The integral image representation is a remarkable idea that permits to evaluate the sum ofimage values over rectangular regions of the image with four operations, regardless of the size ofthe region. It was first proposed under the name of summed area table in the computer graphicscommunity by Crow’84, in order to efficiently filter texture maps. It was later popularized in thecomputer vision community by Viola & Jones’04 with its use in their real-time object detectionframework. In this article we describe the integral image algorithm and study its application inthe context of block matching. We investigate tradeoffs and the limits of the performance gainwith respect to exhaustive block matching.