Character-level Chinese Writer Identification using Path Signature Feature, DropStroke and Deep CNN

Understand

Most existing online writer-identification systems require that the text content is supplied in advance and rely on separately designed features and classifiers.

• The identifications are based on lines of text, entire paragraphs, or entire documents; however, these materials are not always available.
• In this paper, we introduce a path-signature feature to an end-to-end text-independent writer-identification system with a deep convolutional neural network (DCNN).
• Because deep models require a considerable amount of data to achieve good performance, we propose a data-augmentation method named DropStroke to enrich personal handwriting.