Handwriting Reconstruction for a Camera Pen Using Random Dot Patterns

This paper proposes a new method of handwriting reconstruction using a camera pen. We print random dot patterns on the document background to enable retrieval of both the current document and the pen position on this document. Dot arrangements are stored in a hash table using Locally Likely Arrangement Hashing. For retrieval, they are extracted from the camera image and matched to the corresponding points in the hash table. We were able to achieve high retrieval accuracy (81.1~100.0%), given a sufficient amount of visible dots. Using a two-step homography approximation, an accurate image of handwriting can be reconstructed. By using knowledge about document context and a client-server architecture, our method allows real-time processing on ordinary hardware.