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边缘检测方法研究及应用

发布时间:2019-01-10 20:52  文章来源:笔耕文化传播
【摘要】:随着机电一体化的发展,零件大批量的生产要求不断提高。高速、高精度不断渗透到机加工的各个生产环节,然而在加工过程中经常由于外界及材料本身特性的影响,导致生产出来的销钉存在表面划伤、锈迹、尺寸超出公差范围等缺陷,将影响销钉的正常使用,对于体积较小的销钉,人工对合格零件分拣已经不能满足工业生产对产品质量以及生产速度的要求。因此,基于图像处理对销钉进行非接触检测筛选的技术研究非常重要。通过对众多边缘算法的研究,对销钉边缘精准定位的算法选择中,理论的插值边缘检测算法,在实际图像检测过程中,存在定位不准确的缺点。本文针对高斯亚像素算法无法适用于实际检测情况的缺点,在对销钉的筛选过程中加入了边缘检测步骤,对原始的插值算法进行了优化。本论文基于MATLAB编程平台,将算法实现。并对各种经典的边缘算子进行比较,在销钉表面质量和边缘定位过程中,确定对SSIM结构相似度函数和高斯亚像素插值算法进行优化,并以对应的程序将算法实现。处理过程如下:首先通过Canny算法对图像进行处理,得到图像边缘轮廓,将该轮廓与标准销钉的轮廓进行相似度判断,完成初步的筛选;然后,在针对销钉尺寸测量过程中对边缘的角度进行旋转,对变换后的图像进行高斯插值计算,精确的针对销钉的尺寸进行筛选。这两种边缘检测算法的结合,在对边缘检测过程中具有方向不变性,而且能够高效率的对销钉进行筛选。实验证明将该算法运用于销钉边缘提取能满足精度要求。
[Abstract]:With the development of mechatronics, the requirement of mass production of parts is increasing. High speed and high precision continuously permeate into every production link of machining. However, in the process of processing, the pin produced often has surface scratches and rusts due to the influence of the outside world and the characteristics of the material itself. Such defects as dimension exceeding tolerance range will affect the normal use of pins. For smaller pins, manual sorting of qualified parts can no longer meet the requirements of industrial production for product quality and production speed. Therefore, it is very important to study the non-contact detection and screening of pins based on image processing. Through the study of many edge algorithms, the theoretical interpolation edge detection algorithm in the selection of pin edge accurate location algorithm, in the actual image detection process, there are shortcomings of inaccurate location. Aiming at the disadvantage that the Gussia pixel algorithm can not be applied to the actual detection, the edge detection step is added to the selection process of pin, and the original interpolation algorithm is optimized. This paper is based on MATLAB programming platform, the algorithm is implemented. In the process of pin surface quality and edge location, the similarity function of SSIM structure and Gauss pixel interpolation algorithm are optimized, and the algorithm is implemented by corresponding program. The processing process is as follows: firstly, the image edge contour is obtained by Canny algorithm, and the similarity between the contour and the standard pin contour is judged, and the preliminary screening is completed. Then, the angle of the edge is rotated in the process of pin size measurement, the transformed image is calculated by Gao Si interpolation, and the size of pin is screened accurately. The combination of these two edge detection algorithms is directionally invariant in the process of edge detection and can screen pins efficiently. The experimental results show that the algorithm can meet the precision requirement when it is applied to pin edge detection.
【学位授予单位】:天津工业大学
【学位级别】:硕士
【学位授予年份】:2017
【分类号】:TP391.41

【参考文献】

相关期刊论文 前10条

1 许光明;吴昭;周春兰;沈军民;;基于视觉的零件尺寸测量[J];工业控制计算机;2015年04期

2 刘明周;马靖;张淼;赵志彪;杨铎;王强;;基于机器视觉的机械产品装配系统在线作业方法[J];计算机集成制造系统;2015年09期

3 吕继武;于伟;郑伟;;一种基于改进的HOUGH变换的车轮检测方法[J];电子技术与软件工程;2014年13期

4 崔然;;浅析计算机视觉技术在农产品检测及分级中的应用[J];电子测试;2013年09期

5 祁晓玲;赵霞霞;靳伍银;;基于机器视觉的轴类零件几何尺寸测量[J];组合机床与自动化加工技术;2013年01期

6 来跃深;陈琛;田军委;程钢;;高斯插值亚像素边缘检测算法的优化[J];西安工业大学学报;2012年10期

7 林雯;;基于计算机视觉和神经网络的芒果外观等级分类研究[J];安徽农业科学;2010年23期

8 高晶晶;李景茹;刘瑞敏;;计算机视觉技术在花生破损检测中的应用[J];机电产品开发与创新;2010年03期

9 费丽君;谭峰;;机器视觉技术在大豆叶片叶绿素含量测算上的应用[J];农机化研究;2010年03期

10 凌远焕;徐杜;蒋永平;刘长红;黄杰贤;;基于局部区域灰度矩图像边缘定位方法的研究[J];光学与光电技术;2009年03期



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