analysis of slope stability.The laser scanning technique can be used to acquire the coordinate information pertaining to each point of the structural plane,but large amount of point cloud data,uneven density distribution,and noise point interference make the identification efficiency and accuracy of different types of structural planes limited by point cloud data analysis technology.A new point cloud identification and segmentation algorithm for rock mass structural surfaces is proposed.Based on the distribution states of the original point cloud in different neighborhoods in space,the point clouds are characterized by multi-dimensional eigenvalues and calculated by the robust randomized Hough transform(RRHT).The normal vector difference and the final eigenvalue are proposed for characteristic distinction,and the identification of rock mass structural surfaces is completed through regional growth,which strengthens the difference expression of point clouds.In addition,nearest Voxel downsampling is also introduced in the RRHT calculation,which further reduces the number of sources of neighborhood noises,thereby improving the accuracy and stability of the calculation.The advantages of the method have been verified by laboratory models.The results showed that the proposed method can better achieve the segmentation and statistics of structural planes with interfaces and sharp boundaries.The method works well in the identification of joints,fissures,and other structural planes on Mangshezhai slope in the Three Gorges Reservoir area,China.It can provide a stable and effective technique for the identification and segmentation of rock mass structural planes,which is beneficial in engineering practice.

基于改进Canny算法和Hough变换的脉冲氩弧焊坡口边缘提取研究

针对脉冲氩弧焊中被动光传感采集的图像存在光亮变换快,目标像素少,难以提取出坡口的问题,提出一种基于改进阈值选择和双阈值检测的Canny算法。通过中值滤波和双边滤波代替传统Canny算法中的高斯滤波对图像进行滤波,引入背景像素与前景像素的数量比改进Otsu算法的最大方差,计算得到了靠近坡口的梯度值的阈值,依据改进后的双阈值检测获得完整的坡口边缘信息,对边缘信息进行Hough变换提取出清晰的坡口边缘。实验结果表明,和传统Canny算法相比,改进后的Canny算法提取坡口成功率提高,获得的坡口边缘信息也更加完整。

基于改进Hough变换的消弧线圈接地配电网故障选线新方法

针对配电网在电压过零点和高阻故障时刻选线不准确的问题,提出一种适用于谐振接地系统单相接地故障的选线新方法,利用优化后的变分模态分解对各馈线零序功率进行处理,遴选出与原始零序功率相关强度最高的本征模态函数IMF(k),将IMF(k)转换为JPG格式的二维图像,再利用Hough变换检测技术,得到故障起始阶段IMF(k)的拟合直线及夹角;对各支路模态量拟合直线夹角进行比对处理,将最小综合相关系数值对应的馈线确定为故障馈线;仿真结果表明:该方法不受接地电阻、故障相角、噪声干扰、数据缺失等因素的影响,验证了所提方法的有效性。

Wigner-Hough transform based on slice's entropy and its application to multi-LFM signal detection

To enhance the capacity of the radar-reconnaissance interception receiver recognizing linear frequency modulated (LFM) at a low signal-noise ratio, this paper presents WignerHough transform (WHT) of the LFM signal and its corresponding characteristics, derives the probability density functions of the LFM signal and Gaussian white noise within WHT based on entropy (WHTE), dimension under different assumptions and puts forward a WHT algorithm based on entropy of slice to improve the capacity of detecting the LFM signal. Entropy of the WHT domain slice is adopted to assess the information size of polar radius or angle slice, which is converted into the weight factor to weight every slice. Double-deck weight is used to weaken the influences of noise and disturbance terms and WHTE treatment and signal detection procedure are also summarized. The rationality of the algorithm is demonstrated through theoretical analysis and formula derivation, the efficiency of the algorithm is verified by simulation comparison between WHT, fractional Fourier transform and periodic WHT, and it is highlighted that the WHTE algorithm has better detection accuracy and range of application against strong noise background.

THE COMBINED HOUGH TRANSFORM

On the basis of researching the generalized Hough transform and its im-provements,this paper presents a combined Hough transform(CHT)for recognizing arbi-trary shapes.The combined Hough transform introduces the idea of the adaptive Houghtransform(AHT)into the double Hough transform(DHT).It not only maintains the de-sirable features of the DHT,but also improves the speed of execution and resistanceagainst disturbance,and reduces the memory requirements greatly.The CHT canaccurately recognize objects,partially occluded in complex background.Therefore,it ispossible to implement the CHT in real-time application.