Lookup Table Hough Transform for Real Time Range Image Segmentation and Featureless Co-Registration

The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and allow for acquisition of 3-dimensional measurement sequences that can be used for 3D reconstruction of indoor environments from moving platforms. The role of segmentation is twofold. First the necessary image co-registration can be based on corresponding segments, instead of corresponding point features (which is common practice currently). Secondly, the segments can be used during subsequent object modelling. By realisising that planar regions in disparity images can be modelled as linear functions of the image coordinates, having integer values for both domain and range, the paper introduces a lookup table based implementation of local Hough transform, allowing to obtain good segmentation results at high speeds.

Detection of broken manhole cover using improved Hough and image contrast

The damage or loss of urban road manhole covers may cause great risk to residents＇ lives and property if they cannot be discovered in time. Most existing research recommendations for solving this problem are difficult to implement. This paper proposes an algorithm that combines the improved Hough transform and image comparison to identify the damage or loss of the manhole covers in complicated surface conditions by using existing urban road video images. Focusing on the pre-processed images, the edge contour tracking algorithm is applied to find all of the edges. Then with the improved Hough transformation, color recognition and image matching algorithm, the manhole cover area is found and the change rates of the manhole cover area are calculated. Based on the threshold of the change rates, it can be determined whether there is potential damage or loss in the manhole cover. Compared with the traditional Hough transform, the proposed method can effectively improve the processing speed and reduce invalid sampling and accumulation. Experimental results indicate that the proposed algorithm has the functions of effective positioning and early warning in the conditions of complex background, different perspectives, and different videoing time and conditions, such as when the target is partially covered.

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。

基于投影约束和随机采样Hough变换的虹膜分割方法

非合作式虹膜图像的采集导致图像中具有大量干扰和噪声,因此,提出基于投影约束和随机采样Hough变换的虹膜分割方法提取虹膜有效区域。对虹膜二值图像进行投影粗定位虹膜的外轮廓圆心和半径,通过圆心和半径确定虹膜的大致区域,在该区域上,使用随机采样的Hough变换确定虹膜的内外轮廓,从而提高了虹膜分割的准确性。实验证明,与现有方法相比虹膜分割方法错误指标E1和E2最多提高8%和20%,具有更低的错误率和较高的时间效率。

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.

基于Hough变换的四旋翼无人机自主循迹系统设计

为保证无人机在飞行过程中实现高效、稳定的循迹控制,设计了一种基于Hough变换的四旋翼无人机自主循迹系统。该系统将无人机机载摄像机实时采集的Y1UY2V格式编码的图像转化为RGB图像,使用全局阈值对图像进行二值化处理,利用Canny边缘检测查找灰度图像中的边缘路径,对边缘检测后的图像进行二值形态学计算,通过Hough变换检测出直线和圆形,并将识别出的图像中路径特征转化为位置信息,利用一个约束动力学模型进行无人机自主循迹控制。以跟踪“Ω”字和“L”字形轨迹进行仿真和真机实验,结果表明,该方法具有较高的识别率和循迹精度,能够有效提高无人机的自主循迹能力。

SAR Moving Target Detection and Imaging Based on WVH Transform

Aim To propose a generalized and closed representation of the Wigner Ville Hough transform(WVHT), for the moving target detection and imaging in the design of synthetic aperture radar(SAR). Methods Based on the line integral, the WVH transform was derived by combining the Wigner Ville distribution (WVD) and the Hough transform (HT) together. The new transform was then verified with computer by the simulated SAR echoes. Results and Conclusion The correctness and the validity of the WVH transform were proved by the computer simulation. Compared with the conventional WVD HT method, the new approach based on the WVHT can simplify the processing procedure, it can translate the chirp echoes of multi targets of SAR from the time domain into the parameter space directly, while suppressing the cross terms of WVD and estimating the motion coefficients for the final imaging. It is obvious that the WVH transform can be also used in other cases for the chirp signal detection.

An Efficient Bar Code Image Recognition Algorithm for Sorting System

In the sorting system of the production line,the object movement,fixed angle of view,light intensity and other reasons lead to obscure blurred images.It results in bar code recognition rate being low and real time being poor.Aiming at the above problems,a progressive bar code compressed recognition algorithm is proposed.First,assuming that the source image is not tilted,use the direct recognition method to quickly identify the compressed source image.Failure indicates that the compression ratio is improper or the image is skewed.Then,the source image is enhanced to identify the source image directly.Finally,the inclination of the compressed image is detected by the barcode region recognition method and the source image is corrected to locate the barcode information in the barcode region recognition image.The results of multitype image experiments show that the proposed method is improved by 5+times computational efficiency compared with the former methods,and can recognize fuzzy images better.

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.

A Fast Image Matching Algorithm Using a Combination of Line Segment Features

The scene matching navigation is a research focus in the field of autonomous navigation,but the real-time performance of image matching algorithm is difficult to meet the needs of real navigation systems.Therefore,this paper proposes a fast image matching algorithm.The algorithm improves the traditional line segment extraction algorithm and combines with the Delaunay triangulation method.By combining the geometric features of points and lines,the image feature redundancy is reduced.Then,the error with confidence criterion is analyzed and the matching process is completed.The simulation results show that the proposed algorithm can still work within 3°rotation and small scale variation.In addition,the matching time is less than 0.5 s when the image size is 256 pixel×256 pixel.The proposed algorithm is suitable for autonomous navigation systems with multiple feature distribution and higher real-time requirements.

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.

A MODIFIED DYNAMIC GENERALIZED HOUGHTRANSFORM FOR LINE DETECTING

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Localized Model and Arithmetic System Based on Two Image Sensors Under Complex Circumstance

Two image sensors simulate directly the way of disposing images with the human＇s two eyes, so it has important value to apply in many domains, such as object identification, small unmaned aerial vehicle （UAV）, workpiece localization, robot navigation and so on. The object localization based on two image sensots is studied in this paper. It concentrates on how to apply two charge coupled device （CCD） image sensors to object localization of sphere in complex environments. At first a space model of the two image sensors is set up, then Hough transformation is adopted to get localizated model and arithmetic system. An experiment platform is built in order to prove the correctness and feasibility of that localization algorithm.

Implementation of the Hough Transform for Iris Detection and Segmentation

The iris is used as a reference for the study of unique biometric marks in people. The analysis of how to extract the iris characteristic information represents a fundamental challenge in image analysis, due to the implications it presents: detection of relevant information, data coding schemes, etc. For this reason, in the search for extraction of useful and characteristic information, approximations have been proposed for its analysis. In this article, it is presented a scheme to extract the relevant information based on the Hough transform. This transform helps to find primitive geometries in the irises, which are used to characterize each one of these. The results of the implementation of the algorithm of the Hough transform applied to the location and segmentation of the iris by means of its circumference are presented in the paper. Two public databases of iris images were used: UBIRIS V2 and CASIA-IrisV4, which were acquired under the same conditions and controlled environments. In the pre-processing stage the edges are found from the noise elimination in the image through the Canny detector. Subsequently, to the images of the detected edges, the Hough transform is applied to the disposition of the geometries detected.

Study and Realization of camera wafer image fusion algorithm

Image mosaics not only can make the collected several original images regenerate a complete image, but also can correct the error caused by imaging distortion of the original images, which can achieve the objective of rapid and correct mosaic image. The program studies the image mosaics of wafer defect inspection system. For the problem that the field range taken by CCD camera under resolution of wafer defect inspection system is small, which can＇t get the whole wafer image once and influences the extraction of subsequent defect features, the study demands to add image mosaics to the system.

基于图像边缘与Hough变换的振动位移测量方法

为了解决振动位移测量场合受限于传感器的安装空间,以及其本身质量对测量精度的影响,课题组提出了一种基于视频图像的振动测量方法,建立了图像边缘检测结果与目标物体位移之间的联系。由于使用经典Canny算法进行图像测量时,其图像边缘会出现不连续或虚假的情况,因此采用图像灰度与Hough变换相结合的方法,提高其测量精度。为验证该方法的有效性,搭建了箱体模型(目标物体)进行振动实验;并将经典Canny算法得出的结果及文中提出的视频图像测量的结果与传感器测得结果进行比较。实验结果表明,提出的方法相比使用经典Canny算法进行图像测量时精度提高了大约12%,且具有测量简单和测量范围灵活等优点。该方法为测量环境受限的场地提供了一种新的思路。

基于霍夫变换的透镜中心偏差检测方法

随着光学技术的发展,对光学透镜综合性能提出更高的要求,对心加工作为透镜生产必不可少的一环对镜头综合性能起重要作用,现有对心加工需要工人通过对心器手动测量及调整,对工人技术要求高、加工效率慢。文章基于霍夫变换提出一种适用于对心加工的中心偏检测算法以提升对心加工测量效率。首先通过工业相机拍摄对心器目镜中的图像,对图像进行灰度化、降噪、根据图像特征削弱干扰因素、二值化的预处理操作,再根据Canny边缘检测和霍夫变换识别图像中十字像的直线,最后根据角度区分直线求得交点,使用最小二乘法拟合出透镜的实际中心偏,实现了反射式测量和透射式测量两种工况的中心偏检测。实验结果表明,该算法能够检测两种工况下的中心偏,检测精度达到亚像素级。本文使用的中心偏检测算法可以提升对心加工的效率和精度。

基于中低分辨率卫星影像中舰船目标识别方法

目前,中低分辨率成像侦察卫星已经成为远距离情报保障的重要手段之一。然而,中低分辨率成像侦察卫星对海上机动舰船的侦察存在目标检测、识别难等问题,大大影响了情报使用效益。针对上述问题,提出基于霍夫变换的舰船开尔文尾迹提取方法,用于匹配并识别舰船型号。通过仿真得出不同型号舰船的开尔文尾迹尖头波平均距离,可以有效的识别出真实遥感影像中舰船属性,与实际影像数据对比分析,证明上述算法具有一定可行性。因此,基于霍夫变换的舰船开尔文尾迹提取方法可以在一定条件下基本实现目标舰船型号的识别,提升中低分辨率成像侦察卫星对海上机动舰船目标的识别准确率。

基于图像取反的同心圆环半径和圆心提取方法

为了解决非定域干涉同心圆环图像的圆心和半径的精确提取问题,提出了一种基于图像取反的暗亮环兼顾的算法,以点光源非定域干涉同心圆环为对象,在平滑降噪预处理基础上,利用霍夫圆变换获得参考圆心,以参考圆心为基础分别在其x方向和y方向上[-50,50]像素范围内每隔5 pixel取一条强度轮廓线,每一条强度轮廓线取反后,分别实现暗环和亮环峰位坐标的精确识别,再利用圆回归拟合得到系列圆心和半径,通过系列圆心和半径的平均运算实现图像最终圆心和半径的精确提取。结果表明,靠近中心的3个亮环和3个暗环各自的圆心坐标非常接近,相对于总平均值的最大偏差为-3.7 pixel,即相对于总平均值的最大相对偏差为-0.15%,重复性很好;相邻两个圆环半径平方比值相对于实际比值的误差在-4.18%~0.36%之间变化,验证了算法的可行性。该研究对实现自动化检测、提高测量精度是有帮助的。

基于改进Hough变换和透视变换的透视图像矫正

由于成像系统和目标的距离和方位的原因,会导致形成的图像发生透视而不再是正视图,这对于图像的特征提取、识别等后续处理非常不利。对于发生了透视畸变的图像,透视变换解决了一般仿射变换不能改变图像内部点相对位置的缺陷。文章根据透视变换的原理提出了基于改进的霍夫变换和透视变换的透视图像矫正技术,该算法根据摄像机的成像机理进行透视图像矫正,Matlab仿真实验结果表明,该算法可行性高,简单易行,稳定性好,可广泛推广至目标识别等领域。