Fractional speeded up robust features detector with the Caputo-Fabrizio derivative

Abstract

In this research, a fractional-order method for distinctive keypoints detection and to the image matching based on the Caputo-Fabrizio derivative and in the Speeded-Up Robust Feature (SURF) algorithm is presented and experimentally tested. The main advantage of introducing the fractional-order derivative is the improvement of the texture details detection, by combining this derivative with the SURF algorithm, the images feature extraction is improved to reach accurate images matching. The proposed method is compared experimentally with conventional SURF and SIFT algorithms. The experimental results showed that the proposed method has a high capacity for detecting points of interest in a region of the image with low contrast and weak texture.