An evolutionary algorithm is used to search for iterated function systems (IFS) that can encode black and white images. As the number of maps of the IFS that encodes an image cannot be known in advance, a variable-length genotype is used to represent candidate solutions, Accordingly, feasibility conditions of the maps are introduced, and special genetic operators that maintain and control their feasibility are defined, In addition, several similarity measures are used to define different fitness functions for experimentation. The performance of the proposed methods is tested on a set of binary images, and experimental results are reported.