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A robust edge detection method with sub-pixel accuracy

机译:具有亚像素精度的鲁棒边缘检测方法

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摘要

In this paper, a new edge detection approach combining gray-moments operator with smoothing spline algorithm is proposed, which is invariant to additive and multiplicative noises in the image. This approach consists of two steps: firstly, a continuous blurred edge model is obtained using the smoothing spline algorithm in the edge region detected by Sobel operator; then a gray-moment solution is derived for both the one- and two-dimensional situations using the blurred edge model. Testing of this new detection approach demonstrates more robustness against the white Gaussian noise and speckle noise, and run time very close to the gray-moment and space-moment operators. The above advantages indicate this approach is very suitable for on-line accurate detection.
机译:提出了一种结合灰度矩算子和平滑样条算法的边缘检测新方法,该方法对于图像中的加性和乘性噪声是不变的。该方法包括两个步骤:首先,使用平滑样条算法在Sobel算子检测到的边缘区域中获得连续的模糊边缘模型。然后使用模糊边缘模型针对一维和二维情况导出灰度矩解。对这种新检测方法的测试表明,它对白高斯噪声和斑点噪声具有更强的鲁棒性,并且运行时间非常接近灰度矩和空间矩运算符。以上优点表明该方法非常适合在线精确检测。

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