Abstract Blur is an image degradation that makes object recognition challenging. Restoration approaches solve this problem via deblurring, deep learning methods rely on the augmentation of training sets. Invariants with respect to blur offer alternative way describing and recognising blurred images without any deblurring data augmentation. In paper, we present original theory invariants. Unlike...