A Python Class for Neutrosophic Morphology

In this work, we introduce a Python class, named NSmorph, developed to facilitate image manip ulation through neutrosophic morphological operations. This innovative approach extends traditional image processing 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.