感知器在钢板表面缺陷信息识别中的应用  

Application of perceptron in recognizing surface defect information on steel sheet

作　　者：程万胜[1] 赵杰[1] 李长乐[1] 

机构地区：[1]哈尔滨工业大学机器人研究所,黑龙江哈尔滨150080

出　　处：《光电工程》2006年第11期45-48,119,共5页Opto-Electronic Engineering

摘　　要：通过对钢板表面信息灰度值的详细分析,提出了一种利用简单感知器组成的分类器识别钢板表面缺陷的新方法。该方法在图像采集设备中直接对图像信息进行预处理,把认为是疑似缺陷信息的数据发送给后续处理器分析,可极大地减少系统数据处理量。在FPGA中实现了该方法,结果表明利用该方法简化了系统硬件结构,提高了系统实时性。A novel method was presented to separate defective information from steel sheet surface images by anatomizing the grey values of steel sheet surface images, which uses a classifier composed of some simple perceptrons. The method directly preprocesses image data in camera, and only provides defective data out to be further processed, so the amount of data in the system which must be further processed is reduced dramatically. Furthermore, the method was implemented in FPGA, and experiment results show that after using this method, the system hardware structure is simple, as well as the real-time performance is improved greatly.

关 键 词：感知器 钢板 表面缺陷 信息分类 FPGA 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]