This paper has the following contributions in iris recognition compass: first, novel parameters selection for Gabor filters to extract the iris features. Second, due to iris textures randomness and assigning the Gabor parameters by pre-knowledgeable values, traditionally, a large Gabor filter bank has been used to prevent losing the discriminative information. It leads to perform extracting and matching the features heavily and on the other hand, the generated feature vectors are lengthened as required for extra storage space. We have proposed and compared two different approaches based on Genetic Algorithm to reduce the system complexity: optimizing the Gabor parameters and feature selection. Third, proposing a novel encoding strategy based on the texture variations to generate compact iris codes. The experimental results show that generated iris codes by optimizing the Gabor parameters approach is more distinctive and compact than ones based on feature selection approach.