Recognition of hand-printed characters via Induct-RDR

The goal of character recognition research is to simplify and automate the development of character recognition algorithms. We describe an approach based on applying preprocessing to data sets of Latin characters and then applying a machine learning approach to the data sets to build a knowledge base able to classify unseen pre-processed characters. The machine learning method, Induct/RDR, has a number of features that make it particularly suitable for character recognition. It has the potential to integrate automatic analysis with a manual knowledge acquisition methodology if further refinement is required. Initial results on hand-printed Latin characters show the recognition accuracy of up to 90.2% on unseen cases for the machine learning system.