Meaningful alignments

We propose a method for detecting geometric structures in an image, without any a priori information. Roughly speaking, we say that an observed geomet ric event is "meaningful" if the expectation of its occurences would be ver y small in a random image. We discuss the apories of this definition, solve several of them by introducing "maximal meaningful events" and analyzing t heir structure. This methodology is applied to the detection of alignments in images.