Data di Pubblicazione:
2024
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.
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.
Tipologia CRIS:
14.a.1 Articolo su rivista
Keywords:
neutrosophic set, neutrosophic morphology, morphological image processing, Python programming, uncertainty in image analysis.
Elenco autori:
Affe, Lorenzo; Nordo, Giorgio; Smarandache, Florentin
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