【作者】 陈静；

【导师】 张志佳；

【作者基本信息】 沈阳工业大学 ， 测试计量技术及仪器， 2011， 硕士

【摘要】 图像匹配技术是图像处理技术与机器视觉检测中的核心内容,在工业产品在线检测系统中,传统的匹配方法不适用于发生角度旋转的两幅图像间的匹配,而圆形图像在线检测系统中,采集到的图像与基准图像之间总是存在任意角度偏差,这给检测工作带来了一定的困难性。本课题正是基于这种背景下提出的,以啤酒瓶盖质量检测为例,针对存在角度旋转的圆形图像匹配进行了研究。本文在分析旋转的圆形图像匹配方法发展现状及发展趋势的基础上,针对圆形图像的预处理以及匹配等工作进行了深入研究,主要研究内容如下：在预处理阶段,本文对采集到的瓶盖图像的定位进行了研究,对图像进行分段线性变换并根据三点定位圆的数学理论完成圆形图像的定位。针对图像旋转角度的计算问题,课题分别提出基于关键点检测的旋转角度校正算法与基于傅里叶变换的旋转角度校正算法。前者首先采用基于曲率尺度空间的角点检测算法检测角点,在已检测的角点中找到一个较稳定的关键点,以此关键点为特征点,将该点与图像的几何中心点连线,求出该线与坐标轴的夹角即为待测图像的旋转角度。后者利用傅里叶变换算法在时频域中的旋转不变性,以图像中心为原点,1/2图像宽度为半径做圆,统计在0-180度内径向方向上的灰度累加值,则实际旋转的角度即为最大值所对应的角度。两种算法可以实现相同的功能,但后者对旋转角度的计算具有更高的精度。最后课题在对待测图像旋转校正的基础上,采用基于分块均值的快速块匹配算法和基于对数极坐标变换的匹配算法完成待测图像与基准图像之间的匹配。本文根据以上所提出的方法进行了大量的实验,从解决旋转变化、匹配速度和正确率方面进行分析。实验结果表明,所提出的算法具有较高的匹配速度和鲁棒性,并且算法对于解决图像旋转角度的校正问题具有较好的优势和有效性。更多还原

【Abstract】 The matching technology on image is the core content in picture processing technology and machine vision detecting. In the system of the online measuring of industrial products, the traditional matching method is not applicable to angle rotation between the two matching images, While in round images on-line detection system, there is always existence some angle deviation between the collecting images and benchmark, which brings some difficulties to the detection work. The issue is proposed based on this background, with the example of beer cap quality inspection, aiming to rotation changes of angle between two images this paper was studied.This articles has done some research about the collected round image, and has carried out depth study for the preprocessing and matching of round image. The main research contents as follows.In the pretreatment stage, the paper has made some studies about the location for the collected cap image. Making the round image isolated from the background which based on the mathematics theory of three points positing a circular by segmented linear transformation.Then proposed two angle correction algorithms for image rotation that based on key point detection and Fourier transform. Using the adaptive corner detector based on curvature scale space algorithm to detect corner points, to select a stable key point in the corners which have been detected. Connection the selected point with the geometric center of the image in order to certain the angle of the rotation image. The latter Fourier transform algorithm was introduced, training its time-frequency domain as invariance to rotation, firstly the image rotation angle was corrected by using Fourier transform, which made the untested image and reference image in the same direction.At last using the fast matching algorithm that based on sub block mean and the method of round image matching based on log-polar transform to match the untested and reference image. The experimental results show that compared with existing matching algorithms, the proposed algorithm can solve the rotation with any angle between two images’ matching, and the algorithm has a high matching accuracy and applicability. In addition, the validity and reliability had got verified.更多还原