【作者】 高湘玲；

【导师】 林建辉；

【作者基本信息】 西南交通大学 ， 测试计量技术及仪器， 2002， 硕士

【摘要】 早期的图像处理主要用于改善图像质量，随着计算机技术、图像采集技术的飞速发展，图像处理也越来越广泛地用于解决众多科学与工程领域中的问题，诸如医学图像分析、指纹鉴别、产品质量检验等。由于计算机图像处理具有许多独特的优点，因而发展非常迅速，成为现代技术研究的热点。 在电子工业中，PCB是各种电子产品的主要部件，PCB上的缺陷可能导致整块印制板甚至整台仪器报废，因此印制板的检验和测试是PCB厂商质量控制不可缺少的环节。 随着生产技术的提高，PCB制作工艺日趋复杂，大量超微器件和超细走线的采用，使PCB的质量检验成为一件非常困难的工作，难以实现自动化。传统的电测法和人工目测法已不能满足生产的需要。运用图像处理和识别技术对PCB图像进行分析，从而找出PCB上存在的缺陷是一种实时、无损、高精度和低成本的优秀方法。目前，市场上已有成品设备销售，通常被称为自动光学检查系统(AOI)，但这些设备多为国外研制，价格昂贵，国内尚在起步阶段；此外，现有的AOI系统仍存在较高的误判率。这说明在PCB图像处理和模式识别方法上仍需进一步的研究。 基于上述几点，本论文以数字图像处理和模式识别为理论基础，对PCB图像的采集、处理、识别的方法和难点进行了深入的探讨，并采用Borland 以C++ Builder6.0编制了一套PCB图像检测与识别软件，对印制板上存在的缺陷种类和数量实现自动检测和识别。 PCB图像检测与识别系统由四部分组成：图像采集、图像预处理、特征提取和图像识别。在图像预处理中，本文分析了常用图像增强和恢复方法对PCB图像的适用性，针对PCB图像的偏暗、对比度不强等特点给出了适合PCB图像特点的处理办法。对图像的二值化，采用双峰法和最大方差阈值法求阈值，取得了较好的效果。在图像识别中，本文分析了常用的模式识别方法，根据树分类法和序贯概率比检定法的思想设计了一种独特的PCB缺陷模式识别方法；并给出了针对各种PCB缺陷模式的特征选择与提取方法。同时，文中还对图像采集系统的设计和采集中的难点提出了解决方案。 在软件研制完成后，对大量PCB图像进了检测，经过对比试验证明能有效地识别印制板上的各种缺陷，收到了较好的效果。论文的设计是成功的，达到了预定的效果，研究成果具有较好的应用价值。更多还原

【Abstract】 With the development of computer and image acquisition technology, image processing extends its primitive applying in improving quality of image to resolving problems in many fields of science and technology, such as medical image analysis, fingerprint identification, quality inspection of products, and so on. Because of many unique advantages of digital image processing, it develops very rapidly, and now is one of hotspots in modern technology research.In electronic industry, PCB is the main part of kinds of electronic products, faults of which may led to rejection of the PCB, even more, the whole instrument. So the detecting and testing measure on PCB is necessary for quality control for PCB manufacturer.Because of the complicated manufacture technique of PCB, for example, a great deal of use of ultro-microcomponent and ultro-slimwire, the quality inspection of PCB becomes very difficult and hardly automatized. Traditional measurement of electronic detection and eye-detection can’t satisfy the need in process of manufacture. The way that faults on PCB are found by means of image processing and recognition technique is an excellent method, real-time, nondestructive, high-accuracy and low cost. Now some instruments have been on sale, which is called the Automatic Optical Inspection System(AOI). However, AOI is mainly made by foreign producer with expensive price, while its research is still underway in China; Meanwhile, AOI exists some disadvantages such as high misjudgement rate. All show that the method of PCB image processing and pattern recognition needs more studying.As the result, based on the principles of digital image processing and pattern recognition, this paper is focused on the methods and difficulties of acquisition, processing, recognition of PCB. With the use of Borland C++ Builder 6.0, a set of PCB image detection and recognition software system was developed, which can realize automatic detection and recognition for types and the amount of faults on PCB.The whole PCB image detection & recognition system consists of 4 parts: image acquisition; image pre-processing; feature extraction; image recognition. In terms of dim, low contrast of PCB image at the stage of image pre-processing, by analyzing the applicability of common methods of image enhancing and resuming for PCB image, a certain resolving methods have been shown: Obtaining the thresholding value by means of 2-mode method and maximum variance thresholding method, the result of image binarizaion was satisfied. At the stage of image recognition, a unique model of PCB fault recognition was built on methods of tree-classification and sequenntial probability ratio test, and a kind of method ofmfeature selection and extraction was introduced. In the same time, resolving methods for difficulties in design and acquisition of PCB image acquisition system were given out.Using this software system, amounts of PCB image have been tested. By comparing tests, the results show that it can recognize kinds of faults on PCB effectively, which proves the design of this paper and thus it has practical value.更多还原