At present, in domestic iron and steel plants, the manual inspection method for surface defects of the steel plates features poor reliability, thus the automatic detection system based on machine vision technology has been developed and designed. Through collecting the images of surface of steel strip by the cameras, then the images are processed and analyzed in real time with image processing and pattern identification algorithm for inspecting the defects in surface of the steel plate, and the defects are automatically classifying and identifying. The result indicates that the system can monitor the surface of the steel strip online in real time, and correctly identify the common surface defects of steel strips.%针对国内钢厂采用人工方法检查钢板表面缺陷存在可靠性差的问题,开发设计了基于机器视觉技术的带钢表面缺陷自动检测系统.系统通过摄像头采集带钢表面的图像,然后采用图像处理及模式识别算法对图像进行实时处理和分析,从而检测出钢扳表面缺陷,并对缺陷进行自动分类识别.实验结果表明,系统能够对带钢表面进行实时在线监测,并能正确识别常见的带钢表面缺陷.
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