Sum of square difference (SSD) and normalized cross correlation (NCC) are two different template matching techniques and their fast implementations have been investigated independently. The SSD approach is known to be simple and fast, however it is variant to image intensity change that lead to low performance. On the other hand, the NCC method is invariant to intensity change and has high performance, but its computational cost is high. In this paper, we derive an equation that connects NCC and SSD. From this equation, we propose SSD based partial elimination for the fast implementation of NCC template matching. This new technique takes the advantages of both NCC’s high performance and SSD’s low computational cost. It is fast and has high performance. Then we propose a uniform smoothing approach that further reduces computational cost for NCC. Experiments show that the proposed method is significantly faster than the techniques reported in literature.