A vision mamba-enhanced network with frequency-directional feature fusion for pavement crack segmentation

Key Points

• Improved crack segmentation accuracy leads to more reliable pavement assessments, and shows significant advancements over traditional methods.
• The study reports a 15% increase in segmentation accuracy, with precise identification of cracks across various pavement types.
• Application of a vision mamba-enhanced network in image processing effectively integrates frequency-directional feature fusion techniques.
• Results highlight the potential for better infrastructure maintenance through advanced segmentation methods, but further validation is needed.