Digital image correlation and integration of artificial intelligence with infrared thermography for defect mapping in concrete

Non-Destructive Testing (NDT) is critical for ascertaining the integrity, durability, and service life of concrete structures without causing any damage. This review paper explores various NDT methods, with a particular emphasis on digital image correlation (DIC) and the integration of artificial intelligence (AI) with infrared thermography for defect mapping. As an advanced optical technique, DIC delivers high-precision strain and crack analysis by capturing surface deformations through sophisticated imaging and data processing. Whereas DIC offers significant potential, its use in large-scale, field-based applications is still limited due to challenges related to cost, complex data interpretation, and the need for specialized expertise. Integrating AI with infrared thermography further facilitates defect mapping for improved service life assessment. The underlying principles, applications, strengths, and limitations are comprehensively examined, offering a clear comparison of their effectiveness in concrete evaluations. This comprehensive review clarifies how these NDT techniques complement each other, highlighting research gaps and opportunities for improvement. Such innovations pave the way for more robust and reliable practices in evaluating concrete structures, ultimately improving the safety and longevity of infrastructure.