Evolutionary algorithms have been explored to aid creative tasks such as graphic design, e.g. by speeding up the creative process through the generation of innovative visual solutions that designers may get inspired by or may use as a starting point for their work. However, state-of-the-art systems often present shortcomings in controlling the legibility of the text contents present in the generated artefacts. This paper presents an ocr based approach for evaluating the legibility degree of communication artefacts, such as graphic design posters. We experiment with various metrics to compare the detected with the original text of the posters. To test these metrics, the respective results are compared with human evaluations of legibility. Furthermore, posters are evolved using the proposed approach as a fitness metric. Our findings suggest the developed metrics are more closely aligned with human evaluations. Also, the results indicate our approach can be successfully utilised to generate legible posters.