A Fractional-Order Laplacian Operator for Image Edge Detection

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Abstract:

This paper proposes a novel fractional-order Laplacian operator for image edge detection. The proposed operator can be seen as generalization of the second-order Laplacian operator. The goal is to utilize the global characteristic of the fractional derivative for extracting more edge details. A thresholding is set based on the average fractional-order gradient for marking the edge points, and then the image edge can be extracted. Experiments show that the proposed fractional-order operator yields good visual effects.

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55-58

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April 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Bansal B, Saini J S, Bansal V, et al. Journal of Information and Operations Management. Vol. 3( 2012), p.103.

Google Scholar

[2] Zhang D D, Zhao S. Applied Mechanics and Materials. Vol. 347(2013), p.3541.

Google Scholar

[3] Pu Y F, Zhou J L, Yuan X. Image Processing, IEEE Transactions on. Vol. 19(2010), p.491.

Google Scholar

[4] Bai J, Feng X C. Image Processing, IEEE Transactions on. Vol. 16(2007), p.2492.

Google Scholar

[5] Ding Y, Wei Z, Xu J. Journal of Applied Mathematics and Computing. Vol. 41(2013), p.257.

Google Scholar

[6] Tian D, Xue D, Chen D, et al. Control and Decision Conference. (2013), p.37.

Google Scholar

[7] Podlubny I. Access Online via Elsevier, (1998).

Google Scholar