Image Edge Detection by Global Thresholding Using Riemann–Liouville Fractional Integral Operator

It is difficult to give a fractional global threshold (FGT) that works well on all images as the image contents are totally different. This paper describes an interesting use of fractional calculus in the field of digital image processing. In the proposed method, the fractional global threshold-base...

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Bibliographic Details
Published inMathematical problems in engineering Vol. 2024; pp. 1 - 7
Main Authors Gaur, S., Khan, A. M., Suthar, D. L., Bora, Avnish
Format Journal Article
LanguageEnglish
Published New York Hindawi 2024
Hindawi Limited
Subjects
Calculus
Computing time
Datasets
Digital imaging
Edge detection
Fractional calculus
Image processing
Integrals
Investigations
Sensors
Signal to noise ratio
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Summary:It is difficult to give a fractional global threshold (FGT) that works well on all images as the image contents are totally different. This paper describes an interesting use of fractional calculus in the field of digital image processing. In the proposed method, the fractional global threshold-based edge detector (FGTED) is established using the Riemann–Liouville fractional integral operator. FGTED is used to find the microedges in minimum time for any input digital images. The results demonstrate that the FGTED outperforms conventional techniques for detecting microtype edges. The image with a higher entropy was produced by the FGT value-based approach. Tables and images are used to summarize the output performance analysis of various images using structural similarity index measure, F-score (F-measure), precision and recall, signal-to-noise ratio, peak signal-to-noise ratio, and computational time. The FGTED can be used to detect very thin or microtype edges more accurately in minimum time without training or prior knowledge.
ISSN:1024-123X
1563-5147
DOI:10.1155/2024/9266585