In this work, we introduce a Python class, named NSmorph, developed to facilitate image manipulation through neutrosophic morphological operations. This innovative approach extends traditional image rocessing methods by leveraging the flexibility of neutrosophic logic to handle uncertainty, indeterminacy, and noise in digital images. The class offers implementations of essential morphological operators, such as neu trosophic dilation, erosion, opening, and closing, providing a robust tool for applications where image clarity is often compromised, like medical imaging and surveillance. We detail the class structure and functions and provide multiple examples to demonstrate its practical applications and comparative advantages over classical morphological methods.

A Python Class for Neutrosophic Morphology

Lorenzo Affe
Primo
Investigation
;
Giorgio Nordo
Secondo
Investigation
;
2024-01-01

Abstract

In this work, we introduce a Python class, named NSmorph, developed to facilitate image manipulation through neutrosophic morphological operations. This innovative approach extends traditional image rocessing methods by leveraging the flexibility of neutrosophic logic to handle uncertainty, indeterminacy, and noise in digital images. The class offers implementations of essential morphological operators, such as neu trosophic dilation, erosion, opening, and closing, providing a robust tool for applications where image clarity is often compromised, like medical imaging and surveillance. We detail the class structure and functions and provide multiple examples to demonstrate its practical applications and comparative advantages over classical morphological methods.
2024
Inglese
STAMPA
University of New Mexico
76
500
519
20
https://fs.unm.edu/nss8/index.php/111/article/view/5217
no
Internazionale
Esperti anonimi
neutrosophic set, neutrosophic morphology, morphological image processing, Python programming, uncertainty in image analysis.
info:eu-repo/semantics/article
Affe, Lorenzo; Nordo, Giorgio; Smarandache, Florentin
14.a Contributo in Rivista::14.a.1 Articolo su rivista
3
262
open
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3318672
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