Title: A novel edge detection filter based on fractional order Legendre-Laguerre functions

Authors: Mohamed A. SayedElahl

Addresses: Department of Computer Science, Cairo Higher Institute, Egypt

Abstract: In recent decades, image processing technology has made significant advancements, but low-frequency images still pose challenges for analysis. To address this issue, we propose a novel edge detection filter based on fractional order orthogonal Legendre-Laguerre functions. Our filter can detect edges both horizontally and vertically in an image and can be adjusted to accommodate varying filter mask sizes, enabling it to scan low-pass and high-pass images with ease. We have successfully tested our filter on both greyscale and colour images, and it can effectively detect edges even in noisy images. Our numerical results indicate that our newly developed edge detection filter is an efficient method for grey and colour image segmentation. Furthermore, the granular parameters of our filter offer flexibility when exploring global features of an image. Overall, our proposed filter represents a significant improvement in edge detection and image segmentation. Its adaptability and accuracy make it a valuable tool for image processing professionals, researchers, and hobbyists. We believe that our filter will help overcome the limitations of existing edge detection techniques and facilitate more accurate analysis of low-frequency images.

Keywords: image segmentation; fractional order Legendre-Laguerre functions; edge detection.

DOI: 10.1504/IJISTA.2023.134982

International Journal of Intelligent Systems Technologies and Applications, 2023 Vol.21 No.4, pp.321 - 343

Received: 31 Dec 2022
Accepted: 27 Mar 2023
Published online: 23 Nov 2023 *

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