Robust concrete crack recognition based on improved image segmentation and machine learning

This paper presents an automatical crack recognition approach. Compared with the existing methods, it has a significant increase in robustness and efficiency when faced with widely varying field conditions. Inherent characteristics of crack images are exploited using proportional segmentation, combined with robust feature extraction to improve machine learning classifier performance. Experiments show that this method perform well in crack images recognition across different concrete conditions.