一种用于电子元件检测的圆定位算法
A Circle Positioning Algorithm for Electronic Element Detection

作者: 杨志涵 , 邵秀丽 , 袁兆争 , 张华东 :南开大学计算机与控制工程学院,天津;

关键词: 圆定位PCB光学检测边沿检测灰度梯度Circle Location PCB Optical Detection Edge Detection Gray Gradient

摘要: 目前基于机器视觉、图像处理的PCB电路检测系统首要实现的就是对元件的准确定位。本文针对PCB板上的圆形电子元件进行机器视觉定位,提出了先使用Canny边缘检测结合Sobel变换的粗定位检测方法,再根据检测目标圆的边缘上的点,以及各点的灰度梯度,得到过边缘点的直线集合,继而使用正方形滑动窗口,实现圆心的定位,最后再使用同心圆环的方法,找到圆形边缘的半径,从而精确定位圆形电子元件的位置。经实际使用,本文算法满足电子企业工业生产中实时性和精确性的要求。

Abstract: At present, the image processing of the PCB circuit detection system based on machine vision is mainly to achieve the accurate positioning of components. According to machine vision positioning of the circular electronic components on the PCB board, we put forward the method: 1) to use Canny edge detection combined with Sobel transform coarse positioning detection method, 2) according to the detection target circle on the edge, and the gray gradient, to get the line set across edge points, 3) and then to use a sliding window to implement positioning of the center of the circle, 4) then to use the method of concentric rings, find the rounded edge radius, which can accurately locate the position of the circular electronic components. In practical application, the algorithm meets the requirements of real-time and accuracy in the industrial production of electronic enterprises.

文章引用: 杨志涵 , 邵秀丽 , 袁兆争 , 张华东 (2016) 一种用于电子元件检测的圆定位算法。 计算机科学与应用, 6, 607-616. doi: 10.12677/CSA.2016.610075

参考文献

[1] Uda, R.O. and Hart, P.E. (1972) Use of the Hough Transform to Detect Lines and Curves in Pictures. Communications of the ACM, 15, 11-15.
http://dx.doi.org/10.1145/361237.361242

[2] 夏磊, 蔡超, 周成平, 丁明跃. 一种用Hough变换检测圆的快速算法[J]. 计算机应用研究, 2007, 10(24): 197-210.

[3] Pei, S.-C. and Horng, J.-H. (1995) Circular Arc Detection Based on Hough Transform. Pattern Recognition Letters, 16, 615-625.
http://dx.doi.org/10.1016/0167-8655(95)80007-G

[4] 叶峰, 陈灿杰, 赖乙宗, 等. 基于有序Hough变换的快速圆检测算法[J]. 光学精密工程, 2014, 22(4): 1105-1111.

[5] 郭峰林, 管庶安, 何健. 基于势函数的印刷电路板定位孔快速定位算法[J]. 科技导报, 2010, 28(16): 71-73.

[6] 王耀贵. 图像高斯平滑滤波分析[J]. 计算机与信息技术, 2008(8).

[7] Jain, R., Kasturi, R. and Schunck, B.G. (1995) Machine Vision. McGraw-Hill, Inc., Boston, 112-139.

[8] Canny, J. (1986) A Computational Approach to Edge Detection. IEEE Trans Pattern Analysis and Machine Intelligence, 8, 679-698.
http://dx.doi.org/10.1109/TPAMI.1986.4767851

[9] 何春华, 张雪飞, 胡迎春. 基于改进Sobel算子的边缘检测算法的研究[J]. 光学技术, 2012(3): 323-327.

[10] Vincent, O.R. and Folorunso, O. (2009) A Descriptive Algorithm for Sobel Image Edge Detection. Proceedings of Informing Science & IT Education Conference (InSITE), 97-107.

[11] 沈德海, 侯建, 鄂旭. 基于改进的Sobel算子边缘检测算法[J]. 计算机技术与发展, 2013(11): 22-25.

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