Retrieval of Handwritten Lines in Historical Documents

Abstract

This study describes methods for the retrieval of handwritten lines of text in a historical administrative collection. The goal is to develop generic methods for bootstrapping the retrieval system from a tabula rasa starting condition, i.e., the virtual absence of labeled samples. By exploiting the currently available computing power and the fact that computation takes place off line, it should be possible to provide a good starting point for statistical learning methods. In this manner, a closed collection can be incrementally indexed. A cross-correlation method on line-strip images is presented and results are compared to feature-based methods.