(eng): In this paper, we show that methods detecting multiple change points in a discrete distribution of variables can play an effective role in identifying image tampering. Methods analyzing change points deal with detecting abrupt changes in the characteristics of signals. Methods dealing with detecting image tampering isolate a subset of the given image that is significantly different from the rest. Apparently, both groups of methods have similar goals and thus there might be an interesting synergy between these two research fields. Change points detection algorithms can help in automatically detecting altered parts of digital images without any previous training or complicated threshold settings.