Figure 1: (left) Several examples of handwritten text and shapes before and after beautification. The beautified results are found by shifting the strokes closer to means of token clusters. Notice how the beautified results are more consistent and easier to read, yet they still have the variation and style of the original writings. (right) Example tokens generated from writing "SIGGRAPH."
AbstractIn this paper, we propose a general purpose approach to handwriting beautification using online input from a stylus. Given a sample of writings, drawings, or sketches from the same user, our method improves a user's strokes in real-time as they are drawn. Our approach relies on one main insight. The appearance of the average of multiple instances of the same written word or shape is better than most of the individual instances. We utilize this observation using a two-stage approach. First, we propose an efficient real-time method for finding matching sets of stroke samples called tokens in a potentially large database of writings from a user. Second, we refine the user's most recently written strokes by averaging them with the matching tokens. Our approach works without handwriting recognition, and does not require a database of predefined letters, words, or shapes. Our results show improved results for a wide range of writing styles and drawings.