Edge Detection Based on the Newton Interpolation’s Fractional Differentiation
Chaobang Gao1,2, Jiliu Zhou2,3, and Weihua Zhang3
1College of Information Science and Technology, Chengdu University, China
2Key Laboratory of Pattern Recognition and Intelligent Information Processing, Chengdu University, China
3School of Computer Science, Sichuan University, China
1College of Information Science and Technology, Chengdu University, China
2Key Laboratory of Pattern Recognition and Intelligent Information Processing, Chengdu University, China
3School of Computer Science, Sichuan University, China
Abstract: In this paper, according to the development of the fractional differentiation and its applications in the modern signal processing, we improve the numerical calculation of fractional differentiation by Newton interpolation equation, and propose a new mask, the Newton Interpolation’s Fractional Differentiation (NIFD). Then we apply this new mask to image edge detection and can obtain the better edge information image. In order to get continuous and thin edges, we synthesize a new gradient and adopt the non_maxima suppression method. For a comparison, we consider the edge map yielded by the Sobel operator and Canny operator. By contrast, we discover that the edge image obtained by NIFD operator is better than those of Sobel and Canny operators, and specially for a noisy image, NIFD operator has the best anti-noise ability.
Keywords: NIFD operator, edge detection, newton interpolation, fractional differentiation.
Received September 4, 2011; accepted May 22, 2012
