Continuous efforts have been made to improve the robustness of iris coding methods, since Daugman’s pioneering work [5] on iris recognition was published. Iris recognition is presently used in several scenarios (airport check-in, refugees control,. . . ) with very satisfactory results. However, in order to achieve acceptable error rates several imaging constraints are enforced, which reduce the fluidity of iris recognition systems. The majority of the published iris recognition methods follow the statistical pattern recognition paradigm and encode the iris texture information through phase, zero-crossing or textureanalysis based methods. In this paper we propose a method that follows the structural (syntactic) pattern recognition paradigm. Besides the intrinsic advantages of this type of approaches (intuitive description and human-perception of the system functioning), our experiments show that the proposed method behaves comparably to the statistical approach that constitutes the basis of nearly all deployed systems.