The ‘signature’, from the theory of differential equations driven by rough paths, provides a very efficient way of characterizing curves. From a machine learning perspective, the elements of the signature can be used as a set of features for consumption by a classification algorithm.
Using datasets of letters, digits, Indian characters and Chinese characters, we see that this improves the accuracy of online character recognition—that is the task of reading characters represented as a collection of pen strokes.