| Print Circuit Board (PCB) is an information carrier integrating various electronic components. It has been applied in different fields widely.also with the continuous development of production technology, PCB are prone to be more layers and more density。Because of the complexity of PCB production process, makes the PCB quality inspection become a very difficult job. The traditional examination method can not satisfy the production’s needs already. The study on the automatic vision examination of PCB flaw is popular in the PCB examination, which is based on the computer and the image processing technology.This paper mainly research on the application of BP(Back Propogation) neural network and AOI (Automatic Optic Inspection) Technology which most widely used in industry, with the help of computer vision, according to characteristics of the meter PCB components, carrying out the matching recognition of the PCB’s image. This review focuses on the following specific research issues.First, it is introduced the importance of Automatic detection of PCB board and the technical means used, the basic idea and technical features of PCB board image recognition; next, it is illustrated the extraction method of the PCB board components image’s feature, and introduced the related algorithms for image processing; then,this paper described the implementation and technical features of neural network in this systems in detailed. We have designed and produced the corresponding detection device, prepared the supporting operating software for image acquisition, matching recognition, result analysis, reports given. The experimental results indicates that this means have low error decision rate, high matching precision, can be used in testing the consistency of PCB board’s components. |
PDF Full Text Request