A Fractional-Order Laplacian Operator for Image Edge Detection

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.