Robust cutting-edge detection based on intensity concentration

Wei Li, Cheng-Bin Jin, Mingjie Ma, Jonghee Kim, Hakil Kim, X. Cui
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引用次数: 0

Abstract

This paper proposes three robust detection algorithms for locating the cutting line in an image captured by a panel-cutting system. All of the proposed methods contain two stages: edge detection and line fitting. In this paper, edge detection can search interest gradients depending on the intensity concentration. Meanwhile, the proposed line-fitting algorithm is able to precisely fit a line by minimizing the summation of L1 distance from each detected edge point to the fitted line. As the result, all of the proposed methods achieve accuracy of more than 85%. Going one step further, full-scale edge detection (FSED) obtains the best performance at 99.05%, which is evaluated by using a variety of real-world images.
基于强度集中的鲁棒前沿检测
本文提出了三种鲁棒检测算法,用于定位面板切割系统捕获的图像中的切割线。所有提出的方法都包含两个阶段:边缘检测和线拟合。在本文中,边缘检测可以根据强度集中来搜索兴趣梯度。同时,所提出的直线拟合算法通过最小化每个检测边缘点到拟合直线的L1距离之和来精确拟合直线。结果表明,所有方法的准确率均在85%以上。更进一步,全尺寸边缘检测(FSED)获得了99.05%的最佳性能,这是通过使用各种真实图像来评估的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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