Accurate crack detection in concrete and pavement images is critical for infrastructure assessment but is limited by the scarcity of large, consistently annotated datasets. Supervised learning methods are particularly sensitive to data scarcity, often overfitting and generalizing poorly across crack types and imaging conditions. This study proposes a synthetic crack generation framework to augment or partially replace real dat...