  In this paper, we propose a novel set of features for offline writer
identification based on the path signature approach, which provides a
principled way to express information contained in a path. By extracting local
pathlets from handwriting contours, the path signature can also characterize
the offline handwriting style. A codebook method based on the log path
signature---a more compact way to express the path signature---is used in this
work and shows competitive results on several benchmark offline writer
identification datasets, namely the IAM, Firemaker, CVL and ICDAR2013 writer
identification contest dataset.
