The visibility of a traffic sign at night depends on its retro-reflectivity, a property that needs to be frequently monitored to ensure transportation safety. In the U.S., Federal Highway Administration (FHWA) maintains regulations to ensure minimum retro-reflectivity levels. Current measurement techniques either (a) use vehicle mounted device during the night, or (b) use manual handheld devices during the day. The former is expensive due to nighttime labor cost. The latter is time-consuming and unsafe. To address these limitations, this paper presents a computer vision-based technique to measure retro-reflectivity during daytime using a vehicle mounted device. The presented algorithms simulate nighttime visibility of traffic signs from images taken during daytime and measure their retro-reflectivity. The technique is faster, cheaper, and safer as it neither requires nighttime operation nor requires manual sign inspection. It also satisfies FHWA measurement guidelines both in terms of granularity and accuracy. The performance of the presented technique is evaluated under various testing conditions. The results are promising and demonstrate a strong potential in lowering inspection cost and improving safety in practical applications on retro-reflectivity measurement. 
Image-based retro-reflectivity measurement of traffic signs in day time