【摘要】 对基于人工神经网络的印制线路板(PCB)图件识别进行了研究。识别过程主要分为两个阶段:图像的预处理和模式识别。图像预处理阶段运用数字图像处理技术,从原始PCB图中提取出待识别的图件对象;在模式识别阶段,采用BP神经网络模型对PCB图件图像进行识别,为降低网络规模,经深入分析比较,提出了一种行、列扫描提取图件图像特征向量的算法,并对标准BP学习算法进行了改进,获得了较好的效果。更多还原

【Abstract】 The paper research the application of artificial neural network in the recognition of diagram pieces rooting in PCB.The recognition makes up of two phases: image pretreatment and recognition.In the first phase,we distill the diagram pieces from the original image of PCB by the technique of digital image process;In the second phase,recognizing the diagram pieces of PCB using the BP neural network,in order to lower the scale of the network,we put forward a algorithm extracting the feature vector of diagram pieces by the row or column scanning,in addition,we mend the standard algorithm in the study course of BP neural network,and achieving better effect.更多还原