The invention relates to a method for distinguishing false iris images based on robust texture features and machine learning, which comprises the following steps: preprocessing true iris images or false iris images; extracting the partitioned statistical features of a robust weighted partial binary pattern; and carrying out training and sorting of a support vector machine, and judging whether thetest images are false iris images or not according to the output result of a sorter. The method of the invention combines SIFT descriptors and partial binary pattern features to extract the robust texture features, the description of textures is more stable because of the robustness of the SIFT to brightness, translation, rotation and scale change, and the support vector machine enables the method to have better universality. The invention can be used for effectively distinguishing the false iris images, has the advantages of high precision, high robustness and high reliability, can be used for distinguishing false irises such as paper printing irises, color printing contact lenses, synthetic eyes and the like, and can improve the safety of the system when being applied to the applicationsystem in which iris recognition is used for carrying out identification.