Research On Inspection And Recognition Of PCB Digital Image

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.