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Effective arc extraction method for ellipse detection in complicated images

机译:复杂图像椭圆检测的有效弧提取方法

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Due to corruption from image clutter and noise in Complicated natural images, ellipses are likely to be broken into many small disconnected arcs which is challenging for ellipse detection methods based on edge following techniques. In order to cope with this problem, a novel arc extraction method is proposed based on edge curvature. The method first groups connected pixels to form line segments and then breaks edge contours into smooth arcs at the turning points, inflexion points and noise connection points of the curve. Finally, near distance arcs are reconnected based on edge curvature. In this aspect, two arcs are linked if the new arc has no turning points, inflexion points and noise connection points. Additionally, we apply the arc reconnection method on a set of challenging images and the ellipse detection results get improved. Therefore, this work contributes towards ellipse detection.
机译:由于复杂图像中图像杂乱和噪声的破坏,椭圆很可能会分解成许多小的不连续弧,这对于基于边缘跟踪技术的椭圆检测方法是一个挑战。为了解决这个问题,提出了一种基于边缘曲率的电弧提取方法。该方法首先将连接的像素分组以形成线段,然后在曲线的转折点,拐点和噪声连接点将边缘轮廓分成平滑的弧线。最后,基于边缘曲率重新连接近距离弧。在这方面,如果新弧没有转折点,拐点和噪声连接点,则将两个弧链接在一起。此外,我们将弧线重新连接方法应用于一组具有挑战性的图像,并且椭圆检测结果得到了改善。因此,这项工作有助于椭圆检测。

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