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A Novel Edge Detection Method Based on Fractional-order Calculus Mask
一种基于分数阶次微积分模板的新型边缘检测方法

Keywords: Image processing,edge detection,fractional differentiation and integration,noise immunity,quantitative analysis
图像处理
,边缘检测,分数阶次微积分,抗噪性,定量分析

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Abstract:

In this paper, a new edge detection operator based on a composite derivative is proposed, which is realized by the combination of fractional differentiation and integration. The new complex edge-detection mask is also deduced for the implementation of fractional differentiation. The abilities of the compound derivative in terms of approximate simulation of first-order derivative and suppression of noise are demonstrated through one-dimensional examples. The experimental results of two-dimensional examples indicate that without the contamination of noise, the new operator can accurately detect the edge, while with the noise contamination, the new operator can effectively suppress the noise. Finally, quantitative analysis of the new operator is given. The results of the comparison between the new operator and Canny operator show that the new operator has the advantage of a low mispositioning rate.

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