Imagine trying to find a face in a crowd. If we know what the face looks like we could search for it at every possible location — this is the essence of template matching. To make it work we need to describe how similar each area we are checking is to the reference face image and we discuss a number of similarity measures such as sum of absolute differences (SAD, ZSAD), sum of squared differences (SSD, ZSSD) and normalized cross correlation (NCC, ZNCC). We also invesigate the effect of intensity scale and offset error on the performance of these measures.