Light Propagation and Multi-Scale Enhanced DeepLabV3+ for Underwater Crack Detection

Achieving state-of-the-art performance (82.5% IoU, 85.6% F1), this paper proposes an enhanced DeepLabV3+ model for robust underwater crack detection through three integrated innovations: a physics-based light propagation correction model for illumination distortion, multi-scale feature extraction for variable crack dimensions, and curvature flow-guided loss for boundary precision. Our approach significantly outperforms DeepLabV3+, SCTNet, and LarvSeg by 10.6–13.4% IoU, demonstrating particular strength in detecting small cracks (78.1% IoU) under challenging low-light/high-turbidity conditions. The solution provides a practical framework for automated underwater infrastructure inspection.