This paper presents a fractal image compression method that utilized a genetic optimization algorithm for optimal domain block selection. The technique successfully addresses the problem of finding an optimal domain block pool for a given range partition, one of the most important issues in fractal image compression. This technique utilizes a genetic optimization algorithm that starts with a source image and generates both a random range partition and a random set of candidate domain blocks for each element of the range partition. Each member of the candidate domain block set was mapped to the corresponding element of the range partition. It was subsequently tested via a quantitative objective function, ranked using a linear fitness scheme and modified, as required, using crossover and mutation operators. This evolutionary process converged to produce an optimal iterated function system (IFS) representation of the source image within a few generations in a robust and efficient manner. © 1999 John Wiley & Sons, Inc. Int J Imaging Syst Technol 10, 369–378, 1999