Optical Character Recognition of Off-Line Typed and Handwritten English Text Using Morphological and Template Matching Techniques

Olakanmi Olufemi Oladayo (University of Ibadan)

IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 3, No 3: September 2014

The existence of several documents in historical archives which need to be edited and stored in a computer has been one of the drives of Optical Character Reader (OCR) research. Earlier scanner has been used to achieve this tedious task however scanner only produces picture images of the documents.This makes the documents unreadable and un-editable through other word processing applications.This paper proposed an OCR system which converts off line typed and handwritten texts into their editable textual representations.The morphological correlation technique improves the mapping and recognition efficiency of the OCR system.