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Analysis of Block Matching Algorithms for the application of image mosaicing to online surface inspection of steel products

机译:块匹配算法分析,用于将图像镶嵌应用于钢铁产品的在线表面检验

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Steel industry requires high quality controls to ensure certain requirements of the final products. In on-line inspection applications for long steel products, a camera is usually placed in the top, in order to view a portion of the product while it passes under the sensor in a roll table. The high relation between the length of the steel product and the necessary resolution to carry out these quality controls generates a set of partially overlapped images, that in many cases must be superimposed in order to obtain a full large image of the target. The characteristics of the algorithms for this image stitching process are essential to incorporate these techniques into the production line, with specific requirements about accuracy, processing speed and robustness. This paper presents a comparison between several Block Matching Algorithms (BMA) applied to two radically different steel industry cases, in which the surface reconstruction is necessary for defects detection and measurements. A general method is outlined for both cases, and it's effectiveness is shown by means of experimental results.
机译:钢铁行业需要高质量的控制,以确保最终产品的某些要求。在长钢制品的在线检查应用中,相机通常放置在顶部,以便在卷桌中通过传感器时查看产品的一部分。钢产品的长度与执行这些质量控制的必要分辨率之间的高关系产生一组部分重叠的图像,在许多情况下必须叠加,以便获得目标的全部大图像。用于该图像拼接过程的算法的特性对于将这些技术纳入生产线的必要性是必不可少的,具有关于精度,处理速度和鲁棒性的具体要求。本文介绍了应用于两个完全不同的钢铁工业案例的几个块匹配算法(BMA)之间的比较,其中表面重建是缺陷检测和测量所必需的。两种情况下概述了一般方法,通过实验结果显示了其有效性。

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