Discrimination of machine-printed from handwritten text using simple structural characteristics
Ergina Kavallieratou, S. Stamatatos · Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. · 2004
In this paper, we present a trainable approach to discriminate between machine-printed and handwritten text. An integrated system able to localize text areas and split them in text-lines is used. A set of simple and easy-to-compute structural characteristics that capture the differences between machine-printed and handwritten text-lines is introduced. Experiments on document images taken from IAM-DB and GRUHD databases show a remarkable performance of the proposed approach that requires minimal training data.