SLEE算法与Hough圆拟合在香烟小包拉线错牙检测中的研究

针对香烟生产中广泛存在的小包拉线错牙问题,提出一种基于图形识别的检测方法;利用图像校正、平滑滤波、迭代阈值分割、边缘提取对拉线图像进行预处理,再采用随机霍夫变换(RHT)对两个拉线U型切口进行圆拟合,进而根据两个圆心在垂直方向上的距离计算出拉线错牙偏移量;针对Sobel、Canny等获取的边缘存在较多冗余信息问题,提出了一种扫描线边缘提取(SLEE)算法;实验结果表明所提方法能有效地检测出烟包拉线的错牙程度,误差小于0.3 mm且具有较好的鲁棒性。     

基于弦中点Hough变换的同心圆检测方法

给出了一种基于Hough变换的同心圆检测方法,其核心思想是降低经典Hough变换圆检测中的Hough累积维数,将经典Hough变换圆检测时的三维参量统计,转变成基于弦中点的圆心和半径的参量统计。根据圆上所有点的内切圆必经过圆中心的事实,提取黑白边缘图像来建立二维数组累加器,依照像素点分布扫描边缘图像,累加器计数,计算出圆心位置,对每个圆心进行半径累积,确定同心圆半径集。与经典的Hough变换检测方法相比,该方法降低了计算复杂度。     

基于Hough变换的汽车零件中圆形检测的改进算法

针对汽车零件中的圆检测实际需求,在分析了基本Hough变换和随机Hough变换进行圆检测的技术特征基础上,对基本Hough变换进行算法改进。采用Sobel算子提取图像边缘,利用圆参数范围已知的先验知识确定感兴趣区域和圆半径的检索范围,使得计算量大大减少,从而实现圆心坐标和半径的快速检测,满足工业生产实时性的要求。     

一种用Hough变换检测圆的快速算法*

为了克服传统Hough变换检测圆时耗时巨大的缺陷,给出了一种新的基于Hough变换检测圆的快速算法.新算法与传统的方法相比具有以下特点:计算量少,提高了检测的速度;保留了传统Hough变换识别率高、抗噪性强、对不完整边缘具有鲁棒性等所有优点;不需要任何特殊的限定条件.实验表明,新的快速算法可以快速进行目标识别,在实时目标识别系统中具有良好的表现.     

基于肤色检测和Hough变换的彩色图像人眼定位

提出一种基于肤色检测和Hough变换两步快速定位人眼的方法。通过YCbCr肤色模型对图像肤色区域进行检测,同时进行Sobel边缘提取,然后用Hough变换的圆检测方法对二值化图像进行圆检测,从而确定双眼的精确位置。实验结果表明该算法受噪声和边缘间断影响小,具有较高的定位准确率。同时具有很好的容错性和健壮性。     

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.     

一种随机Hough 变换检测圆的优化方法

随机Hough变换是常用的图像测圆方法,当图像数据杂乱时,随机Hough变换的结果不理想且检测实时性差.针对激光扫描检测直缝焊管焊缝噘嘴问题,提出了一种优化的随机Hough变换检测圆方法.首先计算激光扫描所得轮廓离散点的曲率值,然后采用K均值聚类法从轮廓图像中分离出圆弧数据点,最后使用随机Hough算法检测圆.实验表明,本文方法可以准确而快速地计算出焊管径向横截面二维轮廓圆的圆心和半径,可以满足工业实际应用需求.     

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。     

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.     

瞳孔中心快速定位方法研究

眼球运动是获得和揭示大脑工作信息的重要途径。近年来的研究多将眼球建模成圆或椭圆,利用Hough变换检测圆或椭圆,从而达到瞳孔中心定位的目的。传统的Hough变换（含随机Hough变换）的实时性较差,而为了获得更加准确有效的眼球运动信息,采集帧率往往需要超过100 f/s。为此,利用VOG的暗瞳特性及二值化后瞳孔图像圆的唯一性,通过Video Oculographic（VOG）设备采集眼部视频,对Hough变换进行改进,对预处理过的二值图像进行边缘提取,同时选取边缘上的三点通过点Hough变换得到一个参数组,再用数学期望替代传统Hough变换投票方式,对所有参数组求数学期望,得到最终瞳孔中心。实验证明,该方法可行、精确、稳定。     

一种基于Hough变换的损伤检测方法

针对香烟条包端面透明纸损伤的实时、在线图像检测问题,提出一种基于Hough变换的损伤检测方法.根据香烟条包端面透明纸的损伤特点,利用Hough变换原理构造了一个损伤判别准则,并根据该准则值的大小来实现损伤的在线检测.构建了图像检测系统,利用实际采集的香烟条包端面透明纸损伤图像对该方法进行了分析和验证,结果表明,其可以有效地检测香烟条包端面透明纸出现的异常现象.     

基于形状信息的三角形交通标志检测方法

提出一种基于快速辐射对称性和Hough变换的三角形交通标志检测方法。利用快速辐射对称性检测三角形的内心,在内心处设置一个窗口对窗口内图像作Hough变换,在图像的Hough域中检测三角形交通标志。实验结果表明,该算法能有效弥补现有同类算法的缺陷,具有较高的检测效率。     

基于椭圆拟合的快速钢管计数方法

为满足钢管计数中精度和速度的需求,提出了一种新型的椭圆检测方法.该方法避开了Hough变换或随机Hough变换的复杂性,直接通过边缘跟踪对椭圆进行拟合,通过其它边缘像素对拟合结果进行校验和对比,对概率超过阈值的无包含椭圆进行计数.在边缘检测过程中对Robert算子进行了改进,并在阈值分割前对边缘进行了增强,在阈值分割后对边缘进行了保持连通性的细化.根据需要还可以在计数过程中加入人工指导.实验结果表明,该方法能快速准确地检测出图像中所有椭圆.     

Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.     

Circle Detection Based on HSI Color Space

A method based on HSI color space is presented to solve the problem of circle detection from color images. In terms of the evaluation to the edge detection method based on intensity, the edge detection based on hue is chosen to process the color image, and the simplified calculation of hue transform is discussed. Then the algorithm of circle detection based on Canny edge detection is proposed. Due to the dispersive distribution of the detected result, Hough transformation and template smooth are used in circle detection, and the proposed method gives a quite good result.     

A hybrid multi-scale model for thyroid nodule boundary detection on ultrasound images

A hybrid model for thyroid nodule boundary detection on ultrasound images is introduced. The segmentation model combines the advantages of the “á trous” wavelet transform to detect sharp gray-level variations and the efficiency of the Hough transform to discriminate the region of interest within an environment with excessive structural noise. The proposed method comprise three major steps: a wavelet edge detection procedure for speckle reduction and edge map estimation, based on local maxima representation. Subsequently, a multiscale structure model is utilised in order to acquire a contour representation by means of local maxima chaining with similar attributes to form significant structures. Finally, the Hough transform is employed with ‘a priori’ knowledge related to the nodule's shape in order to distinguish the nodule's contour from adjacent structures. The comparative study between our automatic method and manual delineations demonstrated that the boundaries extracted by the hybrid model are closely correlated with that of the physicians. The proposed hybrid method can be of value to thyroid nodules’ shape-based classification and as an educational tool for inexperienced radiologists.     

A hybrid multi-scale model for thyroid nodule boundary detection on ultrasound images

A hybrid model for thyroid nodule boundary detection on ultrasound images is introduced. The segmentation model combines the advantages of the "á trous" wavelet transform to detect sharp gray-level variations and the efficiency of the Hough transform to discriminate the region of interest within an environment with excessive structural noise. The proposed method comprise three major steps: a wavelet edge detection procedure for speckle reduction and edge map estimation, based on local maxima representation. Subsequently, a multiscale structure model is utilised in order to acquire a contour representation by means of local maxima chaining with similar attributes to form significant structures. Finally, the Hough transform is employed with 'a priori' knowledge related to the nodule's shape in order to distinguish the nodule's contour from adjacent structures. The comparative study between our automatic method and manual delineations demonstrated that the boundaries extracted by the hybrid model are closely correlated with that of the physicians. The proposed hybrid method can be of value to thyroid nodules' shape-based classification and as an educational tool for inexperienced radiologists.     

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。     

结合LTS和Hough变换的直线检测算法

为提高Hough变换检测直线的精度,提出一种结合Hough变换与截断最小二乘法的直线检测算法。利用Hough变换确定图像中直线所在的大致区域,提取候选区域内的特征点集,采用截断最小二乘法拟合得到精确的直线参数。实验结果表明,该算法的检测率和检测精度较高,对Hough变换的分辨率要求较低,整体空间开销较小。