Some new edge detecting techniques based on fractional derivatives with non-local and non-singular kernels

B Ghanbari, A Atangana - Advances in Difference Equations, 2020 - Springer
Computers and electronics play an enormous role in today's society, impacting everything
from communication and medicine to science. The development of computer-related …

Fractional Fourier Transform based Riesz fractional derivative approach for edge detection and its application in image enhancement

K Kaur, N Jindal, K Singh - Signal Processing, 2021 - Elsevier
Edge detection plays a key role in detecting the boundaries of an object in the image to
improve the quality of image edges. The edge detection techniques based on integer order …

QRFODD: Quaternion Riesz fractional order directional derivative for color image edge detection

K Kaur, N Jindal, K Singh - Signal Processing, 2023 - Elsevier
Edge detection is the prominent method to determine the discontinuities present in an
image. There exists an issue of loss of information and correlation during the extraction of …

A new fractional-order mask for image edge detection based on Caputo–Fabrizio fractional-order derivative without singular kernel

JE Lavín-Delgado, JE Solís-Pérez… - Circuits, Systems, and …, 2020 - Springer
In this work, we consider the Caputo–Fabrizio fractional-order derivative to generalize the
first-order Sobel operator. The resulting fractional mask is used to carry out edge analysis of …

Generalized framework for the design of adaptive fractional-order masks for image denoising

A Gupta, S Kumar - Digital Signal Processing, 2022 - Elsevier
This paper proposes a generalized fractional differential (GFD) mask which incorporates
various fractional-order kernels such as power-law kernel, exponentional kernel, and Mittag …

[PDF][PDF] About Edge Detection in Digital Images.

M Hagara, P Kubinec - Radioengineering, 2018 - radioeng.cz
Edge detection is one of the most commonly used procedures in digital image processing. In
the last 30–40 years, many methods and algorithms for edge detection have been proposed …

An improved method for image denoising based on fractional-order integration

L Xu, G Huang, Q Chen, H Qin, T Men, Y Pu - Frontiers of Information …, 2020 - Springer
Given that the existing image denoising methods damage the texture details of an image, a
new method based on fractional integration is proposed. First, the fractional-order integral …

Computational fractional-order calculus and classical calculus AI for comparative differentiability prediction analyses of complex-systems-grounded paradigm

Y Karaca, D Baleanu - Multi-Chaos, Fractal and Multi-fractional Artificial …, 2022 - Elsevier
Modern science having embarked on the thorough and accurate interpretation of natural
and physical phenomena has proven to provide successful models for the analysis of …

Discrete Laplacian operator and its applications in signal processing

W Waheed, G Deng, B Liu - IEEE Access, 2020 - ieeexplore.ieee.org
Fractional calculus has increased in popularity in recent years, as the number of its
applications in different fields has increased. Compared to the traditional operations in …

Fractional derivatives for edge detection: application to road obstacles

R Abi Zeid Daou, F El Samarani, C Yaacoub… - … , cognition, & security, 2020 - Springer
Detecting road obstacles is a major challenge in autonomous vehicles for smart
transportation and safe cities. They have always been a major problem, as they increase car …