A text feature-based recognition registration method is proposed to address the problems that the accuracy of the augmented reality recognition registration is prone to be affected by textures and that there is lack of text-based recognition targets. In template imaging processing, two sampling methods,i.e., downsampling and 2 power-based sampling,are combined to construct a multi-scale pyramid, achieving scale invariance. The text feature points are extracted based on an improved algorithm that uses fast retina keypoint (FREAK). Finally, the augmented reality system based on text features is realized. The experimental results show that the proposed algorithm can extract text feature points accurately and reduce the effect of the texture on accuracy, and it is applicable to the recognition registration for text images. Further, the augmented reality system based on the improved method can realize recognition registration in the situation that the target is partially obscured under different scales.