In Hong Kong, there is great abundancy of aged buildings and infrastructures for which a re-assessment of the current status is needed. Water exfiltrations/infiltrations, deteriorating insulations, thermal bridges and regions of failure are among the most recurrent symptoms to be found in existing Reinforced Concrete (RC) structures. Diagnosis of such symptoms, in the form of thermal infrared anomalies, is usually performed through infrared (IR) image capturing, followed by qualitative assessment. This paper presents a novel automated computer-vision-based method for detecting thermal anomalies. Such Computer-Vision (CV) algorithm is tested on different thermal scenarios including beam elements, roofs and entire façades of RC buildings. Thermal anomalies related to cases of water leakages, moisture trapping and debonding are successfully detected. The authors intend to undertake further research for successfully implementing the method for detecting also other thermal dissimilarities.