Population studies often incorporate capture-mark-recapture (CMR) techniques to gather information on long-term biological and demographic characteristics. A fundamental requirement for CMR studies is that an individual must be uniquely and permanently marked to ensure reliable reidentification throughout its lifespan. Photographic identification involving automated photographic identification software has become a popular and efficient non-invasive method for identifying individuals based on natural markings. However, few studies have a) robustly assessed the performance of automated programs by using a double-marking system or b) determined their efficacy for long-term studies by incorporating multi-year data. Here, we evaluated the performance of the program Interactive Individual Identification System (I³S) by cross-validating photographic identifications based on the head scale pattern of the prairie lizard (Sceloporus consobrinus) with individual microsatellite genotyping (N=863). Further, we assessed the efficacy of the program to identify individuals over time by comparing error rates between within-year and between-year recaptures. Recaptured lizards were correctly identified by I³S in 94.1% of cases. We estimated a false rejection rate (FRR) of 5.9% and a false acceptance rate (FAR) of 0%. By using I³S we correctly identified 97.8% of within-year recaptures (FRR=2.2%; FAR=0%) and 91.1% of between-year recaptures (FRR=8.9%; FAR=0%). Misidentifications were primarily due to poor photo quality (N=4). However, two misidentifications were caused by indistinct scale configuration due to scale damage (N=1) and ontogenetic changes in head scalation between capture events (N=1). We conclude that automated photographic identification based on head scale patterns is a reliable and accurate method for identifying individuals over time. Because many lizard or reptilian species possess variable head squamation, this method has potential for successful application in many species.