Data-embedding pen-augmenting ink strokes with meta-information

In this paper we present the first operational version of the data-embedding pen. During writing a pattern, this pen produces an additional ink-dot sequence along the ink stroke of the pattern. The ink-dot sequence represents, for exam-ple, meta-information (such as the writer's name and the date of writing) and thus drastically increases the value of the handwriting on a physical paper. Since the information is placed on the paper, it can be extracted just by scanning or photographing the paper. There is no need to get access to any memory on the pen to recover the information. This is useful especially in multi-writer or multi-pen scenarios. The experiments using an encoding scheme and a decoding algorithm showed very promising results. For example, it was proved that we can embed 28 or more bits of informa-tion on simple handwritten patterns and decode them with a high reliability.