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摘 要

印刷电路板(PCB)是集成各种电子元器件的信息载体，在各个领域得到了广泛的应用。近年来随着印刷电路板生产复杂度和产量的提高，传统PCB缺陷检测方式因接触受限、高成本、低效率等因素，己经逐渐不能满足现代检测需要，因此研究实现一种PCB缺陷的自动检测系统具有很大的现实意义和实用价值。PCB缺陷检测技术中，自动光学检测技术越来越受到重视，其中图像检测法也将成为自动光学检测的主流。

本课题在分析国内外对AOI系统中图像识别软件研究成果的基础上，基于图像处理技术、模式识别技术和缺陷检测技术，提出了一种运用参考法和设计规则校验法处理彩色PCB图像进行缺陷检测的方案。该系统主要由光照、CCD摄像机、图像采集卡及计算机图像处理软件组成。其中图像处理软件部分作为本课题的核心,着重研究了其关键功能模块包括图像灰度化、图像滤波、图像锐化、图像识别几个部分算法的选择与设计，并在MATLAB7.0的环境下进行仿真。

运用现代成熟的数字图像处理技术，本文实现了PCB缺陷的软件检测方案。在预处理模块中，结合PCB板的特点运用图像预处理手段,首先对彩色图像进行灰度化，其次运用图像滤波,最后通过图像锐化得到高质量的PCB图像。在识别模块中结合电路板的短路、断路缺陷的特征，识别短路和断路故障。提高了生产效率，降低了生产成本。

关键词： 缺陷检测；图像处理；图像滤波；图像识别

Title Detection of Short Circuit and Open Circuit of PCB Based on Image

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Abstract

Printed Circuit Board (PCB) is an information carrier integrating various electronic components. It has been applied in different fields widely.With the higher complexity and output of Printed Circuit Board manufacture in recent years, the traditional methods of PCB defect inspection can not meet demands of inspection gradually because of restricted contact, high cost or low efficiency.Therefore, the study of automatic defect inspection system is meaningful in the PCB production today. Automatic optical inspection (AOI) technology is more and more important, in which the image detection will become mainstream of automatic optical inspection in PCB defect inspection technology.

Image recognition software on the basis of research results in AOI system is analyzed in the system. Then, the scheme of PCB color images treatment and PCB defect inspection was proposed, in which a reference method and design rule method is used. It is based on image processing, pattern recognition and defect detection.The inspection system is composed of several parts, including light, CCD cameras, capture cards and computer image processing software systems. As the core of this thesis, the design and implementation algorithm of functional modules is the key of image processing. Functional modules is composed of image pre-processing as image graying, image filter, sharpening, and image recognition. These algorithms are simulated in MATLAB7.0.

The software detection program of PCB defect is implemented using modern sophisticated digital image processing technology in this paper. In the preprocessing module, image preprocessing methods is used combining the characteristics of PCB board.In order to get high-quality PCB image, first, the color image is grayed, then the gray image is filtered, and finally, the image is sharpened. In the module of image recognition, short circuit and open circuit is recognized by analyzing the character of two defects.The system have high production efficiency and low production costs.

Keywords: Defect inspection; Image processing; Image Filtering; Image recognition

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目 次

1 绪论 ............................................................... 1 1.1 课题研究的背景 ..................................................... 1 1.2 国内外现状和发展趋势 ............................................... 2 1.3 课题研究的目的和意义 ............................................... 3 1.4 本课题主要研究的内容 ............................................... 4 2 检测总体方案的设计 .................................................. 6 2.1 图像检测结构 ....................................................... 6 2.2 图像采集单元 ....................................................... 6 2.3 图像处理单元 ....................................................... 7 2.4 采集到的图像 ....................................................... 7 3 PCB图像的预处理 .................................................... 9 3.1 MATLAB软件简介 ..................................................... 9 3.2 彩色图像灰度化 .................................................... 10 3.3 PCB图像的滤波 ..................................................... 11 3.4 PCB图像的锐化 ..................................................... 14 4 PCB图像的缺陷检测 ................................................. 19 4.1 PCB的主要缺陷 ..................................................... 19 4.2 PCB缺陷检测方法 ................................................... 19 4.3 图像对比 .......................................................... 20 4.4 短路断路的检测 .................................................... 20 结论 ................................................................ 23 致谢 ................................................................ 24 参考文献 ............................................................ 25

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