Binarization and cleanup of handwritten text from carbon copy medical form images

Authors:
Robert Milewski;Venu Govindaraju
Affiliations:
Center of Excellence for Document Analysis and Recognition, University at Buffalo, UB Commons, 520 Lee Entrance, Suite 202, Amherst NY 14228, USA;Center of Excellence for Document Analysis and Recognition, University at Buffalo, UB Commons, 520 Lee Entrance, Suite 202, Amherst NY 14228, USA
Venue:
Pattern Recognition
Year:
2008

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Abstract

This paper presents a methodology for separating handwritten foreground pixels, from background pixels, in carbon copied medical forms. Comparisons between prior and proposed techniques are illustrated. This study involves the analysis of the New York State (NYS) Department of Health (DoH) Pre-Hospital Care Report (PCR) [Western Regional Emergency Medical Services, Bureau of Emergency Medical Services, New York State (NYS) Department of Health (DoH), Prehospital Care Report v4.] which is a standard form used in New York by all Basic and Advanced Life Support pre-hospital health care professionals to document patient status in the emergency environment. The forms suffer from extreme carbon mesh noise, varying handwriting pressure sensitivity issues, and smudging which are further complicated by the writing environment. Extraction of handwriting from these medical forms is a vital step in automating emergency medical health surveillance systems.